N: 39.176142 S: 38.867847 E: -108.032283 W: -108.298097
N: 48.672717 S: 48.481442 E: -120.993 W: -121.203708
N: 48.441717 S: 48.269722 E: -120.932614 W: -121.179528
This data set includes: (1) fine-scale snow and land cover maps from two mountainous study sites in the Western U.S., produced using machine-learning models trained to extract land cover data from WorldView-2 and WorldView-3 stereo panchromatic and multispectral images; (2) binary snow maps derived from the land cover maps; and (3) 30 m and 465 m fractional snow-covered area (fSCA) maps, produced via downsampling of the binary snow maps. The land cover classification maps feature between three and six classes common to mountainous regions and integral for accurate stereo snow depth mapping: illuminated snow, shaded snow, vegetation, exposed surfaces, surface water, and clouds. Also included are Landsat and MODSCAG fSCA map products. The source imagery for these data are the Maxar WorldView-2 and Maxar WorldView-3 Level-1B 8-band multispectral images, orthorectified and converted to top-of-atmosphere reflectance. These Level-1B images are available under the NGA NextView/EnhancedView license.
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Six Consecutive Seasons of High-Resolution Mountain Snow Depth Maps From Satellite Stereo Imagery | Hu, J. Michelle, Shean, David, Bhushan, Shashank | Snow Density, Snow Depth, Snow Grain Size, Snow/Ice Temperature, Snow Stratigraphy, Snow Water Equivalent, Land Use/Land Cover, Snow Cover, Digital Elevation/Terrain Model (DEM), Snow Depth | |
| Improving Mountain Snow and Land Cover Mapping Using Very-High-Resolution (VHR) Optical Satellite Images and Random Forest Machine Learning Models | Hu, J. Michelle, Shean, David | Land Use/Land Cover, Snow Cover |