Subpixel Melt Index In Antarctic Peninsula Using Spatially Constrained
Linear Unmixing From Time Series Satellite Passive Microwave Images
Abstract
The inevitable coarse pixels (~25 km) of satellite
passive microwave images introduced large uncertainty to the surface
melt area estimation on Antarctic ice margins. Our test showed that the
melt index of the Austral year 2012-13 in the Antarctic Peninsula
calculated from the high resolution product was 33% lower than the
original Special Sensor Microwave/Imager (SSM/I) images. Therefore, by
allowing for fractional melt estimation, a subpixel mapping method was
adopted in this research to improve the accuracy and reliability of
surface melt measurement from passive microwave images. This innovative
method uses the least squares mixture analysis (LSMA) on the time series
of daily passive microwave images by taking advantage of their high
temporal resolution. The endmembers for the unmixing calculation were
collected under the constraint of voronoi polygons. The fractional melt
index of each pixel was calculated by multiplying its area with melt
fraction. By using the high resolution passive microwave earth system
data record (PMESDR) dataset as the reference, we found that compared
with the original SSM/I images, the overestimation of surface melt was
corrected by the unmixing analysis. A log-linear regression between melt
fraction and elevation showed that the melt fraction is inversely
correlated to the elevation, and the topography is the dominant factor
for melt fraction distribution in high elevations. We recommend such a
treatment of linear unmixing analysis on the passive microwave images to
be used for future surface melt mapping in Antarctica and Greenland.