Scientific Investigations Map 3323
The U.S. Geological Survey (USGS) has initiated a multi-disciplinary study investigating the applicability of remote sensing technologies for geologic mapping and identification of prospective areas for base and precious metal deposits in remote parts of Alaska. The Kahiltna terrane in southwestern Alaska was selected for investigation because of its known mineral deposits and potential for additional mineral resources. An assortment of technologies is being investigated to aid in remote analysis of terrain, and includes imaging spectroscopy (hyperspectral remote sensing), high spatial resolution electro-optical imagery, and Synthetic Aperture Radar (SAR). However, there are significant challenges to applying imaging spectroscopy and electro-optical imagery technologies in this area because of the low solar angle for parts of the year, seasonal periods of darkness and snow cover, and the frequently cloudy weather that characterizes Alaska. Synthetic Aperture Radar (SAR) was selected because this technology does not rely on solar illumination and has all-weather capability.
The USGS has compiled a continuous, cloud-free 12.5-meter resolution radar mosaic of SAR data of approximately 212,000 square kilometers to examine the suitability of this technology for geologic mapping. This mosaic was created from Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data collected from 2007 to 2010 spanning the Kahiltna terrane and the surrounding area. Interpretation of these data may help geologists understand past geologic processes and identify areas with potential for near-surface mineral resources for further ground-based geological and geochemical investigations.
First posted April 13, 2015
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Cole, C.J., Johnson, M.R., and Graham, G.E., 2014, Advanced Land Observing Satellite (ALOS) Phased Array Type L-Band Synthetic Aperture Radar (PALSAR) mosaic for the Kahiltna terrane, Alaska, 2007–2010: U.S. Geological Survey Scientific Investigations Map, 1 sheet, scale 1:1,000,000, https://dx.doi.org/10.3133/sim3323.
ISSN 2329-132X (online)