USE OF WORLDVIEW-3 MULTISPECTRAL DATA FOR MAPPING URANIUM MINE WASTE PILES AND DISTINGUISHING THEM FROM OTHER NATURAL AND ANTHROPOGENIC LANDSCAPE FEATURES, SOUTH TEXAS COASTAL PLAINS

Worldview-3 (WV3) multispectral data (16 bands) were used to determine if poorly reclaimed uranium mine waste piles can be distinguished from other landscape features in the Texas Coastal Plain and if representative spectral signatures could be identified and used to map and inventory additional abandoned mine sites. Between 1955 and 2013, about 8% of total U.S. production of U₃O₈ was extracted from an estimated 92 mines in Karnes, Live Oak, and Atascosa counties (this study area) in the Texas Coastal Plain (Hall et al., 2017 – Ore Geology Reviews 80, p. 716-753). These sandstone-hosted uranium roll front deposits were created when oxidized groundwater containing soluble uranium (e.g., U⁶⁺) interacted with organic- or sulfide-rich reducing zones in coastal marine sediments, where U-bearing minerals such as coffinite were precipitated. Much of this ore was recovered using open pit mining (OPM) methods commencing from the late 1950s/early 1960s until around the late 1990s. The legacy of uranium OPM is evident throughout the landscape, with numerous pit lakes and waste piles scattered throughout Karnes and adjacent counties. Some of these waste piles have been reclaimed using stabilizing vegetation cover, while others are more exposed due to constant erosion by water, wind, and grazing animals.

The spectral signatures of OPM and landscape features were extracted from the imagery using the “spectral hourglass” approach (Kruse et al., 2003 – IEEE-TGARS 41/6, p. 1388-1400). This approach evaluates each pixel in the scene for purity in a 16- (or less) dimensional “mixing” space. Fifty-eight different spectral signatures from our study area were derived, many of which represent pixels covering known and previously unknown abandoned OPM sites. The 2.5-meter spatial resolution of WV3 together with geomorphological evidence from LiDAR (Light Detection and Ranging) data and GIS locations of known mines and occurrences, provided us with a means of distinguishing mine waste piles from bare soils on pasture and cropland. Class similarity was further evaluated and the dominant minerals in each class were identified by comparison to spectral libraries. The most unique spectral signatures were then used to create a map of all well-exposed abandoned mine features within our study area.