Mapping Abandoned Uranium Mine Features Using Worldview-3 Imagery in Portions of Karnes, Atascosa and Live Oak Counties, Texas

Abstract

Worldview-3 (WV3) 16-band multispectral data were used to map exposed bedrock and mine waste piles associated with legacy open-pit mining of sandstone-hosted roll-front uranium deposits along the South Texas Coastal Plain. We used the “spectral hourglass” approach to extract spectral endmembers representative of these features from the image. This approach first requires calibrating the imagery to reflectance, then masking for vegetation, followed by spatial and spectral data reduction using a principal component analysis-based procedure that reduces noise and identifies homogeneous targets which are “pure” enough to be considered spectral endmembers. In this case, we used a single WV3 image which covered an ~11.5 km by ~19.5 km area of Karnes, Atascosa and Live Oak Counties, underlain by mined rocks from the Jackson Group and Catahoula Formation. Up to 58 spectral endmembers were identified using a further multi-dimensional class segregation method and were used as inputs for spectral angle mapper (SAM) classification. SAM classification resulted in the identification of at least 117 mine- and mine waste-related features, most of which were previously unknown. Class similarity was further evaluated, and the dominant minerals in each class were identified by comparison to spectral libraries and measured samples of actual Jackson Group uranium host rocks. Redundant classes were eliminated, and SAM was run a second time using a reduced set of 23 endmembers, which were found to map these same features as effectively as using the full 58 set of endmembers, but with significantly reduced noise and spectral outliers. Our classification results were validated by evaluating detailed scale mapping of three known mine sites (Esse-Spoonamore, Wright-McCrady and Garbysch-Thane) with published ground truth information about the vegetation cover, extent of erosion and exposure of waste pile materials and/or geologic information about host lithology and mineralization. Despite successful demonstration of the utility of WV3 data for inventorying mine features, additional landscape features such as bare agricultural fields and oil and gas drill pads were also identified. The elimination of such features will require combining the spectral classification maps presented in this study with high-quality topographic data. Also, the spectral endmembers identified during the course of this study could be useful for larger-scale mapping efforts using additional well-calibrated WV3 images beyond the coverage of our initial study area.