GIS-BASED AUTOMATED TIME-SERIES REMOTE SENSING DATA CONVERSION AND INFORMATION RETRIEVAL

The earth system (land, ocean, and atmosphere) is a complex and dynamic system. Geoinformatics for the Earth should not only deal with the geologic record of long-term processes that have shaped the earth, but should also deal with the current dynamic changes of the Earth system such as precipitation, vegetation, temperature, soil moisture, land use and land cover, etc. Remote sensing has been revolutionized in recent decades by the explosion of new data with spatial resolution from sub-meter to tens of kilometer and temporal resolution from minutes to tens of days. However, many obstacles, such as different data formats, different coordinate systems, interoperability, and large hourly or daily datasets have hindered scientists and educators in the access and full use of these tremendous and constantly growing volumes of datasets available. The algorithms and approaches needed to deal with these voluminous and diverse data are not fully developed. In this paper, we will present a GIS based approach to automatically convert different types of remote sensing data such as from NEXRAD and MODIS into a GIS grid format, project or reproject them to a common user-defined coordinate system, and clip and retrieve time series of information (such as precipitation, snow cover, reflectivity, NDVI, temperature) for any region or pixel of interest. The final results then can be easily employed in various applications to encourage integrated analyses in research, education, planning and other applications.