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Computer Optics, 2019, Volume 43, Issue 1, Pages 90–98
DOI: https://doi.org/10.18287/2412-6179-2019-43-1-90-98
(Mi co608)
 

This article is cited in 2 scientific papers (total in 2 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

A remote sensing and GIS based approach for land use/cover, inundation and vulnerability analysis in Moscow, Russia

K. Choudharyab, M. Booriac, A. V. Kupriyanovad

a Samara National Research University, 443086, Russia, Samara, Moskovskoye Shosse 34
b The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
c American Sentinel University, 2260 South Xanadu Way, Suite 310, Aurora, Colorado 80014, USA
d IPSI RAS - Branch of the FSRC “Crystallography and Photonics” RAS, Molodogvardeyskaya 151, 443001, Samara, Russia
References:
Abstract: 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.
Keywords: LULC, Sea level rise, Landsat data, remote sensing and GIS.
Funding agency Grant number
Ministry of Education and Science of the Russian Federation
Russian Foundation for Basic Research 15-29-03823
16-41-630761
17-01-00972
18-37-00418
Ministry of Science and Higher Education of the Russian Federation 0026-2018-0102
This work was partially supported by the Ministry of education and science of the Russian Federation in the framework of the implementation of the Program of increasing the competitiveness of Samara University among the world’s leading scientific and educational centers for 2013-2020 years; by the Russian Foundation for Basic Research grants (# 15-29-03823, # 16-41-630761, # 17-01-00972, # 18-37-00418), in the framework of the state task # 0026-2018-0102 “Optoinformation technologies for obtaining and processing hyperspectral data”.
Received: 17.07.2018
Accepted: 11.11.2018
Document Type: Article
Language: English
Citation: K. Choudhary, M. Boori, A. V. Kupriyanov, “A remote sensing and GIS based approach for land use/cover, inundation and vulnerability analysis in Moscow, Russia”, Computer Optics, 43:1 (2019), 90–98
Citation in format AMSBIB
\Bibitem{ChoBooKup19}
\by K.~Choudhary, M.~Boori, A.~V.~Kupriyanov
\paper A remote sensing and GIS based approach for land use/cover, inundation and vulnerability analysis in Moscow, Russia
\jour Computer Optics
\yr 2019
\vol 43
\issue 1
\pages 90--98
\mathnet{http://mi.mathnet.ru/co608}
\crossref{https://doi.org/10.18287/2412-6179-2019-43-1-90-98}
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  • https://www.mathnet.ru/eng/co608
  • https://www.mathnet.ru/eng/co/v43/i1/p90
  • This publication is cited in the following 2 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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