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Stephanie Rogers: yeah all right, well, I think we're gonna get started here so it's 130.

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Stephanie Rogers: Thank you everyone who's here for being here right now, I will just quickly organized.

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Stephanie Rogers: introduce the session organizers it's myself i'm stephanie Rogers from auburn the Department of geosciences we have Dr James or Jim connors.

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Stephanie Rogers: We have Edna Fernandez, and we have Dr kumar saying and you'll actually hear from them all today as we go along, so I won't take too much time introducing them.

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Stephanie Rogers: So just quickly an overview we're going to have three talks in a row, and then we are going to have a short break at 235 for 15 minutes, then we're going to come back and have two more talks and then.

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Stephanie Rogers: About 10 hopefully 1510 to 15 minutes for discussion.

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Stephanie Rogers: from everyone at the end so just a couple reminders that all of these talks are 17 minutes each with three minutes for questions and the moderators will time the speakers and tell you when the two minute mark.

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Stephanie Rogers: Is upon you, and the audience, please keep yourself muted and if you have questions in the question period just use the raise hand function, or you can type type out your question in the chat box as well.

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Stephanie Rogers: So.

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Stephanie Rogers: Those are the logistics of what's going to happen.

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Stephanie Rogers: We still have a couple minutes i'm sure we could get started early if we want is there any, are there any questions that anybody has before we get started.

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Stephanie Rogers: Alright, so I will ask.

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Stephanie Rogers: You to share your screen.

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Stephanie Rogers: Please.

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Stephanie Rogers: Okay excellent that so fast.

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Stephanie Rogers: And i'm going to try to.

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Stephanie Rogers: Do something fancy here hang on.

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kunwarsingh: So is it visible and are you guys able to hear me.

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Stephanie Rogers: Well, yes and yes.

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Stephanie Rogers: Great and i'm going to.

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Stephanie Rogers: We can't see you though I don't know if you have.

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kunwarsingh: I paused it, so I can I don't want to see myself.

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Stephanie Rogers: No problem.

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kunwarsingh: So they will distraction so.

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Stephanie Rogers: that's okay so.

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kunwarsingh: So let me know whenever I should start.

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kunwarsingh: Time did 15 minutes.

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kunwarsingh: Okay, give enough time for questions and interaction it's Friday afternoon, so we should not we should have time to discuss and talk quite fit.

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Stephanie Rogers: That sounds good.

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Stephanie Rogers: Well, there is some there is a chat message from cj he's our tech support here today, so everyone feel free to read that in the text box.

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Stephanie Rogers: And I think we might as well just go ahead and get started we're one minute early, but let me start my timer and i'll mute myself and take it away core.

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kunwarsingh: Well, thank you stephanie for the introduction and Hello everyone, it is pleasure to be here and thank you for attending my talk today I will talk about the burdens of drones and their practices in geography.

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kunwarsingh: Other Member Member involved in this project sorry stephanie who is our moderator Dr Anthony cummings is an assistant professor at the University of Texas at Dallas Dr Adam Matthew is an associate professor at Western Michigan university.

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kunwarsingh: While this talking light will be on time.

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kunwarsingh: i'll be happy to answer any question.

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kunwarsingh: During the presentation and after the presentation.

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kunwarsingh: To put this talk in the context.

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Of.

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kunwarsingh: inexpensive drones with precision technology have equipped geographers with the capacity to collect high quality geospatial data desire to solutions.

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kunwarsingh: Today, from novice to highly trained geospatial scientists are in gazing but drones to address geographic challenges, while the adoption of drones is increasing across the geography discipline our knowledge of.

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kunwarsingh: And emergence of drones and their practices in geography is unclear.

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kunwarsingh: drones have the potential to bring us more data, but this is always but is this always a positive outcome in the pursuit of geographical knowledge, we do not know, likewise, we hardly know.

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kunwarsingh: How does gender ethnicity and a's affects who uses drones, how is the use of drones in influencing the discipline how have grown drones impacted the trajectory of research teaching and the way we experience our surroundings.

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kunwarsingh: And what future opportunities are presented to geographers as they engage with drones remains unclear.

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kunwarsingh: We have noticed a strong connection between geography and technology over the years and that motivated us to find answers to these questions.

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kunwarsingh: to accomplish this we performed a web based survey we targeted faculty members scientists graduate students lab members to complete the survey.

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kunwarsingh: IRB was approved by auburn university we prepared the survey and call tricks oceans were focused on to three topics, the.

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kunwarsingh: Participants demographics and professional background drone users and experiences and opinions on the use of drones in geography.

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kunwarsingh: questions on the farmer two topics were commonly shark question answer answer questions the letter what letter set of questions we're open ended, which enabled participant to provide a little in depth part and opinion and what they they have experienced over the years.

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kunwarsingh: We we disseminated the survey via email spirit speciality group lists are including twitter's.

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kunwarsingh: survey can have a subway have had 20 cautions and we're avail and subway was available from September 30 2022 number first 2020.

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kunwarsingh: We received in total 88 responses we also an ominous data to protect the spot responders identity and perform the data.

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kunwarsingh: Pre processing before we double up the summary statistics frequencies and percentages, we also created a word cloud provide a graphical summary of all open ended responses were font size.

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kunwarsingh: Was professional professional professional to word frequency if frequency of any word was less than 10 be removed that word from the word cloud.

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kunwarsingh: outcomes were interesting and very informative our study suggests that almost 85% of geographers that uses drone and research and teaching our wide.

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kunwarsingh: Approximately 30% of female geographers users drone but the ratio is much higher at the at the age of 18 to 24 the traditional faculty and graduate students, they cumulatively constitute more than 50% of the population.

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kunwarsingh: Asian and Hispanic drug for some reason they call population approximately 5% each with the majority means almost 90% being faculty members and fall in between the age of 25 and 44 eight for.

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kunwarsingh: The Asian and Hispanic male geographers represents almost 7% of the total population, but white male constitute more than 87% and surprisingly good representation from black African American Community.

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kunwarsingh: Interestingly, while the word.

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kunwarsingh: drone has a negative connotation many geographers prefer using this term.

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kunwarsingh: followed by unmanned.

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kunwarsingh: unmanned aerial vehicle and unmanned aerial system.

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kunwarsingh: Apart from this, many female geographer well interestingly, many female geographers preferred using either us uab acronym over drones in academic research and in daily user settings.

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kunwarsingh: Abroad approximately 40% of geographers exclusively used.

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kunwarsingh: drones and research, followed by approximately 30% in both teaching and research.

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kunwarsingh: The expertise of 40% of drone users is in geographic techniques, followed by 20% in physical geography.

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kunwarsingh: Only 22% of drone geographers had more than 6% of experience experience.

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kunwarsingh: Approximately 25% of geographers collect imagery our data twice or more per month, however many.

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kunwarsingh: There was.

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kunwarsingh: What we obviously have that many of you just collect the misery.

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kunwarsingh: Only once per month.

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kunwarsingh: 30 32% percent per semester.

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kunwarsingh: Approximately 6% but once in academic year.

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kunwarsingh: So it varied, but only 25% of geography geographers collect imagery.

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kunwarsingh: more than twice per month.

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kunwarsingh: Approximately 40 54% of total geographers carry a drone pilot license license issued either.

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kunwarsingh: means the United States, Miss almost 36% they were issued by the United States and our primary person by United Kingdom.

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kunwarsingh: Many geographies bit and without drone pilot license you use various versions various versions of off the cell phone system off the self and don't even drones are the most desirable.

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kunwarsingh: Perhaps that because that look awesome.

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kunwarsingh: easy to use.

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kunwarsingh: And this slide basically represents word cloud and the font size is basically.

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kunwarsingh: proportional to the word frequency and, as you see drone and data were mentioned very frequently, followed by a remote sensing high resolution and technology, this search and students were also frequently repeated.

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kunwarsingh: Which attest to the importance of don't users in both research and instruction for the sample group.

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kunwarsingh: On the, on the other hand.

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kunwarsingh: Open ended questions.

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kunwarsingh: That.

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kunwarsingh: There are four open ended question first one is here, how do drones positively or negatively or otherwise influence the discipline of geography geography.

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kunwarsingh: And certainly what we noticed was that the respondents were very positive regarding how drones influence that discipline of geography.

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kunwarsingh: Nearly all the respondent mentioned that drones provide unparalleled opportunity for geographers to obtain a high resolution data even one is stated that.

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kunwarsingh: don't have democratized remote sensing while others echoed this by noting how don't facilitate data collection by.

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kunwarsingh: more diverse users many responded or respondents.

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kunwarsingh: articulated that drone for the cool factor that attract the strength to geography courses and programs many responded all respondents also stated that tones enables geographers to get back into the field in both instructional and research capacity.

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kunwarsingh: Some respondents mentioned that also mentioned negative aspects, with the donor adoption and geography.

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kunwarsingh: One particular.

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kunwarsingh: responded mentioned that in an era of big data don't provides too much data and not enough time to research everything and enable the fantasies of overly precise data.

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kunwarsingh: and similar similarly few other responded noted potential misuse of drones and ethical issue the searches with the highest spatial resolution is looking.

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kunwarsingh: For the second open ended question how has drone technology changed the work that we do.

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kunwarsingh: It despondent is stressed how drone technology had changed what and how they teach many noted altering your.

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kunwarsingh: Open geospatial courses to incorporate elements of what drones have miss Jones offers geographers but some mentioned creation of new don't focus remote sensing courses.

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kunwarsingh: and remote and respond respondents also emphasize that drone could support active beta particle approaches as tools for data collection and inch and.

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kunwarsingh: instruments that increase fieldwork.

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kunwarsingh: Other side one as a unique tool to link strength to the local community enabling citizen science and outreach.

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kunwarsingh: For the third open ended question what future opportunities to drone respondent drones present two geographers and the discipline of geography.

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kunwarsingh: Some is stress the importance of job parts of geography, is to own this area of drones for mapping don't provide a new office by the citation between geography and provide a great opportunity for academic geography.

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kunwarsingh: Regarding a scholarship many research respondents indicated that drone provides jagger for a new ability to address the research question that might have not been possible.

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kunwarsingh: Prior to using drone technology one respondents said that don't enable the measurement of thing that we cannot measure in other in other ways.

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kunwarsingh: In terms of instruction responded noted how going based remote sensing is much less abstract for students, compared to other form of remote sensing such as area domains is airborne I space mark remote sensing.

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kunwarsingh: hands on demonstration of drones for geospatial data collection and creation can can be carried out quickly and therefore it's practical for an instructor to adopt in courses.

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kunwarsingh: majority of the in response to the beach cody's caution, they are positive and that extremely positive, and as soon as the for the last open ended question, do you think students should be exposed to using drones in geography.

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kunwarsingh: Almost.

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kunwarsingh: 95% more than 95% responded answer yes to this question.

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kunwarsingh: And I will read this quote one of the respondents said that it is a new and rapidly growing technology that.

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kunwarsingh: That will only become more integrated with the study of geography and geosciences much like collecting GPS data and using GIs was in.

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kunwarsingh: 20 years ago and, in fact, one stated that technology can be applied in all realms of geographic inquiry, then it is a skill set that all contemporary geography geography students should be exposed to.

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kunwarsingh: And not surprisingly, given the history of this discipline responded also said that geography, has a bit a bit of identity crisis but.

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kunwarsingh: But that drone can help to change your perception perception in the in this space other reflected that ignoring such technology would be detrimental to the advancement of discipline and it's just stood.

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kunwarsingh: Over all the service souls how.

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kunwarsingh: geographers have embraced on one of the responded road that more data more chaos and more excitement that search.

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kunwarsingh: To highlight the sentiment of Tony users in the system, moving forward.

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kunwarsingh: It is important that geography agree upon a single term to refer to refer this technology as you notice, as you note notice that throughout the presentation, I mean, so I repeated drones and it's because.

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kunwarsingh: responded they even they.

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kunwarsingh: indicated one other acronym but they use drones in the description that shows that.

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kunwarsingh: It will be, it would be realistic, are useful to either use.

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kunwarsingh: drone.

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kunwarsingh: unmanned aircraft system.

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kunwarsingh: Based on based on our survey simply using drone, as we have provides a jargon free terms were term.

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kunwarsingh: geographer must also find a balance between data collection frequency, especially vision mission and quality i'm sure you have noticed that.

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kunwarsingh: Those who collects data.

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kunwarsingh: Two aspects of collecting data collection excites them the most one is flying the drone and other in other one is higher resolution means if data is sub centimeter centimeter level, they are the happiest one, not necessarily they can use that level of the data and one.

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Stephanie Rogers: color is that one one minute left sorry to interrupt you.

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kunwarsingh: I have, I need 30 seconds only.

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kunwarsingh: So what aspect of this survey is very crucial and important more than 75% female participant at the youngest is between 18 and 25 give us much more hope and encouragement for the future of geography.

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kunwarsingh: As a drone may have the power to improve gender and ethnicity ethnic ethnicity group with exciting resources to draw.

