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Detection of Earth surface changes are essential to monitor regional climatic, snow avalanche hazard analysis and energy balance studies that occur due to air temperature irregularities. Geographic Information System (GIS) enables such research activities to be carried out through change detection analysis. From this viewpoint, different change detection algorithms have been developed for land-use land-cover (LULC) region. Among the different change detection algorithms, change vector analysis (CVA) has level headed capability of extracting maximum information in terms of overall magnitude of change and the direction of change between multi-spectral bands from multi-temporal satellite data sets. Since past two–three decades, many effective CVA based change detection techniques e.g., improved change vector analysis (ICVA), modified change vector analysis (MCVA) and change vector analysis …