IDENTIFYING POTENTIAL FOSSIL BEARING DEPOSITS IN THE BIGHORN BASIN, WYOMING USING GIS AND REMOTE SENSING

The application of geographic information systems (GIS) and remote sensing techniques for the exploration of paleontologically significant rocks is relatively new. Before the widespread availability of satellite imagery and GIS data, along with a wealth of experience in processing and statistically analyzing various image spectra with relation to physical samples, paleontologists relied on information from previous expeditions to explore and identify new study areas. Despite the great potential for remote sensing to identify different geologic materials at Earth’s surface, very few studies have been completed regarding its efficacy in finding fossil deposits. Using Landsat 8 satellite imagery and previously gathered field data from the Bighorn Basin Paleontological Institute, we tested the effectiveness of three supervised classification algorithms to determine areas of potential fossil deposits based on known fossil bearing locales. Our results suggest that the Maximum Likelihood classification algorithm performed with the highest accuracy, with 90% of known localities being located within the determined “fossil” class. This provides valuable insight for future studies in paleontological remote sensing as the Bighorn Basin has yet to be mapped with remotely sensed imagery and the findings ground-truthed. Although the maps presented are not spatially accurate to a degree which makes site location easy, this technique could drive future expeditions to explore the best possible areas for finding fossils.