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kunwarsingh: Diverse population in the field and as to conclude this presentation, I will say that job of his throne have that capacity and tools and excitement that can bring a lot to the to the geography and can.

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kunwarsingh: Along with data and people student and just so says assets that's the end of the presentation, thank you.

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Stephanie Rogers: Excellent Thank you very much.

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Stephanie Rogers: You can stop sharing your screen, if you like, and we will open up the floor to.

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Stephanie Rogers: Questions so.

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Stephanie Rogers: There are any hands raised so if anyone just wants to unmute themselves and ask a question, you are more than welcome to do so.

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Ann Ojeda: If I had a question.

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Stephanie Rogers: Sure go ahead and.

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Ann Ojeda: hi great presentation, thank you um my question is about the.

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Ann Ojeda: geographic distribution of your respondents I would assume that they're connected, you know you sent these surveys out so it's people that you're connected to um did you see did you track that through politics.

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Ann Ojeda: Where these people these journeys are coming from.

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Ann Ojeda: well.

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Stephanie Rogers: you're you're muted color color.

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kunwarsingh: Sorry, so so despondent they were from across the globe is various part of the world from Australia UK.

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kunwarsingh: Saudi Arabia and Canada, and so they were from various parts of the world majority, they were from the United States.

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kunwarsingh: And to, as I mentioned the presentation to hide their identity, we remove that details we just had a what they said about drones and how what what are their demography, be at be presented, that in this presentation, as well as a publication via summit.

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Stephanie Rogers: cool thanks OK, I see and now has a question.

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Edna Fernandez: um so I was wondering if anybody talked about whether or not they started off analyzing satellite data and then moved into drones like is that a typical pathway or are these people only utilizing drones for the research.

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kunwarsingh: that's good question, and there was not an indication, but.

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kunwarsingh: Flying drone is one aspect and collecting and analyzing That is another aspect, so if any person who wanted to analyze they must have remote sensing background and that comes from.

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kunwarsingh: Using some of the basic remote sensing beta then getting into the drone so if.

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kunwarsingh: To answer your question, we did do we do not have that response on the response on that particular question, but we are we assume that because fundamental comes from mostly airborne space on satellite data, so I assume they just have that.

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Stephanie Rogers: um do you mind if I comment on that to come more.

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kunwarsingh: Sure sure sure.

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Stephanie Rogers: So what we did see come up a couple times was that.

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Stephanie Rogers: drones made it easier and more readily.

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Stephanie Rogers: People were able to conceptualize the whole process because they could see you know they see this tool that is being flown in the air that is allowing you to collect imagery and.

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Stephanie Rogers: satellites are so abstract because you know they're massive things orbiting the earth that nobody can really conceptualize so a lot of people mentioned that.

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Stephanie Rogers: It was just easier for students to start to complete a project from start to finish, because they could physically put their hands on this machine that was going to collect the data for them.

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Stephanie Rogers: And then analyze the data, whereas, sometimes with satellite imagery it's really difficult to wrap your head around where the data are coming from.

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Edna Fernandez: yeah great.

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True.

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Stephanie Rogers: Okay excellent I don't see any more hands raise, so let us move on to our second speaker, which is Jim connors who's a professional genealogist and a consultant as well, so Jim if you would like to share your screen would be great.

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James Connors: i'd like to.

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Stephanie Rogers: All right.

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James Connors: Let me know when it happens.

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Stephanie Rogers: it's coming up yes we're good to go great thank it away.

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James Connors: Of all right well welcome everybody as.

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James Connors: stephanie said, my name is Jim connors i'm a professional genealogist i'm sort of semi retired i've spent a lot of time in the consulting industry and also some time in academia doing a few things.

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James Connors: What i'm going to talk to you about today is the role of drones aerial drones in expert witness testimony and opinions, which is the majority of what i'm doing nowadays so i'm going to jump to the next slide here if my computer will cooperate.

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James Connors: When you when you qualify in court as an expert and some of you probably have done this kind of work, you go through a process where.

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James Connors: it's called voice dear and that's basically an old Norman term that means to speak the truth and they asked about your qualifications and they determine or make a determination as to whether or not you'll be.

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James Connors: allowed to opine in that particular procedure, so I the.

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James Connors: background of myself is, I have a bs Ms in geology PhD and marine sciences.

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James Connors: I am a practicing professional geologists have been since 94, and that is.

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James Connors: Even though i'm extremely old.

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James Connors: I currently have a license in Alabama Louisiana Mississippi New York in Texas.

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James Connors: I have 35 plus years of consulting experience i'm at that age that I I say plus i'm also 30 plus years old, but a lot of that is focused on groundwater contamination.

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James Connors: Groundwater flow water supply from groundwater also surface water hydrology including storm water very much focused on storm water and the environmental impacts associated with those things.

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James Connors: Also, but 10 plus years of academia started out as an instructor.

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James Connors: became an associate Professor before it was all over taught geology hydrology hydrogeologist geophysics other courses that were related awards, etc, etc.

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James Connors: I think I upset the President he made me be the.

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James Connors: Interim Dean interim Vice President for research.

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James Connors: associate Dean, I was even the director of international education for about 18 months, so I was really in the doghouse.

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James Connors: Now the expert.

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James Connors: Their standards as to who can.

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James Connors: opine in a court case and what your opinions can be the process we just went through making sure that you have the qualifications to do it very important.

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James Connors: The dog Burt standard is probably the number one thing that people look at nowadays, as far as whether your opinions can be valid and appear in court.

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James Connors: And that comes from a case called delbert versus Meryl TAO pharmaceuticals 1993 in that case, there was a drug that was given to pregnant women who.

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James Connors: Had nausea issues and there was the idea that somehow that was causing birth defects, so the dilbert family sued Merrill Dell pharmaceuticals, the producer of the drug.

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James Connors: And it went to court and the judge ruled summary judgment in favor of America down basically.

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James Connors: At the end of the presentation of the plaintiffs case they said you haven't proved it the experts on Meryl dal side we're relying on generally accepted science and that was that there wasn't an issue.

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James Connors: The dark side the plaintiff side had scientist who were saying yeah but they're these things, these animals studies these statistical analyses that we've done.

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James Connors: So it was thrown out because back at that time, if you didn't use generally accepted science or conclusions.

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James Connors: What was called the fried test from another case back in 1923.

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James Connors: It wasn't something that could be admitted in court.

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James Connors: Well, that was appealed the appellate Court upheld the decision and it was appealed again to the Supreme Court, and they basically threw it out completely threw it out.

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James Connors: But they basically changed the way expert witness work in testimony is accepted and done in what's called the double standard.

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James Connors: They decided that the Federal rules of evidence, specifically real 702 superseded the fright test and that while general acceptance by the scientific community was instructive wasn't necessary.

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James Connors: That, if there was good science behind it good methodology, the opinion could be accepted in court so under Rule 702 experts are defined as people who are qualified by knowledge skill experience training or education and any of the above.

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James Connors: they're basically disinterested third parties are educators and their job is to help the Trier of fact, which is the judge or the jury to understand the evidence or determine some issue of importance of relevance in the case.

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James Connors: Their testimony and opinions have to be based on sufficient data and facts, they have to be the product of reliable principles and methods, most importantly, the scientific method.

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James Connors: And the reliability.

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James Connors: of their method is also tied into the the the actual facts of this particular case, so it has to be relevant to the case itself well this open the door in a lot of ways for a lot of new science, a new ideas and also new techniques which is really where drones come in.

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James Connors: So drones you probably all know this, but they've the concept of drones and the idea of remote.

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James Connors: actions have been used by the military for quite a while in the mid 1800s the Austrians laid siege to Venice and they released a swarm of hundreds of incendiary balloons, most of which actually blue back on them by 1916 and we're we're to power drones were first being used.

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James Connors: Radio control was being implemented in moving drones or controlling them post World War Two TV was beginning to become something that was used in 1960.

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James Connors: The United States had a you to spy planes shot down over the Soviet Union pilot was captured and that really put the military into gear to develop drone technology.

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James Connors: To take human beings out of those dangerous positions, but still gather the data they needed they were used extensively in Vietnam Sue as the young computer war, the Israelis and the Yom Kippur war use them as.

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James Connors: As decoys trying to get the Egyptians to use up their very expensive high tech surface to air missiles.

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James Connors: We think about these things as being just a big part of our society they're really remarkably new.

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James Connors: By 2006 non military use of drones by the government, primarily in large corporations was becoming more commonplace that you could fly large areas like pipelines and look for leaks, or you could could use them in a disaster response, like a overturned hazardous train.

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James Connors: of interest when you look at the statistics between 2006 and 2014 the FAA only issued 16 commercial drone permits but that's about how many were requested.

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James Connors: Then in 2015 to the big story breaks Amazon is going to use drones for delivery, potentially, and it seems to capture the imagination and, since then, if you look at the number of of permits, there have been thousands upon thousands and just is accelerating.

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James Connors: In my practice as an expert witness I have six drones I have my own little air force certainly dated and I have to 3dr solos, I have three.

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James Connors: dji phantom threes one is a professional the other two are standards and also carry around a little tello selfie drone in my briefcase that I can just throw up into the air.

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James Connors: I call it the golden snitch so it helps me out to do some quick reconnaissance.

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James Connors: examples of how i've used drones in cases.

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James Connors: include this one, this was a situation where, if you look at the bottom right hand side of that screen there's a neighborhood just off the the photograph.

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James Connors: And at the very bottom of that neighborhood literally the bottom, there was a House that was flooded on numerous occasions by.

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James Connors: By rainfall events and it and it became more and more frequent and that's because everything up stream was being developed as a very rapidly growing part of the country.

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James Connors: This is an area that a big sports complex was built and it actually drains into the only place that water had to go back behind that residence is a very tragic case and people lost their house, it became overrun with mold they became sick ultimately it worked out in their favor.

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James Connors: here's an example where erosion was a big issue, there was the taking of sediments soils from an area and it was causing a tremendous amount of erosion, these are 40 foot cliffs here.

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James Connors: That have been dug out, and you can see all the erosion sedimentation very hard to really get a perspective on it when you're standing on the ground up in the air, with a drone and it's very instructive.

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James Connors: here's another case of erosion, leading to sedimentation in a very high priced.

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James Connors: Coastal.

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James Connors: result residents, you can see, in that first photo on the left.

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James Connors: This area of sediment building out that eventually encompasses all the way out to that boathouse, which is about.

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James Connors: Probably 50 yards out into the bay.

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James Connors: On the right hand side you see how it's supposed to look, this was years before.

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James Connors: engineers stream had a God God love our engineers, they had built a structure to control erosion that actually went up causing more erosion.

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James Connors: This is a case that I did in Houston where there was flooding associated with hurricane Harvey.

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James Connors: which was certainly, by all accounts, an act of God event, and that was the opinion that I had that, even though there was damage that was done, also in a residential area some some very high price real estate.

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James Connors: There was a lot of slip failures, this was something that no one could have foreseen or could have somehow defend it against there was no duty that you could pin, on the other side for for making that not happen.

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James Connors: here's a case where that commercial building in the photograph on the left.

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James Connors: regularly flooded and the owners blamed.

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James Connors: On auto you pull it parts junkyard thing that was down at the bottom of that photograph heading up a hill.

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James Connors: And Sure enough, they had deforested about 10 acres and increase run off dramatically and put all their their old cars and things out there was actually pretty clean operation but.

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James Connors: The the flooding.

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James Connors: was something that lift all these sediment deposits, that you can see right here around that door well when I went back and compared my drone footage to.

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James Connors: aerial photos taken many, many years before back when that hillside was still forced it you still saw this gravel and coarse grained sand being deposited on a regular basis, after rainfall events, indicating that that was not the only contributing factor.

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James Connors: here's an issue of timidity and a lawsuit these these ponds are being choked by fine grain sediment very hard to get to not with a drone.

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James Connors: Issues of environmental compliance, this is a landfill, and that is all supposed to be covered up every day it's called daily cover and very obviously in this case it's not being.

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James Connors: Here is an issue of compliance with stormwater regulations, these are best management practices that are pretty shoddy and we could see them on a large scale, with our drones.

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James Connors: topographical mapping very often on on in situations where water flow has changed over time and I may have remarkably good.

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James Connors: topographical maps from lidar or other imagery but I don't have anything now well even drones as simple as the ones that I have can be geared up to do pretty detailed topographical.

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James Connors: mapping on a survey level so that they can not even necessarily have to fly over specific areas, but they can get a very good idea about the the tub graphical really wetlands remarkably useful in wetlands because.

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James Connors: You go out into a wetland your, by definition, causing damages and in their snakes and things out there to which i'm not real wild about.

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James Connors: So here, I was looking at places where a construction site that is down off the screen here had released sediment into this wetland and I was looking for areas that I could go and take samples.

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James Connors: here's another wetland.

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Stephanie Rogers: Again that's your two minute warning.

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James Connors: Two minutes okay.

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James Connors: here's another.

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James Connors: wetland area that actually look like this, eight years earlier, a company that determined that it was 100% wetland and earlier zero percent got sued.

