Be the first to like this
Himalayan snow cover area(SCA) is an essential parameter for environmental, meteorological, hydrological and climatologically applications. Due to the hostile climate condition and remoteness of Himalaya, it is very difficult to estimate the SCA. Conventional methods have limitations in measuring SCA in this region especially during extreme weather condition. Optical remote sensing have given good results of SCA in cloud free conditions. But haze, fog and cloud in the snow melting season hinders the capability of optical SCA estimation. Passive microwave remote sensing have given good results in low forested areas. In the dense forest, passive microwave does not provides accurate SCA estimation. The Himalayan glacier and snow lines are very poorly surveyed and continuous monitoring is needed. Comprehensive measurement of SCA has been made in major forested area around the world, but there remains a significant gap in Himalayan snow cover research. Microwave remote sensing with its all weather and cloud penetration ability has already proven good result in estimating SCA in forest and mountainous areas. Considering the Himalayas and coniferous forest characteristics - SCA determining methodology using SAR data have been done for this region in this study. The microwave scattering models - Water Cloud model and Semi-empirical model have been used to estimate the radar backscattering contribution of forest and snow below the forest from the total backscatter using L-band and C-band SAR data. Once the modelling has been done by using the forest in-situ measurements, the forest backscatter contribution have been subtracted to get the backscatter contribution from wet snow covered forest floor. Single reference ratio technique have been used on the forest floor backscatter to determine wet SCA. The forest backscatter Water Cloud Model in L-band have shown a promising result with low RMSE and high coefficient of determination. After the forest minimisation with this model, the SCA estimation (33 Km^2) have shown good co-relation (94%) with MODIS SCA estimation (35 Km^2). Semi-empirical backscatter model with C-band have not able to give much comprehensive result due to fluctuating model parameters. The SCA estimation is not reliable for consideration, although the co-relation with MODIS snow cover estimation is high. The C-band have been tried with Water Cloud Model, which gave a better model with low RMSE and high coefficient of determination. The SCA estimation (35 Km^2) from this have show a good symmetry (97%) with the MODIS SCA estimation (36 Km^2).