RUS  ENG JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB
General information
Latest issue
Archive

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Computer Optics:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Computer Optics, 2017, Volume 41, Issue 4, Pages 528–534 (Mi co416)  

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

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”.


DOI: https://doi.org/10.18287/2412-6179-2017-41-4-528-534

Full text: PDF file (1182 kB)
Full text: http://www.computeroptics.smr.ru/.../410410.html
References: PDF file   HTML file

Received: 19.03.2017
Accepted:28.06.2017
Language:

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}


Linking options:
  • http://mi.mathnet.ru/eng/co416
  • http://mi.mathnet.ru/eng/co/v41/i4/p528

    SHARE: VKontakte.ru FaceBook Twitter Mail.ru Livejournal Memori.ru


    Citing articles on Google Scholar: Russian citations, English citations
    Related articles on Google Scholar: Russian articles, English articles
  • Computer Optics
    Number of views:
    This page:121
    Full text:43
    References:19

     
    Contact us:
     Terms of Use  Registration  Logotypes © Steklov Mathematical Institute RAS, 2020