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James Connors: turned out that the county had pushed a tremendous amount of water, all the water in an unplanned developed area into that property and an eight years, it turned it into a bona fide wetland.

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James Connors: Contamination this is oil that goes to the surface, almost overnight.

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James Connors: The causation of that was what we looked at with these drones here's a situation where two gigantic above ground storage tanks collapsed, and these holes here have targhee black goo and them, it looks like jed clampett was hanging out around here.

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James Connors: A lot of places you can't use drones i'd love to use it on this project said urban watershed that snakes through a city, but it's right on the flight path of a.

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James Connors: of an airport and here's what a big source massive source of an emerging environmental contaminants and a water intake for a region on a river.

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James Connors: A few miles away flow in this direction, but as much as I would love to show all those plumes coming out of that facility.

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James Connors: This is a small airport, and that is a nuclear power plant, and even though the NRC says, you can fly a drone over a nuclear power plant, I have avoided federal prison all these years i'd like to not push my luck.

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James Connors: So.

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The end.

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Stephanie Rogers: Any questions perfect timing.

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James Connors: Thank you, thank.

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James Connors: Well, there are no questions I will.

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Stephanie Rogers: haha yeah right you can't get off that easy all right, where did mind.

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Stephanie Rogers: I don't see any hands raised so while we wait, I would like to ask you a question, so what do you predominantly do with your images, do you collect them solely for visual effects or do you also do some image analysis as well for changing landscapes, or whatever it might be.

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James Connors: Well, you know I I primarily try to get the lay of the land, because very often it's just amazing what you can see, even with the Tele which only goes up to 100 feet when you get that perspective, you go wow or.

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James Connors: A great example, and this is a case I can't talk too much about but there's something that we discovered and we've been working on this case for several years and using drones.

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James Connors: and going back through the data I found that same material showing up for years in drone footage that i'd taken and and not even thought about looking for because it had not become an issue.

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James Connors: And now that it is an issue all that's recorded in the background, but to actually get into spectral analysis and things like that no not not at this point.

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James Connors: You really talking about in big investment I probably got $1,000 into all of those drones that that I showed a little bit earlier.

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James Connors: So yeah if it ever became an issue it's not that money would be the issue but.

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James Connors: That would be something i'd probably sell out to a specialist in that area and remember to back to our delbert standard at some point i'm no longer the expert i'm going.

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to rely on somebody like you do that.

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Stephanie Rogers: Great thanks i'm Maryland do you have a question.

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Marilyn Vogel: Yes, I do Hello.

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Marilyn Vogel: Great pre I caught I didn't get all of this, I loved what I caught of it fascinating.

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Marilyn Vogel: I had this question come up recently about the question and miniaturization and regulation on and so on, and.

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Marilyn Vogel: i'm wondering like what your perspective would be or you might not have a perspective about this, but if you don't that's fine like it seems to me the 250 gram.

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Marilyn Vogel: Cut off with sort of a short sight on the part of FAA because it's like they can now make these drones that are weighing a lot less you know.

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Marilyn Vogel: And what what's your perspective, like doesn't seem like they considered the moore's curve, are we going to see a lot of like people going around that fence a little bit or do you have any idea like what that little specification regulation is about.

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James Connors: Well i'll tell you this, I you know dealt with a lot of.

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Marilyn Vogel: federal agencies.

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From.

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James Connors: From the EPA to the irs and others I can't even mention, but I can tell you that.

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James Connors: FAA seems to at least in recent years seems to have its act together on drones and and they're willing to change a great example.

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James Connors: As a commercial operator, I have to take a test now stephanie can get a grant and get summer salary money changes hands but she's not a commercial operator, but so.

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Stephanie Rogers: yeah I am I am a commercial pilot's license.

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James Connors: But, but you don't have to.

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Stephanie Rogers: um you should if you're going to publish any of your results, you should well.

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James Connors: i'm just telling you the regulations don't require that anymore as of March of think last year.

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James Connors: The academia for.

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Clark Alexander: The universities do.

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Stephanie Rogers: yeah they do.

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James Connors: But FAA doesn't so.

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James Connors: If you if you're in a situation where you have to go back and retest or be 24 months that recently was changed to where all you have to do is do.

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James Connors: A retraining, which is online and free so instead of having to go back and sit for the test every 24 months to get a recertification you just go through this is basically an update.

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James Connors: course and it's online, so I think they're actually being pretty progressive and we'll just have to see how they handle that.

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James Connors: i'm glad glad to see the universities are doing that, though.

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Stephanie Rogers: That would probably be good for their lives.

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Stephanie Rogers: Right Okay, thank you i'm just want to remind everyone, we are going to have time at the end of the session to open up you know, a broader discussion, but I think.

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Stephanie Rogers: For the sake of time we're going to move on now to our next presenter which is Edna Fernandez, and not I will prepare the timer and let you.

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Stephanie Rogers: take it away when you're ready.

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Stephanie Rogers: alright.

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Edna Fernandez: hi everyone, my name is Edna i'm a graduate student here at auburn university.

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Edna Fernandez: And today i'm going to talk a little bit about our research using drones for monitoring harmful algal blooms.

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Edna Fernandez: So i'm going to give a quick review on what harmful algal bloom is and i'm going to focus on these terms phytoplankton and cyanobacteria.

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Edna Fernandez: Because i'm going to be referring to them a lot throughout my talk and I want to make sure these two things are really clear.

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Edna Fernandez: So phytoplankton are things like cyanobacteria green algae and diatoms which are primary producers that make up the base of a lot of aquatic food woods and they need a resource such such as nutrients, in order to survive, can you all see my mouse.

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Edna Fernandez: You can.

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Stephanie Rogers: know if you right click you can start your laser there you go.

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Edna Fernandez: Perfect so nutrients like nitrogen and phosphorus are going to feed our phytoplankton in aquatic ecosystems.

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Edna Fernandez: But since the industrial revolution there's been an increase in the use of fertilizers for agriculture, as well as for other industrial uses.

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Edna Fernandez: And there's more nitrogen and phosphorus entering our aquatic ecosystems and it's causing the rabbit and massive accumulation of certain phytoplankton species and then freshwater ecosystems is to typically attributed to sign a bacteria.

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Edna Fernandez: Now, saying it back to your pretty problematic in fresh water systems because they can produce Santa toxins.

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Edna Fernandez: Which are a type of toxin that can poison aquatic organisms, such as apiculture fish in this picture.

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Edna Fernandez: As well as humans and our livestock on our pets, so it can have a pretty negative health and economic impact on these industries.

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Edna Fernandez: They can also produce off flavor compounds that make drinking water and agriculture fish have this like musty or muddy sentence flavor.

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Edna Fernandez: And it causes a lot of consumer complaints, even though there aren't really any health effects associated with these compounds people don't want to drink stinky water so it's it's a really big problem, and they can also dictate oxygen levels.

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Edna Fernandez: which can essentially replicate other aquatic organisms.

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Edna Fernandez: So sometimes wounds are really easy to the tech, so this is a giant bloom in South Africa in 2008 and we can see the the dense algos also the surface and even more.

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Edna Fernandez: Intense one is at one here one of our agriculture pawns at auburn university cyanobacteria blooms tend to have this like characteristic neon green color.

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Edna Fernandez: But it can be a little bit more challenging when we're looking at a lot of ponds, at the same time and in our lab what we do to.

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Edna Fernandez: estimate phytoplankton and cyanobacteria abundance is well there's a few methods, the first is the eyeball method.

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Edna Fernandez: And typically ponds that are dominated by phytoplankton kind of have what we term here in the south, the camel green color.

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Edna Fernandez: And when you look at those that water under the microscope you're going to see a nice combination of different phytoplankton species and they're probably not going to be as dense as the sample.

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Edna Fernandez: And typically boat ponds that are dominated by saying the bacteria have this john deere color and they tend to have these like surface gone that accumulate downwind and when you look at them under the scope it's going to look like this, like a single tax and it's usually cyanobacteria.

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Edna Fernandez: And we want to get better and quicker estimates, we can also do pigment extractions, and so the pigment that we look at estimate vital pain points in a book of abundance.

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Edna Fernandez: Is chlorophyll which is found in all phytoplankton species and Corvo absorbs light in the blue and red region of the electromagnetic spectrum.

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Edna Fernandez: And reflects light in the Green and your infrared region and that's why plants appear green because they reflect bring light.

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Edna Fernandez: If we want to estimate cyanobacteria abundance we measure Fido sanon, which is a access story pigment down in cyanobacteria and this pigment.

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Edna Fernandez: absorbs light in the orange region of the electromagnetic spectrum and reflects blue and near infrared light and again it reflects green light and that's why a lot of people call cyanobacteria blue green algae because they make the water appear blue.

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Edna Fernandez: And now we work very closely with our.

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Edna Fernandez: Oh, how do I do this now We work very closely with our agriculture, farmers out here in West Alabama.

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Edna Fernandez: And we go on sample for them about once a month and give them an idea of how much cyanobacteria they have in the water.

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Edna Fernandez: But sometimes they need a little bit of higher resolution because they have sometimes over 100 pounds and they just don't really have the access to the tools.

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Edna Fernandez: The time and the training to actually go out and sample these cons on a consistent basis, so this is where the idea of using the drone came from.

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Edna Fernandez: So you really wanted to devolve like a really easy method for them to just find a job and be able to say okay well this con is dominated by saying bacteria we potentially need to treat with chemicals.

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Edna Fernandez: So the way the drone works is here, we have our nice spectral signature of chlorophyll when we have the sun it's going to have our Hadar phytoplankton.

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Edna Fernandez: In the water and then again they absorb blue and red light and reflect green and your infrared light.

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Edna Fernandez: Our sensor records these wavelength, and then we can use them to calculate.

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Edna Fernandez: These things, called meditation indices, this is a really popular vegetation index, known as the normalized difference vegetation index.

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Edna Fernandez: And essentially what it's doing is that it's really capturing the reflections and absorption properties of that surface and then it gives you a value to to give you an estimate of.

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Edna Fernandez: photosynthetic activity, so in this picture on the right, I think this is a cornfield that couldn't find all the data for this, but.

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Edna Fernandez: Essentially, as the colors get stronger or more red there's a higher photosynthetic activity in that area.

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Edna Fernandez: And I really wanted to show a picture like this, because a lot of these techniques and tools were developed for our cultural use so when it came down to utilizing these sensors for our agriculture ponds.

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Edna Fernandez: We really didn't know which sounds or what's going to work and which meditation and that's what's going to work so that was basically this study, so I was lucky enough to have access to four different sensors.

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Edna Fernandez: Two of them are the integrated visible light spectrum sensors that are in these quad copter is known as phantom four and phantom four pro they're they're really popular and these sensors record.

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Edna Fernandez: Blue green and red wavelengths and then we had these two multi spectral sensors that were attached to our quad copter, as you can see them in this picture above.

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Edna Fernandez: So this is a relatively inexpensive modified multi spectral sensor known as an APP for survey three I was really excited about this one, because it's it's pretty cheap.

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Edna Fernandez: And it's essentially just a gopro that sacrifices, the Red wavelength to measure near infrared and then we have this more expensive multi band multi spectral sensor called the parrot sequoia and it has individual sensors that measure green red red edge and near infrared wavelengths.

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Edna Fernandez: Alright, so like I mentioned, we didn't really know what sensors were going to work, and we also didn't know which meditation indices are going to work I scoured the literature and there were some papers that utilize drones for estimating.

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Edna Fernandez: phytoplankton abundance, but not specifically cyanobacteria so we ended up kind of finding all the ones that were relevant and we just wanted to test them all out.

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Edna Fernandez: And I just want to point out that not all the vegetation indices work for all the sensors they really depend on which wavelengths are sensor can measure.

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Edna Fernandez: And to test these vegetation indices we collected data from 54 ponds and we really wanted to make sure that we collected data from pawns of different sizes.

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Edna Fernandez: Tropic states so very clear, all the way to bury green ponds.

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Edna Fernandez: Different depths and different terminology, so you can see in the picture on the right, some of my poems are really.

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Edna Fernandez: brown because sometimes our agriculture ponds are really Brown and we wanted to have that in our data set and also through time, so you can see how this pond greener and greener as the summer went on, so this is, I think, in January, all the way to May.

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Edna Fernandez: or July.

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Edna Fernandez: And we collected several samples from the same pond for a total of 72 samples so, for example in this pond that has this really thick scum cover.

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Edna Fernandez: I would collect a sample from the scum and then also from the clear portion of the pond just to get an idea what was happening in the entire system.

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Edna Fernandez: And we collected integrated samples up to where we could see this sexy disk, which is a measure of transparency and the idea is the drone can see as far down as the, as you can see, the second disc.

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Edna Fernandez: And I just wanted to show Catherine Cruz, who was the RU student to help me with this project last number.

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Edna Fernandez: Alright, so i'm going to talk about the two separate.

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Edna Fernandez: The two separate pigments and then for the for each sensor and each vegetation index so i'm only showing the best vegetation index for each sensor.

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Edna Fernandez: So here on the y axis, we have the vegetation index on the X axis, we have the log of the measured pigments and we did this proof the Rama Rama tree.

