Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries

Abstract

The classifi cation of Synthetic Aperture Radar (SAR) images by knowledgebased algorithms with elevation and backscatter thresholds were used in several studies to detect the Wet Snow Radar Zone (WSZ) in the Antarctic Peninsula. To identify it more accurately based on its seasonal variations, this study proposed the additional use of a threshold in synthetic images, created by rationing summer and winter sigma linear images. In our algorithm we used the following thresholds to detect the WSZ in Envisat ASAR imageries, using the Radarsat Antarctic Map Digital Elevation Model as ancillary data: i) -25 dB < s 0 < -14 dB; ii) s linear summer / s linear winter < 0.4; iii) elevation H < 1,200 m for northern tip and H < 800 m for southern tip of the Antarctic Peninsula. The classifi ed images were post-processed by a focal majority 5 x 5 fi lter and superimposed by an image of rock outcrops derived from the Antarctic Digital Database. The ratio image threshold allowed discriminating the WSZ from the Dry Snow Radar Zone and radar shadows, as well as transitional areas between this glacier zone and the Frozen Percolation Radar Zone, which would be classifi ed incorrectly if we used only elevation and backscatter thresholds.

Multispectral Characteristics of Glacier Surface Facies (Chandra-Bhaga Basin, Himalaya, and Ny-Ålesund, Svalbard) through Investigations of Pixel and Object-Based Mapping Using Variable Processing Routines

“…GEOBIA is most accurate, but PBIA is more efficient. Mendes Jr. et al [75] mapped glacier radar facies in Antarctica to retrieve snowmelt by monitoring the wet snow zone. The authors also mapped dry snow, frozen percolation, and bare ice zones.…”