DEVELOPING AN ARCGIS TOOLBOX FOR AUTOMATED ROADSIDE OUTCROP DETECTION: A CASE STUDY FROM MIDDLE TENNESSEE

A significant challenge in the geoscience community when initiating studies in new regions is the absence of a comprehensive database that includes local outcrop locations of geologic formations, their precise geographic coordinates, and their geologic ages. Moreover, accessible outcrop locations often remain unknown to researchers due to their remote nature or lack of documentation. To address this, we utilized publicly available light detection and ranging (LiDAR) data, road centerline features, county and geologic polygon data sources provided by the USGS and Tennessee Geological Survey. Our study focused on an area of ~20,000 sq. mi., encompassing the 50 most eastern counties in Tennessee, from Nashville to Johnson City. We systematically located, extracted, and filtered roadside outcrop data across this region. The identified locations were then organized and ranked based on multiple criteria (e.g., distance from roadway, area of exposure, length of face) to generate a quality score. This process involved two Python-based ArcGIS Pro tools and an additional custom application that we developed. The ArcGIS Pro tools function as query-based dialogue boxes, prompting users to connect and organize input data based on county, state, and formation name. The custom application enables the verification of identified locations by checking their visibility in Google Street View. Throughout development, we incrementally scaled up the quantity of data from individual LiDAR tiles to entire counties and then to multiple counties, to test processing load limitations. Our study geospatially identified 5,460 outcrops. Of these, 1,190 locations (22%) were filtered out due to the lack of available street view imagery. The remaining 4,270 outcrops (78%) yielded usable street view imagery. The dataset produced 73% usable locations, and this percentage increased to 86% when the locations within city polygons were excluded. Overall, this research presents a novel method for detecting accessible rock outcrop locations in a region based on county, state, and geologic formation name, significantly reducing the time needed for field-based reconnaissance.