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Edna Fernandez: And we're talking about our visible light spectrum data, right now, we have our phantom four and then our phantom four pro which what had a slightly higher resolution.

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Edna Fernandez: And we were actually pretty impressive this sensor because it's really not designed to estimate.

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Edna Fernandez: photosynthetic activity, but we got pretty good correlation of these data, and if I were to give a farmer a drone right now, it would be this one, because it was really easy to analyze and process these data, and it was really intuitive.

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Edna Fernandez: Unlike our modified multi spectral sensor this one, I was really excited about because it was really cheap and I can measure the near infrared wavelength.

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Edna Fernandez: But it was really challenging to process these data, it took a really long time and the data quality wasn't very good and we ended up getting really poor correlations with powerful concentrations.

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Edna Fernandez: And then the best answer, out of all of them was our multi band multi spectral sensor I had a really good correlation with our measure of chlorophyll.

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Edna Fernandez: And even though it was a little bit more complicated to use a data are really clean and if I were to use this for research, and this will be the drone that I would use.

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Edna Fernandez: Alright, so in terms of psycho CNN, which is the pigment that we use to estimate cyanobacteria on know the drones were not as good at estimating this particular pigment.

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Edna Fernandez: So you can see here are if I go sand and the R squared went down quite a bit.

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Edna Fernandez: We also had a poor correlations with our modified multi spectral sensor.

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Edna Fernandez: And then, again, the best sensor for estimating this pigment was the Multi band multi spectral sensor, and the reason why this.

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Edna Fernandez: This the sensors weren't as good at estimating this particular pigment is, if you look at the spectral.

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Edna Fernandez: per per byte go San and none of the drones can really measure that absorbent peak for ficus and and not the orange wavelength so that's probably why that's actually why we didn't get as good data for five to San and.

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Edna Fernandez: Alright, so in terms of the advantages of using these drones for this application, the first and most important one, is that they can account for the uneven distribution of phytoplankton cells and aquatic systems.

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Edna Fernandez: Typically, when we sample these types of ponds we gaba a point sample from the same spot every time.

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Edna Fernandez: And so you're not really taking into consideration the fact that wind and wave action can be pushing all those cells to one particular side of the pond.

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Edna Fernandez: So you could either be under overestimating the phytoplankton abundance in your system and drones can really capture that distribution really well.

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Edna Fernandez: And one once I mean we did the hard part by actually testing these sensors and figuring out which vegetation index for the best, but now the the training needed to actually get somebody to use these sensors I think will be pretty straightforward.

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Edna Fernandez: And they can cover a relatively large spatial range, depending on the battery life of your drone.

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Edna Fernandez: And our drone really didn't have very long battery life, especially because they were carry an additional sensor but as technology improves, I think that will be able to capture a larger area and that's gonna be really beneficial.

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Edna Fernandez: In terms of limitations, there are a few, including the the battery life limitation.

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Edna Fernandez: The first is weather so first of all you're limited by the time of day, if you look at the image on the right, you can see that the pond kind of have these streaks.

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Edna Fernandez: And that's because I collected samples close to noon, and that means that the the sun is reflecting really heavily off the surface of the water and so we're getting these reflectance.

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Edna Fernandez: streets which aren't aren't great and then, when in temperature so first temperature.

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Edna Fernandez: The drone battery becomes less effective as temperatures go down so once you hit freezing you can't really find the drone very well.

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Edna Fernandez: And then, when So these are all pre specify a flight plan so basically you tell the drone to get a certain amount of overlap.

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Edna Fernandez: And it kind of flies like this depending what direction you tell it to go and if it's really windy it's going to push your drone off of that pre-specified.

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Edna Fernandez: flight plan and we try to stitch those images together kind of like a puzzle the software is going to have a really hard time, which is what happened, and this image, right here.

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Edna Fernandez: Also, the drone has a hard time stitching images together if it's a really large water body, because it doesn't have anything solid to say okay well this picture matches with this picture, right here so that's another important limitation.

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Edna Fernandez: And then terms of water quality, obviously the drones can't measure or say no toxins are all flavor compounds because they don't have a spectral signature, but more importantly, they can't really differentiate among.

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Edna Fernandez: toxin and non toxin producing taxa because not all cyanobacteria are able to produce these compounds and this is a problem that's unique to drones it's also an issue.

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Edna Fernandez: When we're doing our normal pigment instructions.

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Edna Fernandez: Right so In conclusion, the the visible light spectrum and the Multi multi spectral sensors could be reliable tool for measuring chlorophyll especially that multi band multi spectral sensor.

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Edna Fernandez: All the sensors are more sensitive to chlorophyll then vipassana and, and this is likely, because none of them can measure that orange wavelength.

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Edna Fernandez: And again, we, and it would be really nice to have a sensor that will be able to measure that because I could see this being applied in a variety of aquatic ecosystem so.

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Edna Fernandez: yeah this is, I get are you a student i'm really proud of, and if you have any questions I will stop talking.

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Stephanie Rogers: Great.

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Stephanie Rogers: Thank you and.

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Edna Fernandez: Thank you.

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Stephanie Rogers: All right, we have a question from a doctor Ojeda, please.

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Ann Ojeda: Say and that thanks that was wonderful.

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Ann Ojeda: I hadn't seen your data presented like that it made me think of something, and when you get when you take your data from the drone do you get an absorbent or a reading for every wavelength along that band that captures.

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Edna Fernandez: that's a really good question So yes, you get you only get a reading for the wavelength and it's able to measure, so the the camera on your phone it can measure red green and blue wavelengths and it has like a.

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Edna Fernandez: Like a peek at where it can like the maximum absorption in her house like a range but yeah you only get data for those three way of lens and then, when you upload that data into your software, it gives you the three separate.

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Edna Fernandez: wavelengths and that's how your phone camera and all cameras work it's just like numbers on pixel.

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And then it matches.

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Ann Ojeda: The picture that you were showing where like you had the electromagnetic spectrum and then kind of a bar that had a whip.

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Ann Ojeda: Is that true that you're actually measuring multiple wavelengths or is it really just a line where you get one wavelength.

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Edna Fernandez: yeah you get one wavelength, if you wanted to measure the entire spectrum, then you would need something called a hyper spectral drone which can actually measure multiple like a lot of wavelengths at various more intervals.

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Ann Ojeda: Okay, great thanks.

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Stephanie Rogers: Great and I see a question from Bo Yang.

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Bo Yang: And this is oil from North central Florida oh very interesting presentation.

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Bo Yang: Thank you know that yeah yeah.

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Bo Yang: Perhaps there is a big problem, as you can in most of the graduate admissions we're doing some similar work before as well.

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Bo Yang: you'll notice to mapping for the water is kind of wrote with challenger because we know what our surface kind of relatively homogeneous so sometimes that's what it will it processor tool data, there will be some blacks teaching issue.

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Bo Yang: And also, my question is well, my question is, do you have any suggestions I see you match your electrical spectral signature that's the way I also other index with the.

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Bo Yang: Inside your measurements somebody so we'll do this kind of matching I see pick up feel points whole kind of.

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Bo Yang: accurately pick up those posts farms or somebody location, because of the data you're it's it's a very high spiritual revolution centimeter level so much higher than the GPS accuracy.

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Bo Yang: So another question of commerce, I will compare that's how your results, give us that high resolution outperforms our previous notes of the data estimate from the satellite multi spectrum.

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Edna Fernandez: So you said a lot of things so was.

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Edna Fernandez: That really accurate estimates for where I.

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Edna Fernandez: collected my water sample was the first question, and then the second question is, how does the resolution compare to satellites okay.

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Bo Yang: Oh OK yeah OK.

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Edna Fernandez: So the first for the first question, we have a very.

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Edna Fernandez: Very fancy GPS meter and I will we collect ground control points around our flight area, so that the image itself is really well i'm.

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Edna Fernandez: Just like deal referenced and then I also collect the DPS pointed every whenever I collect a war sample and then I can match that pixel that's closest to where I collected that sample to my image is I your question.

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Bo Yang: Yes, yes okay.

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Edna Fernandez: And then, for the second question for the resolution, compared to a satellite that's a really good question satellites are really good tool for estimating.

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Edna Fernandez: Harmful algal blooms and it's actually what is used in ocean system so ocean color satellites are really important, and so, for these systems are pretty small so.

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Edna Fernandez: At this level all those points I showed in the first picture will kind of make just one giant blob and the satellite and I can't really tell you the.

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Edna Fernandez: The exact it depends on the satellite how find the the spectral resolution is, but I think that the smallest one to now is 3030 meter pixels for the satellites, so the drunken really zoom in very much depending on how high you fly.

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Edna Fernandez: Oh.

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Bo Yang: yeah sounds good thanks so much.

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Stephanie Rogers: Great Thank you um I don't see any other hands race so let's take a 13 minute break and the next talk will start at 250 so go stretch your legs and grab a drink, if you like, and we'll See you in 13 minutes, thank you.

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Stephanie Rogers: hey Bo do you want to practice sharing your screen just to make sure it'll work for you.

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Edna Fernandez: No you're good will start in a cup in a few seconds ones that turn into 250 which is now alright so hi everyone.

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Edna Fernandez: Welcome back to our session so we're gonna start up with Dr Yang who is.

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Edna Fernandez: From the University of central Florida and he's in and talk to us about using drones for monitoring seagrasses so go ahead docking.

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Bo Yang: Thank you either yeah good afternoon everyone thanks, very much for having me oh yeah i'm from university of central Florida, and today i'm going to talk about how we use a hybrid solution in the mapping for accessing the secrets, and I was the west coast of North America.

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Bo Yang: yeah so this protect is one of the first attempted to use an interdisciplinary.

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Bo Yang: muscles next to you a remote sensing jazz and logical somebody to access a sequence condition in the West Coast so as we can see.

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Bo Yang: The secrets habitats it's a very potent component for the coastal ecosystem it's a photo critical host for the reverse of the next door LG by the animal an extra so.

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Bo Yang: The traditional we use different types of muscle there's also the current research using different muscles to accessing source equals condition.

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Bo Yang: Like the satellite remote sensing it has a temporary repeating cycle and kind of easily to obtain the historical data.

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Bo Yang: Center so has a relatively moderate resolution on the other hand, there's that arrow remote sensing can provide a very high spatial resolution.

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Bo Yang: And also it kind of falls a multi spectrum light as some other kind of sensors and it's quite expensive have to hire the penetrates into the aircraft.

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Bo Yang: don't you AV remote sensing and all we would not answer you even making has been really fast, the recent year, so it is similar to the arrow data to kind of.

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Bo Yang: offer viral hospital sometimes you can click X one centimeters spatial resolution and it's quite cost effective, we can map that on demand, but in X product efforts of the data processing and data validation.

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Bo Yang: So here is our comparing different for the different data sources so from traditional salary most, as you can see, if we want to see the secret medals.

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Bo Yang: We can just say a kind of a boundary and we cannot see any kind of detail level of the sea grass on the camera here is our economic Alaska can see.

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Bo Yang: If the words of trivialities good enough, we can easily see through the water and each release of the sequence machines, the mythologies the texture and the Green is a very operators and then you can select your software that.

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Bo Yang: We can do together to image to generate a big legs up sequence mad like this one, because it also features, and this has much high spatial resolution than the traditional selected.

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Bo Yang: that's why we have this kind of collaboration, monitor and protect founded about NASA so we monitor the size from Alaska down to the San Diego we have seven different sides to monitor.

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Bo Yang: And for each of summer or will fly as a tool for all the US says, and we have one size in Canada, that will be flagged by our partner.

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Bo Yang: Is a hacker Institute, so we have a continuous of the ratio for the west coast.

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Bo Yang: And we're we're because of our group is responsible for the GIs and the most part, and we have a local research partners, they will collect the incentive like.

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Bo Yang: summary data like they're all from lax the marathons and the biology department and they will like.

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Bo Yang: The user to observe exactly work like you know the disease detection there's lots of disease happening in the west coast and they will also do some blacks acute PCR eds Gani, so we will use that they're like something work as the ground to sing for our DEMO sizing data.

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Bo Yang: So here is a example our mapping error last letter s I just asked the other night that we encounter some difficulties you reduce turnover.

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Bo Yang: image or was a homogeneous water surface, so what we do is we we deploy some boys, like this one out of the water and the land, we deploy something greater, more mark lacks the buckets.

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Bo Yang: To that is very obviously to be distinguished on the image, so the software our country covenant with those kind of targets so you'll see that those regions with our targets that.

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Bo Yang: image teaching will be better and also, we will use them as a gc ground control points to use this with your reference our imagery to be bad her current activities that you set for 78.

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Bo Yang: So here's a workflow our to image processing that has that we collected each each of the sites, we will collect five to six kind of saw.

475
01:12:09.720 --> 01:12:17.190
Bo Yang: Your prospects and we will do the mapping and also will do some processing of current balancing you're referencing correction.

476
01:12:17.490 --> 01:12:26.190
Bo Yang: As a tool will be able to generate a spectral bands, as well as a digital surface model and also, we will do some snacks the segmentation classification.

