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Global Land Cover Classification Based
on Microwave Polarization and Gradient
Ratio (MPGR)
Mukesh Boori and Ralph Ferraro
Abstract Microwave polarization and gradient ratio (MPGR) is an effective
indicator for characterizing the land surface from sensors like EOS Advanced
Microwave Scanning Radiometer (AMSR-E). Satellite-generated brightness tem-
peratures (BT) are largely in
uenced by soil moisture and vegetation cover. The
MPGR combines the microwave gradient ratio with polarization ratio to determine
surface characteristics (i.e., bare soil/developed, ice, and water) and under cloud
covered conditions when this information cannot be obtained using optical remote
sensing data. This investigation uses the HDF Explorer, Matlab, and ArcGIS
software to process the pixel latitude, longitude, and BT information from the
AMSR-E imagery. This paper uses the polarization and gradient ratio from AMSR-E
BT for 6.9, 10.7, 18.7, 23.8, 36.5, and 89.0 GHz to identify seventeen land cover
types. A smaller MPGR indicates dense vegetation, with the MPGR increasing
progressively for mixed vegetation, degraded vegetation, bare soil/developed, and
ice and water. This information can help improve the characterization of land surface
phenology for use in weather forecasting applications, even during cloudy and
precipitation conditions which often interferes with other sensors.
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Keywords AMSR-E
MODIS
MPGR
Microwave remote sensing
GIS
Climate change
CHAPTER
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