DOQs / Norton / ETM / Michael J. Coan Raytheon Corporation / Earthsat Corporation / DOQ / /
Country
United States / / /
Event
Product Issues / M&A / /
Facility
square km / Limin Yang USGS/EROS Data Center / U.S. Geological Survey EROS Data Center / /
IndustryTerm
machine learning algorithms / Final products / resource management / artificial neural network / at-satellite / final product / at-satellite radiance temperature / unsupervised clustering algorithm / at-satellite reflectance / modularized artificial neural network-based algorithm / regression tree algorithm / geographic information systems / using artificial neural network / /
MusicGroup
IR / /
NaturalFeature
Chesapeake Bay / /
Organization
U.S. Government / National Oceanic and Atmospheric Administration / USDA Forest Service / U.S. Department of the Interior / National Aeronautics and Space Administration / Environmental Protection Agency / /
Person
Collin G. Homer / Bruce K. Wylie / Virginia Several / Limin Yang / Phinn / / /
Position
corresponding author / /
Product
reflectance data / spatially continuous estimates / /
ProgrammingLanguage
R / /
ProvinceOrState
Maryland / Connecticut / South Dakota / Montgomery County / /
Manuscript submitted to Canadian Journal of Remote Sensing (research paper) An approach for mapping large-area impervious surfaces: Synergistic use of Landsat 7 ETM+ and high spatial resolution imagery Limin Yang*, Chen