477
01:12:26.520 --> 01:12:36.900
Bo Yang: and generate some more kind of parameter called the most as a parameter and the world trying to learn to the connected with certain parameter with insight to somebody parameters.

478
01:12:38.130 --> 01:12:52.950
Bo Yang: So this is an example of the color balancing and the atmospheric pressure would bring two types one is pure black and white is pure black black, we can use a simple acts of aggression phone to crack the email.

479
01:12:54.450 --> 01:13:04.710
Bo Yang: And also, this is an example we collect from the tcp points at some topics I mentioned it lacks the boys are the buckets here the collector TTS points and you'll see before.

480
01:13:05.640 --> 01:13:15.540
Bo Yang: The Joe referencing that's true image still have some kind of this location agra after that one, because these are the location accuracy therapy graduate programs.

481
01:13:18.720 --> 01:13:25.140
Bo Yang: that you have a products included, not only that also my back military because of those factors signature.

482
01:13:25.380 --> 01:13:35.100
Bo Yang: But also include the DSL digital surface model so it's very useful for the secrets medals become you'll see the variation can be captured.

483
01:13:35.400 --> 01:13:46.410
Bo Yang: On each of the security patches there are different variations so that one will be take part in the unit segmentation and classification as well, so so far, like I said, we can develop that some.

484
01:13:48.600 --> 01:13:58.800
Bo Yang: The spectral signatures and some activity index from structure of the company and also, we can generate the texture from each kind of segmentation.

485
01:14:00.180 --> 01:14:12.840
Bo Yang: results, and we will do some morphology analysis, the reason we use the green leaf index in this one, because we are mainly based on escaping the Western disease for the sequence so as you can see, this lab testament.

486
01:14:13.290 --> 01:14:26.040
Bo Yang: If the cigars was in fact a bottle of whiskey does is it allows a lot of its greatness so that's why we use green green green leaf impacts to merriment this kind of phenomenon.

487
01:14:28.890 --> 01:14:40.140
Bo Yang: So this is a example of how we process our product for this is the original image of the wild side and after that, we can see after a classification, we can.

488
01:14:40.830 --> 01:14:49.860
Bo Yang: extract all the errors are belong to seagrass we have some compelling some printing samples from the surgery about logical fieldwork.

489
01:14:50.250 --> 01:14:58.410
Bo Yang: and afterwards we segment into one or two patches each packets, which patch we think of it as a one part of the sequence of.

490
01:14:58.650 --> 01:15:06.960
Bo Yang: A cluster a little sick words that has similar characters so after the way based on this segmentation muscle, we can calculate the asset.

491
01:15:07.470 --> 01:15:17.190
Bo Yang: index from the spectral signature and also text for nurses next the entropy and how much energy and also, we will feed each of the object as.

492
01:15:17.940 --> 01:15:31.770
Bo Yang: equals eclipse so that we know that approximately what's a size average size of each object, so we know that for this region or what's the lens of the each of the blaze of the sea glass.

493
01:15:33.090 --> 01:15:42.360
Bo Yang: So this is some legs preliminary and nurseries us, but can see it's quite interesting because, for the grand index for all our side, we kind of.

494
01:15:42.960 --> 01:15:50.700
Bo Yang: says these fabulous allows the last huge difference, so we can see the Lord actual has higher kind of greenleaf index.

495
01:15:50.940 --> 01:16:02.250
Bo Yang: Well, as a higher level, you have lower kind of greenleaf index for the texture can see the entropy and how much energy is it kind of has a universe to kind of trend, but still the patterns of years.

496
01:16:02.610 --> 01:16:20.190
Bo Yang: But for the radiance for the enclosed that ellipse because think of it as like so what's the average length of the each sequence play packages, so we can say there is a candle decrease the trend from the North to source, but the Washington side here is an outlier.

497
01:16:22.710 --> 01:16:31.200
Bo Yang: So another part of this project is a sentence as research, so you know that we have lots of the lizard partners it from a different.

498
01:16:31.740 --> 01:16:41.700
Bo Yang: background like biology my research but they don't have the background photo yes and the most dancing so we're trends on how to fly over to an enabler to there, this is all.

499
01:16:43.590 --> 01:16:53.580
Bo Yang: around our training course it's included lacks the drum set up how to manually flag autumn autumn numerous flair for a map also it includes some test.

500
01:16:54.480 --> 01:17:11.460
Bo Yang: Basically, as an asset like how to stitch from image to assimilate map and also, we will need like 10 to 20 our self study for exam to study by yourself and also take the FAA part of part of selling license so they can live in a flat for work or photo research.

501
01:17:13.320 --> 01:17:23.610
Bo Yang: So here is a short story created data after the training in that 2019 so far i'm sorry, we can see, most of them are very satisfied with this training course.

502
01:17:23.970 --> 01:17:35.490
Bo Yang: But they are not very confident you flying to independently, based on the q3 and Q4 but remember this story was just taken right after the first of your training.

503
01:17:35.940 --> 01:17:43.710
Bo Yang: And we didn't think that this can be pay off so quick because several years 2020 the car the car were not able to travel.

504
01:17:44.100 --> 01:17:58.350
Bo Yang: To the west coast, so we use like our previous training and combining this one and let them to take every part of our lessons but part of our summer lessons and a couple other tools for us, so we continue to collect the data during the 2020.

505
01:17:58.890 --> 01:18:18.060
Bo Yang: And you can see, after 20 that each of our collaborator in Washington in California and the Alaska they all got like where it goes most The fly after training and collect that data so here is a quick story map that that way.

506
01:18:20.130 --> 01:18:21.150
Bo Yang: recorded this one.

507
01:18:24.510 --> 01:18:28.590
Stephanie Rogers: This one I think you have to turn your laser off to be able to click it.

508
01:18:40.560 --> 01:18:41.730
Bo Yang: And then you can see.

509
01:18:42.960 --> 01:18:51.150
Bo Yang: That this is some of our next the local suddenly work and controlling work and, most importantly, I want to show the last one.

510
01:18:51.720 --> 01:19:04.980
Bo Yang: Because this is a combination of the different Luxor this swept map, you can see, on the left is a drone data collected by our X the X remote sensing expert, for the first year.

511
01:19:05.460 --> 01:19:18.060
Bo Yang: And second year, this is a collective our research partner would just take the training and we can see the covers pretty much the same area and the image quality is pretty much all very good for the analysis so.

512
01:19:18.480 --> 01:19:25.530
Bo Yang: that's our kind of the story of our projects and i'll be happy to take questions.

513
01:19:27.660 --> 01:19:30.810
Edna Fernandez: Great Thank you does anybody have any questions for Dr Yang.

514
01:19:36.330 --> 01:19:48.720
Edna Fernandez: All right, well, I have a question so when you're collecting these images, do you take into account title fluctuations, is that affected at all the way to tie drops you get a better image of the vegetation or.

515
01:19:49.320 --> 01:20:00.720
Bo Yang: Yes, that's very good question because for us when my of focus on that interim title area, so we have to take a load like no time serious like our travel data.

516
01:20:01.050 --> 01:20:13.860
Bo Yang: strictly limited to that that low tax returns a mouse, and a lot of time is usually where are the ammonia so sometimes we have to wait until we get our food like illumination of sunlight, so we can do the.

517
01:20:14.340 --> 01:20:23.070
Bo Yang: To the market so like this one, because this is intertidal return so nolan is submerge only during your low tire because see the sequence here okay.

518
01:20:23.520 --> 01:20:24.450
Edna Fernandez: Great Thank you.

519
01:20:25.680 --> 01:20:26.310
Edna Fernandez: 70.

520
01:20:28.050 --> 01:20:42.360
Stephanie Rogers: That great Thank you um I was wondering if this project is going to continue, or if it's complete now and what were your greatest challenges in getting citizen scientists trained and ready to go collect data.

521
01:20:43.470 --> 01:20:50.880
Bo Yang: Oh, so this year, this is a three year project, and this is a certain year so that is our first year we go to a size.

522
01:20:52.020 --> 01:20:58.110
Bo Yang: Where expanding like after three years, they will can turn on collected data but suddenly.

523
01:20:58.590 --> 01:21:08.070
Bo Yang: Last year's as a pandemic coming, so we have to force them to take the FA well seven lessons and start collecting data for us, but it goes really well.

524
01:21:08.670 --> 01:21:14.700
Bo Yang: Because we have some partners with my friend at multiple people we have fun.

525
01:21:15.360 --> 01:21:24.090
Bo Yang: At least a while, tourism, I really interested in this kind of the traumatic so they went to the facility take the examination and started cracking.

526
01:21:24.540 --> 01:21:30.900
Bo Yang: data for us there's this go smoother that's Another reason is because there is a function I don't know.

527
01:21:31.590 --> 01:21:36.510
Bo Yang: If he knows, as you can create that with Madeline region we created like so.

528
01:21:36.960 --> 01:21:48.120
Bo Yang: Flemish by myself, who have flood this region and we upload this mission to the cloud, they just a tunnel that be sure and go to medical field, they actually need to do is one click flat.

529
01:21:48.690 --> 01:22:00.960
Bo Yang: To will automatically matches that area and what we are doing is it's a useful controls are Joe what keep an eye on and watch the weather condition so that's that's that's kind of a smarter than we thought.

530
01:22:02.460 --> 01:22:03.570
Stephanie Rogers: Great thanks.

531
01:22:06.420 --> 01:22:17.430
Edna Fernandez: All right, we have a question here from Clark Alexander and it says were there any special considerations for comparing data from all those different drones and operators was data comparable between all the phantoms.

532
01:22:19.350 --> 01:22:31.320
Bo Yang: Oh yeah so for four hours is that we use to kind of drums one is Paris bluegrass one is phantom four pro but, for the first year and second year, we always send it.

533
01:22:32.280 --> 01:22:41.400
Bo Yang: Over as a collection of the fence and four so basically all of our reseller partner on ourselves will collect the rgb banner using the phantom.

534
01:22:41.940 --> 01:22:50.940
Bo Yang: phantom four pro so basically the same lacks the platform so so as I sit same sense of further processing.

535
01:22:51.360 --> 01:23:03.900
Bo Yang: Because we have a documentation of the other protocol that for how long you flat words into also our APP and it was a major cleverly collection steps so Basically, they are the same, we can earn a similar results.

536
01:23:07.830 --> 01:23:08.820
Edna Fernandez: Great Thank you.

537
01:23:10.530 --> 01:23:11.190
Thank you.

538
01:23:14.460 --> 01:23:19.860
Edna Fernandez: So we have a little bit more time, so we have four minutes before stephanie's presentation, I have one more question for you.

539
01:23:20.490 --> 01:23:35.790
Edna Fernandez: So you're collecting all these data on seagrass beds Has anybody tried to collect any additional data on like the types of organisms that are in the seagrass beds, because that could be also an indicator of health, maybe or is that, beyond the capabilities for the project at this point.

540
01:23:36.690 --> 01:23:48.960
Bo Yang: Oh that's a good question actually you know that when we're collecting a jogger how we always kind of collecting the area larger than targeting seagrass beds so like the surrounding like a part of the show.

541
01:23:49.470 --> 01:24:04.260
Bo Yang: And portals of the sand, the sun, which is also collected so well also working on kind of accessing sandbox environment so parameters that could affect us as well, so yeah lots of work can be done, based on this.

542
01:24:05.520 --> 01:24:08.730
Edna Fernandez: Great I look forward to that Thank you.

543
01:24:10.080 --> 01:24:21.480
Stephanie Rogers: I have another question, what do you think the benefit of using a multi spectral drone would allow you to do that the the rgb sensors wouldn't let you in this situation.

544
01:24:22.620 --> 01:24:37.860
Bo Yang: Oh yeah so you know the most powerful the most advantage is it has a near infrared the near a river is very responsive to the career field so sometimes the secrets House can be more responsive to this kind of.

545
01:24:38.940 --> 01:24:47.880
Bo Yang: The bandwidth so we can get more kind of the comprehensive spectral signature, so we contacted better classification results better kind of the parameter estimate.

546
01:24:48.960 --> 01:25:00.570
Bo Yang: But on the other hand, this well, we will select to those those normal phantom four legs rtb job because his resolution is very hot that if a flat 200 feet, it can generate to the.

547
01:25:01.170 --> 01:25:13.920
Bo Yang: Special at 1.5 centimeters so pretty high, and also because we're interested the rest of this disease on the sea grass, so that wasting the words like I showed the cost of.

548
01:25:14.370 --> 01:25:23.520
Bo Yang: secrets to lose agreements so that's why we use this color rgb values or greenleaf index will try to access your House conditional seagrass.

549
01:25:25.860 --> 01:25:34.740
Stephanie Rogers: Great so in this case you're getting everything that you need just from the the rgb and multi spectral not necessary.

550
01:25:38.940 --> 01:25:43.350
Bo Yang: Also, this year, this year we are able to travel again.

551
01:25:43.950 --> 01:25:45.840
Bo Yang: What we do is represent both kind of.

