Title of article :
Retrieval of subpixel snow covered area, grain size, and albedo from MODIS
Author/Authors :
Painter، نويسنده , , Thomas H. and Rittger، نويسنده , , Karl and McKenzie، نويسنده , , Ceretha and Slaughter، نويسنده , , Peter and Davis، نويسنده , , Robert E. and Dozier، نويسنده , , Jeff، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Pages :
12
From page :
868
To page :
879
Abstract :
We describe and validate a model that retrieves fractional snow-covered area and the grain size and albedo of that snow from surface reflectance data (product MOD09GA) acquired by NASAʹs Moderate Resolution Imaging Spectroradiometer (MODIS). The model analyzes the MODIS visible, near infrared, and shortwave infrared bands with multiple endmember spectral mixtures from a library of snow, vegetation, rock, and soil. We derive snow spectral endmembers of varying grain size from a radiative transfer model specific to a sceneʹs illumination geometry; spectra for vegetation, rock, and soil were collected in the field and laboratory. We validate the model with fractional snow cover estimates from Landsat Thematic Mapper data, at 30 m resolution, for the Sierra Nevada, Rocky Mountains, high plains of Colorado, and Himalaya. Grain size measurements are validated with field measurements during the Cold Land Processes Experiment, and albedo retrievals are validated with in situ measurements in the San Juan Mountains of Colorado. The pixel-weighted average RMS error for snow-covered area across 31 scenes is 5%, ranging from 1% to 13%. The mean absolute error for grain size was 51 µm and the mean absolute error for albedo was 4.2%. Fractional snow cover errors are relatively insensitive to solar zenith angle. Because MODSCAG is a physically based algorithm that accounts for the spatial and temporal variation in surface reflectances of snow and other surfaces, it is capable of global snow cover mapping in its more computationally efficient, operational mode.
Keywords :
Snow , grain size , Albedo , Spectral Mixture Analysis , MODIS
Journal title :
Remote Sensing of Environment
Serial Year :
2009
Journal title :
Remote Sensing of Environment
Record number :
1629004
Link To Document :
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