Defence Research & Development Organization DRDO

Chandigarh, India

Defence Research & Development Organization DRDO

Chandigarh, India
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Singh M.,Shoolini University of Biotechnology and Management Sciences | Mishra V.D.,Defence Research & Development Organization DRDO | Thakur N.K.,Defence Research & Development Organization DRDO | Sharma J.D.,Shoolini University of Biotechnology and Management Sciences
Journal of the Indian Society of Remote Sensing | Year: 2015

Irregular shape of terrain causes variable illumination angles and diverse reflectance values within same land cover type in optical remote sensing image. It causes problems in image segmentation and misclassification (snow with other land cover). This perception leads to develop an empirical-statistical based topographic correction (ESbTC) algorithm for reflectance modeling after compared with existed topographic correction methods like Cosine correction, C-correction, Minnaert correction, sun–canopy–senor with c-correction (SCS + C) and slope matching, in the context of snow reflectance. An image based atmospheric correction has used in present study included dark-object subtraction (DOS) and effect of Rayleigh scattering on the transmissivity in different spectral bands of AWiFS and MODIS image data. The performance of different models is evaluated using (1) visual analysis, (2) change in snow reflectance on sunny and shady slopes after the corrections, (3) validation with in situ observations and (4) graphical analysis. Further snow cover area (SCA) has been estimated with normalized difference snow index (NDSI) and validated with support vector machine (SVM), a supervised classification technique. The result shows that the proposed algorithm (ESbTC) and slope-matching technique could eliminate most of the shadowing effects in Himalayan rugged terrain and correctly estimate snow reflectance from AWiFS and MODIS imagery as compared with in situ observations whereas other methods significantly underestimate reflectance values after the corrections. © 2015, Indian Society of Remote Sensing.


Singh M.,Shoolini University of Biotechnology and Management Sciences | Mishra V.D.,Defence Research & Development Organization DRDO | Thakur N.K.,Defence Research & Development Organization DRDO | Sharma J.D.,Shoolini University of Biotechnology and Management Sciences
Journal of the Indian Society of Remote Sensing | Year: 2015

Albedo is a critical snow physical parameter that affects the earth’s climate system directly by altering the energy balance at the ground surface and indirectly by controlling the ecosystem processes. Thus spatial variability of snow albedo has immense importance in the study of geomorphology, climate dynamics, seasonal snow melt and hydrology. This paper describes and examines the retrieval of snow albedo for the period October 2012 to May 2013 by using multispectral Advance Wide Field Sensor (AWiFS) on board IRS-P6 of RESOURCESAT-1. The analysis procedure to compute spectral reflectance is achieved by converting the digital numbers after an image based atmospheric and topographic correction that include dark object subtraction (DOS) and effect of Rayleigh scattering on the transmissivity in different spectral bands of AWiFS images. Snow spectral reflectance and satellite derived snow albedo has been validated with in-situ data at the time of satellite pass over the study area using spectroradiometer, pyronometer and Automated Weather Station (AWS) respectively. A fine agreement between satellite derived snow albedo and in-situ measurements shows the relative accuracy of model. Present study also reveal the temporal and spatial variability of snow albedo in a basin which is an evidently indication of the seasonal melt due to decreasing trend in snow depth, snow cover area (SCA) and increased degree day temperature. © 2015, Indian Society of Remote Sensing.

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