552
01:25:46.590 --> 01:25:49.740
Bo Yang: Under the motors function will also want to say that.

553
01:25:50.100 --> 01:25:54.720
Bo Yang: If we can do a more kind of parameter from you know modest fashion, is expensive.

554
01:25:54.870 --> 01:26:02.160
Bo Yang: Yes, yeah urine is a platform is heavier so for the last year, our cutoff line don't we really don't want to.

555
01:26:02.190 --> 01:26:03.630
Stephanie Rogers: risk of these kind of things, yes.

556
01:26:05.580 --> 01:26:08.520
Bo Yang: or no, no mojo that's very stable very robust.

557
01:26:08.640 --> 01:26:11.730
Stephanie Rogers: Right yeah it's risky I agree yeah.

558
01:26:13.590 --> 01:26:14.400
Bo Yang: Later this year.

559
01:26:15.180 --> 01:26:17.220
Stephanie Rogers: seems like a really interesting project.

560
01:26:17.910 --> 01:26:20.220
Bo Yang: Thank you happy to talk them all.

561
01:26:24.900 --> 01:26:31.470
Edna Fernandez: Right so where 319 so I guess, we can start with stephanie's presentation in a minute.

562
01:26:31.890 --> 01:26:33.270
Edna Fernandez: If you want to share your screen.

563
01:26:51.270 --> 01:26:58.710
Edna Fernandez: This is Dr stephanie Rogers and you're going to tell us about using on occupied aerial systems for studying liquefaction so.

564
01:27:00.180 --> 01:27:03.090
Stephanie Rogers: Great i'm also going to time myself, so I know.

565
01:27:04.200 --> 01:27:15.390
Stephanie Rogers: When i'm talking too much so Thank you everyone for being here, I am stephanie Rogers i'm an assistant professor and GI science in the department of geosciences.

566
01:27:16.710 --> 01:27:20.670
Stephanie Rogers: i'm going to tell you about a ongoing project that.

567
01:27:22.110 --> 01:27:24.030
Stephanie Rogers: we're working on, let me get my laser out.

568
01:27:25.140 --> 01:27:38.310
Stephanie Rogers: So I don't have any definitive results for you today, but I have some preliminary ones, but it's about exploring the use of us is or unoccupied aircraft systems for studying earthquake induced liquefaction deposits.

569
01:27:38.760 --> 01:27:52.260
Stephanie Rogers: And i'd like to give shout outs to my colleague Dr Lorraine Wolf, who I believe is in the room and graduate students john Goodman and Stephen Matthew, so this is john, and this is Stephen.

570
01:27:52.830 --> 01:27:56.940
Stephanie Rogers: with special thanks to Dr mark tisha total who's not in the photo.

571
01:27:57.390 --> 01:28:15.390
Stephanie Rogers: But she is a geologist who's an expert in liquefaction in this region that i'll tell you about today and Marion haynes here in the middle, who is a retired archaeologist who helps us out with our site selection and just generally knows the region very well so.

572
01:28:16.590 --> 01:28:23.940
Stephanie Rogers: He has a very old truck in his yard so it's neat to take pictures with his some of his antiques relics that he has anyway.

573
01:28:24.600 --> 01:28:35.520
Stephanie Rogers: let's get into it, so the region of the world i'm going to be telling you about is here in the new magic seismic zone, some of you may or may not have heard about that, before.

574
01:28:36.300 --> 01:28:51.480
Stephanie Rogers: Here we are in auburn or some of us are in auburn and some of us are not, and this is our studies site called yarborough and it's just north of blythe bill in Arkansas So although the last major earthquakes in this region occurred in.

575
01:28:53.580 --> 01:28:59.760
Stephanie Rogers: Earthquake hazards from the new Madrid seismic zone poses significant risk to this region, even today.

576
01:29:00.120 --> 01:29:05.400
Stephanie Rogers: A large earthquake magnitude greater than six will affect people property infrastructure.

577
01:29:05.730 --> 01:29:20.940
Stephanie Rogers: And market and supply sectors, however, the importance of the region as a transportation and distribution Center means that large earthquake would have serious ripple effects are beyond the area of shaking so the last major earthquake was.

578
01:29:23.520 --> 01:29:32.040
Stephanie Rogers: One of the questions that i'm not answering but that researchers are trying to answer is the what is the return period of large earthquake in this area.

579
01:29:32.610 --> 01:29:50.610
Stephanie Rogers: Originally it was postulated that it was 500 years but recent dating efforts have shown that it's perhaps closer to 200 years, so if you do the math we're now at 2020 we could be due for a very large earthquake in this region, which could have devastating effects on the region.

580
01:29:52.290 --> 01:29:54.240
Stephanie Rogers: So what is liquefaction.

581
01:29:56.430 --> 01:30:10.710
Stephanie Rogers: I I assume there's a lot of geologists in the room i'm not a geologist so i'm going to use my notes that Dr Wolfe prepared for me to make sure I don't mess this up, but essentially earthquake induced liquefaction.

582
01:30:11.310 --> 01:30:22.530
Stephanie Rogers: Its form from strong ground shaking from large greater than magnitude six earthquakes that creates a click strains in saturated sand deposits so like down here.

583
01:30:23.640 --> 01:30:42.690
Stephanie Rogers: Situated just below the water table under the right conditions for example low permeability layers above, for example, these layers poor pressure builds up in a slurry of water laden sand breaks through the overlaying layers to the surface forming a sand blow.

584
01:30:44.430 --> 01:31:00.450
Stephanie Rogers: which resembles a sand volcano or a Fisher the pathway to the surface is referred to as a San dike and dykes, are important because they cross cut younger strata and provide relative age estimates, so this is a way that you can get.

585
01:31:01.890 --> 01:31:10.680
Stephanie Rogers: Relative ages of earthquakes that have occurred in the region in the right hand figure the aerial photo shows extensive sand blows.

586
01:31:11.220 --> 01:31:30.330
Stephanie Rogers: And Sam fisher's samples are typically circular light colored patches like the ones circled and San fishers are typically on Echelon and sub parallel to point bar deposits or stream channels, so these surface expressions are common of liquefaction features.

587
01:31:32.100 --> 01:31:46.680
Stephanie Rogers: So here's an image from Google Earth is from October 2010, and this is near our study area so as you can tell you see some of these surface expressions in the area and.

588
01:31:47.250 --> 01:32:02.610
Stephanie Rogers: If you go through a Google earth through time sometimes the sandalow expressions are very visible and sometimes they're not visible at all, so this is one of the good examples from October 2010 that you can find so i'm just going to zoom in.

589
01:32:04.770 --> 01:32:08.280
Stephanie Rogers: So you can see, so this is one of our sites and these lovely.

590
01:32:09.750 --> 01:32:16.050
Stephanie Rogers: orange dots are some GPS points that we have taken, but essentially you can see these.

591
01:32:18.270 --> 01:32:23.280
Stephanie Rogers: What are expected to be liquefaction features on the surface.

592
01:32:25.470 --> 01:32:31.680
Stephanie Rogers: So the product overview is that some of you might be giggling about this, but this is.

593
01:32:32.880 --> 01:32:46.470
Stephanie Rogers: The overview of the project, so what we're trying to do is get a look at the envelope features from above using unoccupied aircraft systems and we want to know what's going on below the surface, as well, so we're using a ground penetrating radar.

594
01:32:47.550 --> 01:32:55.710
Stephanie Rogers: Which kind of looks like the lawn mower which you'll see in a second, this is the best icon I could find for it and we're looking at electrical resistive at.

595
01:32:56.040 --> 01:33:03.480
Stephanie Rogers: Measurements as well, so for this project in particular that i'm that i'm going to talk to you about today it's the drone aspect.

596
01:33:03.840 --> 01:33:23.040
Stephanie Rogers: If you'd like to know more about the the gdpr aspect you can check out the poster by Stephen Matthews and others that was in session D one geophysical insights and applications and for the electrical resisting it, you can check out the talk by john Goodman in the same session.

597
01:33:24.360 --> 01:33:42.120
Stephanie Rogers: And what does that look like in non icon form, this is an example of our field work so over here on the left, this is the ground penetrating radar and Stephen and Dr Wolf, this was taken in November.

598
01:33:43.950 --> 01:33:56.100
Stephanie Rogers: and November 21 and this are October 2020 excuse me October 2020 this image was taken in November 2019.

599
01:33:56.910 --> 01:34:09.030
Stephanie Rogers: And this is john Goodman and Dr Wolf, and this is Dr TIM tuttle she came on our first exploration but i'm not on our second and bishop, who was helping as an undergrad student.

600
01:34:09.360 --> 01:34:21.870
Stephanie Rogers: So you see the gdpr you see the electrical resisted it here the handy dandy GPS, and this is a electrical resistance at output, which shows you the changes in.

601
01:34:23.370 --> 01:34:29.820
Stephanie Rogers: sediment type underneath under the ground so again, if you want to learn more about that you can check out.

602
01:34:31.500 --> 01:34:36.750
Stephanie Rogers: john Gibbons presentation, because that is certainly not my expertise, so that was very fascinating.

603
01:34:37.920 --> 01:35:03.420
Stephanie Rogers: Okay, so to take another look at the region, this is a complicated map, but I will try to break it down for you the colors of the circles represent the ages, the known ages of earthquakes in the region, so you can see, the date from one to 238 ad all the way back to 5000.

604
01:35:04.860 --> 01:35:12.240
Stephanie Rogers: So 5000 years ago, so a long time ago, and this area in the purple.

605
01:35:15.210 --> 01:35:34.110
Stephanie Rogers: purple square is where our study site is so you can see there's a ton of activity in the region, the White area represents the whole liquefaction field so very characteristic of this region very unique study region so let's zoom into.

606
01:35:35.160 --> 01:35:56.310
Stephanie Rogers: All of these data areas, so the hypotheses of this study or that of correlation exists between sambo age and organic content in sediment so that's our first hypothesis, and that these characteristics are distinguishable from multi spectral aerial imagery captured from a US.

607
01:35:57.600 --> 01:36:08.820
Stephanie Rogers: So the research question is, can a US and a multi spectral sensor be used to develop a relative dating mechanism for sand blows in the new magic seismic soon.

608
01:36:11.310 --> 01:36:17.340
Stephanie Rogers: So we have three study sites that we looked at one is called delahunty it's from the.

609
01:36:19.260 --> 01:36:43.560
Stephanie Rogers: Earthquake be is called burnham burnham and it's from the 1450 ad earthquake, these have been previously dated by total at all and see is from the bug 40 as it's called bug 40 and it's expected to be from about 900 ad based on native American occupation at that site.

610
01:36:46.830 --> 01:36:59.250
Stephanie Rogers: So we flew the drone at each of these sites and let's tell you about some of the equipment that we use, so this image my look familiar I stole it from Edna, I believe, but essentially we use the parrot.

611
01:37:00.510 --> 01:37:01.170
Stephanie Rogers: The phantom four.

612
01:37:02.280 --> 01:37:05.190
Stephanie Rogers: phantom four pro with the parents of Korea sensor.

613
01:37:06.330 --> 01:37:17.190
Stephanie Rogers: And we use that the first year and it was very, very cold, it was very cold, when we were flying that November and we had some malfunctioning.

614
01:37:18.360 --> 01:37:28.980
Stephanie Rogers: So much so that one of our sites, we did not get multi spectral imagery so we came into some money and we wanted to upgrade so we got this material.

615
01:37:29.430 --> 01:37:43.020
Stephanie Rogers: 200 V2 and an autumn micro sense autumn sensor so they they're they're each multi spectral the micro Center also has a thermal sensor as well.

616
01:37:45.750 --> 01:38:00.360
Stephanie Rogers: So for the data collection November 2019 we set up ground control targets we collected imagery from all sites, so all three sites, except the Multi spectral did not work for burnham so in October 2020.

617
01:38:02.700 --> 01:38:13.680
Stephanie Rogers: Again we set out our ground control targets we collected imagery using the ultimate this time this first year was all with the parents acquire.

618
01:38:14.490 --> 01:38:21.420
Stephanie Rogers: And we collected soil samples from all of our sites and i'll tell you more about that in a moment.

619
01:38:22.200 --> 01:38:37.320
Stephanie Rogers: So data processing all data were processed in PICs 40 mapper resulting files included digital surface models or though imagery and multi spectral raster bands so each band from the.

620
01:38:37.950 --> 01:38:51.030
Stephanie Rogers: From the sensor so read read edge near infrared green blue and long wave infrared or thermal the Multi spectrum of bands will be used to calculate indices so as.

621
01:38:52.050 --> 01:39:10.170
Stephanie Rogers: I mentioned earlier, this nice table that she showed all these indices that she tested for harmful algal blooms we're going to do something similar to determine which industry is best for determining differentiation in carbon content development in soil.

622
01:39:11.550 --> 01:39:23.760
Stephanie Rogers: And one example i'm going to show you today is the normalized difference read edge the end dare, which is the near infrared minus read edge divided by near infrared plus read.

623
01:39:26.280 --> 01:39:27.240
Stephanie Rogers: So here is.

