MAPPING OF GLACIERS SENSITIVITY SPATIAL TOPOLOGY IN NORTH-WEST HIMALAYA USING SPATIAL MODELING

Seema Mehra Parihar, Ram Kumar Singh, Ashish Gahlot, Sumit Thapa

Abstract


The Study aimed to observe the changes in the glacier post “Himalayan-Tsunami” flood in Uttarakhand region during June 2013, which proved to be a catastrophe for the region, and its effect on Glacier Area Coverage, surrounding Vegetation cover classes and Surface Temperature.

In this study, for reliable mapping of the changes in Glacial region and its surrounding vegetation area, Remote Sensing data derived parameters like statistical measures of ground correlated spatial values NDSI(Normalized Difference Snow Index), changes in the land cover class area, temperatures variation during both Pre-Monsoon and Post-Monsoon (Summer and Winter Season) for more than one decade of data was analyzed. Spatial Modeling was used to semi-automate the process to get the desired output. Parallel analysis using surrounding pixels was used to determine various parameters NDVI (Normalized Difference Vegetation Index), NDVI-categorization for vegetation class. Land surface temperature is also undertaken for the study using temporal images for more than a decade.

 Acquisition of Remote sensing data was done from the satellite sensors Landsat TM5 (Thematic Mapper 5) and ETM+ (Enhanced Thematic Mapper plus), MODIS (Moderate Resolution Imaging Spectroradiometer) Terra 11A1, Survey of India toposheet 1:50000 Scale for demarcation of AOI (Area of Interest), collection of ground control points using field survey. Atmospheric correction was applied on Raw Image Data to get normalized reflectance value after considering the correction for Solar Elevation and Solar Distance, and sensor energy calibration measures (LMax/LMin and Bais/Gain in reflectance value) was estimated. The indices NDSI was calculated using ratio of band Green and band SWIR for classifying snow bound areas. NDVI (Normalized Difference Vegetation Index) was calculated using ratio of band Red and band NIR for classifying forest classes using temporal data. ERDAS Spatial Modeler is used to semi-automate valued parameters to categories and create Snow-Ice map. MODIS Terra 11A1 monthly data for a decade was used to know land surface temperature and its sensitivity. Change detection was carried out using pre-monsoon and post-monsoon Landsat data for analysis on the basis of image classification, image difference and its region demarcation.

Sensitivity analysis observes the resultant changes occurred in terms of dimensions, temperature- statistic and land use and land cover on temporal datasets. In year 2013 post monsoon forest class decreased and same level of change was not observed during decade in snow- glacier region.


Keywords


Glacial Mapping, Spatial Modelling, Land Surface Temperature, Temperature changes at glaciers and forest class changes after Himalayan-Tsunami June2013 in Uttarakhand region.

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