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Computer Optics, 2017, Volume 41, Issue 4, Pages 528–534
DOI: https://doi.org/10.18287/2412-6179-2017-41-4-528-534
(Mi co416)
 

This article is cited in 6 scientific papers (total in 6 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

Mapping and evaluating urban density patterns in Moscow, Russia

K. Choudharya, M. Booriabc, A. V. Kupriyanovda

a Samara National Research University, Samara, Russia
b American Sentinel University, Denver, Colorado, USA
c Bonn University, Bonn, Germany
d Image Processing Systems Institute of the RAS - Branch of the FSRC "Crystallography and Photonics" RAS, Samara, Russia
References:
Abstract: The defense of the notion of ‘compact city’ as a strategy to reduce urban sprawl to support greater utilization of existing infrastructure and services in more compact areas and to improve the connectivity of employment hubs is actively discussed in urban research. Using the urban residential density as a surrogate measure for urban compactness, this paper empirically examines a cadaster database that contains details of every property with a view of capturing changes in urban residential density patterns across Moscow using geospatial techniques. The policy of densification in chase of a more compact city has produced mixed results. Findings of this study signal that the urban densities across the buffer zones around Moscow city are significantly different. The Landsat images from 1995, 2005 and 2016 are classified based on the maximum likelihood to expand the land use/cover maps and identify the land cover. Then, the area coverage for all the land use/cover types at different points in time is combined with the distance from the city center. After that, urbanization densities from the city center toward the outskirts for every 1-km distance from 1 to 60 km are calculated. The city density on the distance of 1 to 35 km is found to be very high in the years 1995 to 2016. As usual, the population, traffic conditions, industrialization and government policy are the major factors that influenced the urban expansion.
Keywords: density, compact city, land use/cover, buffer zones.
Funding agency Grant number
Russian Science Foundation 14-31-00014
This work was financially supported by the Russian Science Foundation (RSF), grant no. 14-31-00014 “Establishment of a Laboratory of Advanced Technology for Earth Remote Sensing”.
Received: 19.03.2017
Accepted: 28.06.2017
Document Type: Article
Language: English
Citation: K. Choudhary, M. Boori, A. V. Kupriyanov, “Mapping and evaluating urban density patterns in Moscow, Russia”, Computer Optics, 41:4 (2017), 528–534
Citation in format AMSBIB
\Bibitem{ChoBooKup17}
\by K.~Choudhary, M.~Boori, A.~V.~Kupriyanov
\paper Mapping and evaluating urban density patterns in Moscow, Russia
\jour Computer Optics
\yr 2017
\vol 41
\issue 4
\pages 528--534
\mathnet{http://mi.mathnet.ru/co416}
\crossref{https://doi.org/10.18287/2412-6179-2017-41-4-528-534}
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  • https://www.mathnet.ru/eng/co/v41/i4/p528
  • This publication is cited in the following 6 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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