624
01:39:28.290 --> 01:39:34.920
Stephanie Rogers: Some of our preliminary results, and this is at the burnham site, so this is the one that we flew.

625
01:39:36.270 --> 01:39:51.990
Stephanie Rogers: This past October so on the left, this is our rgb so or ortho image we see our soil samples the surface soil samples in yellow and then we also had some auger halls which went a bit deeper to get.

626
01:39:52.830 --> 01:39:58.950
Stephanie Rogers: Some subsurface samples as well, we see our digital surface model here.

627
01:39:59.430 --> 01:40:15.300
Stephanie Rogers: And then, this is a thermal image and one thing I particularly wanted to point out is the zoomed in area in this black box here in panels D and E so from the naked eye, you can kind of tell that there's some differentiation between.

628
01:40:16.620 --> 01:40:32.190
Stephanie Rogers: what's going on in this image, but in fact we expect there to be a sand blow in this location and when you when we do the calculation for the end dare that actually makes the visualization of the different.

629
01:40:33.360 --> 01:40:45.270
Stephanie Rogers: Saying carbon contents or textures stand out a lot more so, although this is qualitative at the moment, the next steps are to quantify these differences, using a lot of different indices.

630
01:40:46.950 --> 01:41:00.600
Stephanie Rogers: So, like, I mentioned the next steps calculate more indices and quantify which is best for distinguishing between Sam blow ages in the study area, complete the soil carbon analysis and correlate to imagery.

631
01:41:01.710 --> 01:41:09.240
Stephanie Rogers: compare with the results from the other aspects of the project, so the ground penetrating radar and the electrical resist it.

632
01:41:09.810 --> 01:41:25.050
Stephanie Rogers: To obtain a holistic picture of liquefaction in this study area again so we're working towards developing and adding to this timeline of when the next major earthquake might occur and the project and date is march 2022.

633
01:41:27.900 --> 01:41:35.580
Stephanie Rogers: So that's what I wanted to share with you today, and I thank you very much for your attention i'm happy to discuss and answer questions.

634
01:41:39.780 --> 01:41:41.700
David's iPad (4): Yes, I have a question can you hear me.

635
01:41:42.000 --> 01:41:42.690
Stephanie Rogers: Yes, I can.

636
01:41:43.170 --> 01:41:45.270
David's iPad (4): i'm David Ross with the usgs.

637
01:41:45.750 --> 01:41:48.720
David's iPad (4): hello, done a lot of work there and then Madrid and.

638
01:41:49.860 --> 01:41:59.730
David's iPad (4): Just one dimension, have a comment and a question one our work showed that basically threshold for liquefaction is about magnitude 6.4.

639
01:42:00.270 --> 01:42:09.870
David's iPad (4): Body wave magnitude 6.4 the last liquefaction event that we're familiar with occurred in the what we call the 1895 charleston earthquake northeast is sexton.

640
01:42:10.260 --> 01:42:22.500
David's iPad (4): which was about mang to 6.8 So if you look up north of psych students rich outside of where you specifically looked you'll see the youngest liquefaction field in them new mattress cyclic zone in that area.

641
01:42:22.680 --> 01:42:23.160
David's iPad (4): From around.

642
01:42:23.580 --> 01:42:29.370
David's iPad (4): 95 and then, of course, there are other liquefaction events that happened since 1811 and 1812 as well.

643
01:42:31.260 --> 01:42:38.550
David's iPad (4): And I didn't know so that was a comment I wanted to make about our sense of the threshold for liquid factions about 6.4 body weight magnitude.

644
01:42:39.270 --> 01:42:48.300
David's iPad (4): And I was wondering if you looked at all at Stephen over myers work from the usgs who from looking at soil characterization and pressure tests was able to distinguish.

645
01:42:49.080 --> 01:42:57.210
David's iPad (4): kind of age fields for the various earthquakes that we've detected from his soil analyses and it'd be nice to compare what you find from your.

646
01:42:59.130 --> 01:43:06.990
David's iPad (4): Your work using drones from compared to what he's done from soil testing, and I might just also add just quickly that when we did a lot of our sambo work.

647
01:43:07.770 --> 01:43:22.020
David's iPad (4): we've tried to work as we as much as we could, in April, because the soil contrast with a bit more moisture in there, made the appearance, the sand blows whether the fishers are circular blows much more apparent than during the dryer seasons of the year, when you're harder to distinguish.

648
01:43:22.980 --> 01:43:31.890
Stephanie Rogers: Thank you, those are all really useful, so the obermeyer question I have not looked at his work, but i'll definitely look that up um what was the first name.

649
01:43:32.490 --> 01:43:49.560
Stephanie Rogers: Stephen even okay i'll definitely check into that and the reason of our timing for our field work, as unfortunately determined by the crop rotation schedule the the planting schedule and the harvesting schedule the farmer, so we work at farmer's fields and.

650
01:43:52.710 --> 01:43:57.510
Stephanie Rogers: that's when the harvest off, but I think will rain has a comment on that.

651
01:43:57.900 --> 01:43:58.350
Go ahead.

652
01:43:59.370 --> 01:44:02.310
Lorraine Wolf: yeah we're really familiar with steve's work.

653
01:44:03.330 --> 01:44:13.050
Lorraine Wolf: And we're also familiar with saucy as mapping of the liquid fact and features there so stephanie is not as she said she's a geographer and.

654
01:44:13.470 --> 01:44:16.260
Lorraine Wolf: I feel to this GIs and drones but.

655
01:44:17.670 --> 01:44:27.300
Lorraine Wolf: tish title and I have worked in the area for many years and we're quite familiar with both those people and and their work and their mapping of the sandbox but it's a.

656
01:44:27.840 --> 01:44:41.190
Lorraine Wolf: We will be comparing some of these results with various age dates and also not only our age dates, but also what other people said so recently we published.

657
01:44:44.130 --> 01:45:02.070
Lorraine Wolf: A compilation of all the references for the new Madrid area and Eastern us charleston included of various people's results and literature having to do with the various earthquakes, so that believe that we did that, for the nuclear regulatory Commission.

658
01:45:02.970 --> 01:45:10.920
David's iPad (4): Well that's great to hear, I mean the Roger soca I worked with him for many years, I was down at waterways experiment station with him with the corps of engineers for quite a few years.

659
01:45:11.520 --> 01:45:21.900
David's iPad (4): and Steve obermeyer also did work in the charleston South Carolina area with pradeep Taiwanese and others so work with pretty for many years, as well, so I would simply.

660
01:45:22.650 --> 01:45:32.580
David's iPad (4): curious if if there's still a continuation, to look at the charleston Missouri area northeast of site since rich because that's the youngest liquefaction in the area.

661
01:45:33.450 --> 01:45:35.670
Lorraine Wolf: yeah we you know.

662
01:45:37.980 --> 01:45:42.810
Lorraine Wolf: We thought about that, but you know we've been pretty busy with other areas.

663
01:45:44.010 --> 01:45:53.700
Lorraine Wolf: My tissue has been working a lot, New Zealand and other places and we've done a lot work in California, we tried to do some work in the Pacific Northwest so.

664
01:45:55.110 --> 01:46:01.320
Lorraine Wolf: yeah charleston would be great you're absolutely right great target, but just haven't gotten there.

665
01:46:01.770 --> 01:46:02.280
David's iPad (4): don't understand.

666
01:46:04.350 --> 01:46:10.020
Stephanie Rogers: lucky, for me, one of the great parts about this project is that it's multi disciplinary so I don't.

667
01:46:10.710 --> 01:46:29.490
Stephanie Rogers: I I leave all of the liquefaction details and earthquake details due to Lorraine, and I just go fly drones and and help out with the remote sensing and try to we try to piece it all together as a team so that's that's the cool part but it's always nice to hear external inputs as well.

668
01:46:32.340 --> 01:46:41.010
Stephanie Rogers: i'm Clark were you referring to which publication when you ask the question is that recent some republication available.

669
01:46:41.520 --> 01:46:45.450
Clark Alexander: You know that that's the summary that Lorraine, is just mentioning.

670
01:46:47.370 --> 01:46:58.020
Clark Alexander: About summary of earthquakes and Sam blows and including the charleston earthquake, because it being in savannah we have a lot of interest in what what goes on in charleston earthquake wise.

671
01:47:00.360 --> 01:47:03.480
Stephanie Rogers: Lorraine is was there a publication after that conference.

672
01:47:03.510 --> 01:47:05.070
Lorraine Wolf: yeah so um.

673
01:47:06.090 --> 01:47:21.480
Lorraine Wolf: The presentation was made at the SSA meeting that was held in Seattle, a couple years ago, but you can find it the nuclear regulatory Commission were supposed to publish it, I think, was all this coven stuff things just got really.

674
01:47:22.590 --> 01:47:43.170
Lorraine Wolf: lost in the shuffle, but you can find the results on tissues website, and you can just download them they're publicly available so whatever she has a big compilation for different areas, you can really get there, along with all the you know age date what age dates exist and.

675
01:47:43.890 --> 01:47:46.050
Stephanie Rogers: So i'll try to find that link for you.

676
01:47:47.190 --> 01:47:54.030
Clark Alexander: Great we're all those age date some basically carbon 14 on organic matter in the same boat themselves.

677
01:47:55.020 --> 01:47:56.550
Lorraine Wolf: um some of well.

678
01:47:58.710 --> 01:48:07.080
Lorraine Wolf: No, they weren't all in the sand blow somewhere on top of the sand blows somewhere below the sand blows part of it, dependent on whether there were.

679
01:48:07.380 --> 01:48:19.800
Lorraine Wolf: native American occupation horizons so some some dates come from those different cultural periods usually it was a combination, you know a good site would have.

680
01:48:20.520 --> 01:48:39.570
Lorraine Wolf: Closely constrained ages so maybe, something that was right below the sand below or a contact between a soil horizon and a sambo unit ideally one below one above and you know some of those sites satisfy those strict criteria and some of them didn't so.

681
01:48:40.620 --> 01:48:41.160
Clark Alexander: Thank you.

682
01:48:45.930 --> 01:48:55.470
Edna Fernandez: Right and we have a question from kalan asking, are there any considerations to other drones other drone mountain sensors such as magnet magneto meters.

683
01:48:57.270 --> 01:49:00.600
Stephanie Rogers: There, there are magnetometers on drones.

684
01:49:01.890 --> 01:49:12.960
Stephanie Rogers: Lorraine suggested I look into that we've come we come to looked into that together for for my specific purposes it wouldn't be kind of worth the cost, I know you can do it.

685
01:49:14.130 --> 01:49:26.640
Stephanie Rogers: I try to get sensors that I can use for various applications, and so I didn't look any further into that but, for example, I have used lidar mounted on drone as well as hyper spectral sensor.

686
01:49:27.480 --> 01:49:42.900
Stephanie Rogers: So those are some that i'm familiar with, but basically if if it's within the weight restrictions and you want to try to figure out how to mounted on a drone it's a sensor i'm sure there are many people have come up with many unique ways to to make that happen so.

687
01:49:45.210 --> 01:49:53.970
Stephanie Rogers: I don't know of any specific magnetometer applications, besides that one that I looked that I looked at once.

688
01:49:55.410 --> 01:49:58.500
Lorraine Wolf: There are quite a number of them and and I have to.

689
01:50:00.660 --> 01:50:03.660
Lorraine Wolf: Admit that caleb was one of my former students so.

690
01:50:05.550 --> 01:50:08.220
Lorraine Wolf: And he knows that I probably want him back to town.

691
01:50:14.250 --> 01:50:15.030
Stephanie Rogers: Great.

692
01:50:18.510 --> 01:50:25.470
Edna Fernandez: Alright, so I think it's time for the discussion, so I think it's going to hand it over to Jim who's in charge.

693
01:50:26.310 --> 01:50:27.630
Stephanie Rogers: Gentlemen kumar.

694
01:50:27.780 --> 01:50:30.330
Stephanie Rogers: yeah I don't know if you're still here.

695
01:50:32.760 --> 01:50:35.520
Stephanie Rogers: Oh, Jim we can't hear you if you're talking.

696
01:50:39.180 --> 01:50:48.810
Stephanie Rogers: Anyway, well, he gets that sorted it's going to just like an open, we have several minutes for an open discussion, one thing that I wanted to ask the people in this room.

697
01:50:50.100 --> 01:50:56.970
Stephanie Rogers: is how many of you use drones and if, if you do and what application, do you use them for.

698
01:51:01.530 --> 01:51:14.160
Clark Alexander: Oh i'll talk we're using drones on the coast of Georgia to map sand bodies, you know typically man made dunes or other sand berms that are put up.

699
01:51:15.030 --> 01:51:24.030
Clark Alexander: provide protection for the shoreline and we're using them to go out and do create DSM look at the difference over time.

700
01:51:24.450 --> 01:51:37.290
Clark Alexander: give some guidance to city and other agencies about when they might need to rebuild those kinds of structures and looking at basic settlement redistribution in the coastal systems here in Georgia.

701
01:51:38.970 --> 01:51:39.720
Clark Alexander: are using.

