A remote sensing and GIS based approach for land use/cover, inundation and vulnerability analysis in Moscow, Russia
Choudhary K., Boori M.S., Kupriyanov A.V.


Samara National Research University, 443086, Russia, Samara, Moskovskoye Shosse 34;
American Sentinel University, 2260 South Xanadu Way, Suite 310, Aurora, Colorado 80014, USA;
IPSI RAS - Branch of the FSRC “Crystallography and Photonics” RAS, Molodogvardeyskaya 151, 443001, Samara, Russia;

The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong


Monitoring of land use/cover (LULC) change is very important for sustainable development planning study. This research work is to understand natural and environmental situation and its cause such as intensity, distribution and socio and economic effects in Moscow, Russia based on remote sensing and Geographical Information System techniques. A model was developed by following thematic layers: land use/cover, vegetation, soil, geomorphology and geology in ArcGIS 10.2 software using multi-spectral satellite data obtained from Landsat 7 and 8 for the years of 1995, 2005 and 2016 respectively. Increasing scientific and political interest in regional aspects of global environmental changes, there is a strong stimulus to better understand the patterns causes and environmental consequences of LULC expansion in the elevation of Moscow state, one of the areas in the nation with fast economic growth and high population density. A 70 to 300 m inundation land loss scenarios for surface water and sea level rise (SLR) were developed using digital elevation models of study site topography through remote sensing and GIS techniques by ASTER GDEM and Landsat OLI data. The most severely impacted sectors are expected to be the vegetation, wetland and the natural ecosystem. Improved understanding of the extent and response of SLR will help in preparing for adaptation.

LULC, Sea level rise, Landsat data, remote sensing and GIS.

Choudhary K, Boori MS, Kupriyanov A.V. A remote sensing and GIS based approach for land use/cover, inundation and vulnerability analysis in Moscow, Russia. Computer Optics 2019; 43(1): 90-98. DOI: 10.18287/2412-6179-2019-43-1-90-98.


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