702
01:51:39.750 --> 01:51:41.160
Clark Alexander: phantom fuller's as well.

703
01:51:42.180 --> 01:51:42.510
Stephanie Rogers: Oh.

704
01:51:43.170 --> 01:51:44.730
James Connors: A university researcher Clark.

705
01:51:45.420 --> 01:51:54.090
Clark Alexander: Yes, i'm with the University of Georgia let's get away Institute of Oceanography i'm a coastal geologist by training right.

706
01:51:57.900 --> 01:52:07.350
David's iPad (4): And this is de bras again from usgs and we use drones quite a bit in our coastal zone work particularly up in New England, but also down, we will fly.

707
01:52:07.830 --> 01:52:22.740
David's iPad (4): drones both pre and post hurricanes, to use structure promotion structure promotion to try to understand changes in the morphology the slope into the doom front end of the beach in general that's just one of many applications, we use actually.

708
01:52:29.790 --> 01:52:42.240
Clark Alexander: yeah I will say I got my my first exposure to using lidar drone a couple of weeks ago there's another researcher at uga who has one it's about three feet on a side.

709
01:52:42.840 --> 01:52:44.340
Clark Alexander: It looks like an m 600.

710
01:52:45.030 --> 01:52:45.360
But.

711
01:52:46.380 --> 01:52:51.150
Clark Alexander: You know it'll it'll live like 15 pounds and and it's a monster.

712
01:52:51.840 --> 01:53:00.690
Stephanie Rogers: They are they're beasts I caught the one I use wasn't am 600 with the lidar and the hype respect they're just called it, the beast and it took off and it just sounded like.

713
01:53:01.200 --> 01:53:10.950
Stephanie Rogers: You know, it was creating its own it was impressive is really impressive that the empty hundreds impressive, as it is and then put on a couple other.

714
01:53:12.960 --> 01:53:16.680
Stephanie Rogers: couple other propellers and then that thing and carry a lot of weight.

715
01:53:17.550 --> 01:53:31.380
Clark Alexander: yeah we've been using an m 200 down around in the salt marshes to do more vegetation kinds of analysis there's a long term ecosystem research site out of sample island and lt our site.

716
01:53:32.490 --> 01:53:49.380
Clark Alexander: Looking at salt marsh ecosystems and we've been looking at disturbance of different sorts over the last six years, using drones to use the ultimate camera for multi spectral imagery and then not doing in in db I are in vdi again there remember.

717
01:53:50.580 --> 01:53:52.170
Clark Alexander: geologist I don't care.

718
01:53:53.400 --> 01:53:59.940
Clark Alexander: But yeah so we've been using the mmm 200 to fly that same alum camera it's been interesting stuff.

719
01:54:00.150 --> 01:54:07.440
David's iPad (4): yeah and Clark, have you tried to use that restructured promotion to look changing typography and morphology.

720
01:54:08.670 --> 01:54:09.540
David's iPad (4): dumbo area.

721
01:54:09.780 --> 01:54:11.010
Clark Alexander: The ultimate camera.

722
01:54:11.820 --> 01:54:17.070
David's iPad (4): or whatever cameras, you have if you don't use the to collect structure from motion data.

723
01:54:17.610 --> 01:54:18.780
David's iPad (4): Sure character.

724
01:54:18.930 --> 01:54:20.880
David's iPad (4): Changing morphology beach morphology.

725
01:54:21.480 --> 01:54:31.050
Clark Alexander: We haven't used it down on SAP Hello we've been mostly been using our phantom cameras and phantom pro drones to do it.

726
01:54:31.740 --> 01:54:40.380
Clark Alexander: Around tybee island which just built a whole new set of dunes in early early 2020 as part of a between nourishment.

727
01:54:40.770 --> 01:54:51.900
Clark Alexander: And then at Fort plasticky national monument, which is in the mouth of the savannah river, where there were a lot of cultural resources that were getting ready to be eroded into the River because of all the ship traffic.

728
01:54:52.350 --> 01:55:04.230
Clark Alexander: And so the core pumped up a big bunch of saying to us as a experiment, to see whether they could use beneficial dredge material that way, instead of just putting rocks all along the shore.

729
01:55:06.690 --> 01:55:17.250
Stephanie Rogers: Actually, you can use structure for motion, which is a photo symmetrical technique for for any images that you collect as long as they have a certain percentage of overlap with each other so.

730
01:55:19.230 --> 01:55:32.760
Stephanie Rogers: that's the one of the benefit of using drones because you can create a point cloud from these 2d images which are, which is actually comparable to to light are in, in most cases, maybe not highly vegetated areas right.

731
01:55:33.030 --> 01:55:40.410
Clark Alexander: And that's why we haven't done it down on SAP alone in the Marsh or anything like that everything so vegetated because all you get as a surface model right.

732
01:55:40.890 --> 01:55:53.940
Clark Alexander: Not a not an elevation model so all you see is the top of the trees and the plants and the Marsh grass and yeah but have limited use if you're interested in what the morphology of the land surfaces.

733
01:55:54.030 --> 01:55:54.540
Right.

734
01:55:58.980 --> 01:56:06.150
Stephanie Rogers: Does anyone else have any final questions or comments we've got about two minutes left in our session.

735
01:56:08.940 --> 01:56:11.790
Stephanie Rogers: Any not non drone users who just want to ask.

736
01:56:13.890 --> 01:56:15.990
Stephanie Rogers: simple questions, maybe, how it works.

737
01:56:17.040 --> 01:56:25.800
David's iPad (4): You know I just this is day for us again usgs and wondered, you know there's a an applied to surface geophysics organization society i'm wondering if there's a section of it.

738
01:56:26.310 --> 01:56:34.560
David's iPad (4): That looks at drones and uab type equipment descent, the community of people who can work and talk together on an ongoing basis.

739
01:56:37.230 --> 01:56:40.380
Stephanie Rogers: Not that i'm aware of, maybe Lorraine might know.

740
01:56:40.860 --> 01:56:49.950
Lorraine Wolf: I think there's a you know, there are several are a lot of papers that have come out and sad deep you know I don't know if you're familiar with sal GB.

741
01:56:50.400 --> 01:56:51.570
David's iPad (4): yeah that's what i'm talking about.

742
01:56:51.810 --> 01:56:55.560
Lorraine Wolf: yeah yeah I think there are there is a community is probably growing.

743
01:56:56.940 --> 01:56:59.550
Lorraine Wolf: But i'm not really in that community.

744
01:57:00.570 --> 01:57:03.930
Lorraine Wolf: i'm just kind of associated with it peripherally.

745
01:57:05.040 --> 01:57:15.750
Lorraine Wolf: But yeah probably a lot of interesting work I think there's been a number of studies with I hate to say this next to stephanie but with magnetometers attached.

746
01:57:17.880 --> 01:57:21.030
Lorraine Wolf: To the you ABS so that's pretty good technique.

747
01:57:23.970 --> 01:57:31.320
Clark Alexander: And I will say that Noah has started to develop a user Community they held a drones in the coastal zone workshop.

748
01:57:32.550 --> 01:57:44.190
Clark Alexander: Early well mid mid year last year, and so they're developing a user community that kind of can talk to each other about issues and and concerns and best practices.

749
01:57:45.510 --> 01:57:48.570
Lorraine Wolf: Do they have like a proceedings or any kind of.

750
01:57:49.740 --> 01:57:52.890
Lorraine Wolf: You know summary of the workshop from that.

751
01:57:54.240 --> 01:57:54.540
Clark Alexander: My.

752
01:57:54.660 --> 01:58:05.460
Clark Alexander: group i'm i'm really not sure i'm sure the website is still up and I don't know whether the presentations were recorded, but they might have been i'm sorry I can't be more definitive.

753
01:58:05.640 --> 01:58:09.720
David's iPad (4): Is this the snow is coastal services Center out of charleston it's doing that.

754
01:58:10.560 --> 01:58:13.740
Clark Alexander: um I don't think so.

755
01:58:20.400 --> 01:58:32.760
Stephanie Rogers: Okay, well, I think, where we're at the end of our time so again, I want to thank all of my co convener and the rest of the group for for joining us, and I think we.

756
01:58:34.140 --> 01:58:41.610
Stephanie Rogers: had some really nice presentations this session so it's a little bit different from probably the rest of the ones that were going on.

757
01:58:42.300 --> 01:58:52.080
Stephanie Rogers: At this conference, but anyway, thank you very much for your interest and these videos actually will be available, I think, maybe you saw it in the chat earlier, they will be available online.

758
01:58:52.800 --> 01:59:11.460
Stephanie Rogers: 48 hours from now, so if you want to revisit any you are welcome to do so, so again, thank you very much, and thanks Edna and Jim and kumar and and both for your presentations and we'll leave you at that happy Friday Have a nice weekend.

759
01:59:13.380 --> 01:59:14.010
James Connors: guys.

760
01:59:14.550 --> 01:59:15.330
Next Thursday.

761
01:59:29.160 --> 01:59:30.030
Stephanie Rogers: i'm happy, you are here.

762
01:59:33.450 --> 01:59:35.400
Lorraine Wolf: I was rushing to get here, I had this.

763
01:59:36.090 --> 01:59:39.480
Stephanie Rogers: Talk I just don't know I don't know.

764
01:59:41.010 --> 01:59:41.490
Lorraine Wolf: yeah.

765
01:59:42.510 --> 01:59:45.930
Lorraine Wolf: Anyway, um, I just wanted to make a correction for.

766
01:59:45.930 --> 01:59:48.000
Lorraine Wolf: You at that.

767
01:59:49.260 --> 01:59:53.370
Lorraine Wolf: site that you had listed as 1450 it's another 900.

768
01:59:53.940 --> 01:59:56.130
Lorraine Wolf: Oh okay got corrected that on your.

769
01:59:57.240 --> 01:59:59.730
Lorraine Wolf: On your faculty symposium poster.

770
02:00:01.080 --> 02:00:02.910
Stephanie Rogers: On this symposium it said 14.

771
02:00:03.120 --> 02:00:04.230
Lorraine Wolf: yeah and I made your.

772
02:00:05.190 --> 02:00:06.240
Lorraine Wolf: mouth and correct it.

773
02:00:06.270 --> 02:00:07.500
Stephanie Rogers: But oh shoot okay.

774
02:00:08.010 --> 02:00:09.810
Lorraine Wolf: And that was my initial error.

775
02:00:09.870 --> 02:00:11.040
Stephanie Rogers: So that you are.

776
02:00:11.190 --> 02:00:13.470
Stephanie Rogers: You okay so next time I present it yeah you.

777
02:00:13.800 --> 02:00:16.350
Lorraine Wolf: Know they're both 918.

778
02:00:17.310 --> 02:00:18.060
Lorraine Wolf: At least I think.

779
02:00:18.120 --> 02:00:22.320
Lorraine Wolf: burnham is 900 you know H date is and all that will constrain but.

780
02:00:22.470 --> 02:00:22.770
Stephanie Rogers: Right.

781
02:00:22.800 --> 02:00:29.700
Lorraine Wolf: I think both of them are 900 the bug 40 and burnham and then the deal honey is definitely.

782
02:00:31.170 --> 02:00:32.190
Stephanie Rogers: Great okay.

783
02:00:32.790 --> 02:00:33.570
Lorraine Wolf: So you know.

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Lorraine Wolf: Great might.

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Lorraine Wolf: Come back, and you know after watching your presentation and say something about.

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Stephanie Rogers: yeah oops okay great alright, I guess we'll clear the room so somebody else can take it from you.

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James Connors: And a great job send me your CV and i'll see what I can do to help yeah.

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Edna Fernandez: It was nice meeting you Thank you.

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James Connors: Do and stephanie Oh, I guess.

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James Connors: I guess luring.

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James Connors: Have you guys published anything yet on your your work in the new Madrid fault oh.

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Lorraine Wolf: Well, we i've published a lot of stuff with to title and some of my students.

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Lorraine Wolf: So you know, probably going back about 20 years but.

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Lorraine Wolf: So you can I mean it's all over the place, we.

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Lorraine Wolf: If you're interested, we have a we published titian I published a paper.

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Lorraine Wolf: I don't know how interested, you are but we published a paper with a geotechnical person from Georgia tech as well.

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Lorraine Wolf: And it was a like a review paper is about I don't know 60 pages long and it's a review paper on just the whole idea of Paleo liquefaction how to do surveys, how to what things you look for how the geotechnical tests relate to the liquefaction fields, you know it's a it's a very long.

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Lorraine Wolf: paper that is really I think tish intended it for.

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Lorraine Wolf: kind of a legacy of you know, carrying on the methodologies that she's developed in terms of her studies over you know 30 years and and sort of.

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Lorraine Wolf: Providing that historical perspective, and you know gathering up other people's studies and everything so it's kind of a nice review that 60 pages will.

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James Connors: Save several hundred so I i'll read that.

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Lorraine Wolf: yeah.

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James Connors: Thanks for coming to our already that.

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Lorraine Wolf: yeah Thank you.

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James Connors: bye bye bye bye.

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