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Urban environments, Beijing case study

Urban environments, Beijing case study
Urban environments, Beijing case study

Various remote sensing methods and demographic datasets are used in the Beijing case study to illustrate their capability to observed physical and demographic characteristics of the urban environment. NL data serve well to identify the outer limit of not only large urban areas but also small settlements. For each large urban contour limit from NL, DSM scatterometer data can detect urban extent and typology. Within each urban type classified by DSM data, Landsat spectral signatures can provide highresolution details of the urban land cover. It is found that DSM s0 has the highest correlation with ambient population of Beijing. To monitor urban change, data can be partitioned into different timescales. The combination of multiple remote sensing methods together with demographic measures is necessary to effectively observe urban environments, rather than each dataset standing alone - both by adding shape and contour to urban population estimates as well as to describe patterns of association between population models and those detecting the rapidly changing built environment. Although Beijing may have local characteristics in detail, it shares many issues of a megacity common to other megacities across the world, where methods and results in this Beijing study can be applicable.

1388-4360
869-878
Springer New York, NY
Nghiem, Son V.
adefb467-c15c-4092-863a-e7833765a6e9
Sorichetta, Alessandro
c80d941b-a3f5-4a6d-9a19-e3eeba84443c
Elvidge, Christopher D.
e36a080a-5b19-43d1-82df-a58671f05f5b
Small, Christopher
15833629-ad6f-4378-ba0d-05a0cd44b975
Balk, Deborah
8e5ec7b6-c51c-484e-acd9-be46c9ba8b7a
Deichmann, Uwe
32fe1228-78e1-4e3f-8ddf-be3f9a19369d
Neumann, Gregory
ef75895d-b2d9-4c9e-add8-0346f026104e
Njoku, Eni G.
Nghiem, Son V.
adefb467-c15c-4092-863a-e7833765a6e9
Sorichetta, Alessandro
c80d941b-a3f5-4a6d-9a19-e3eeba84443c
Elvidge, Christopher D.
e36a080a-5b19-43d1-82df-a58671f05f5b
Small, Christopher
15833629-ad6f-4378-ba0d-05a0cd44b975
Balk, Deborah
8e5ec7b6-c51c-484e-acd9-be46c9ba8b7a
Deichmann, Uwe
32fe1228-78e1-4e3f-8ddf-be3f9a19369d
Neumann, Gregory
ef75895d-b2d9-4c9e-add8-0346f026104e
Njoku, Eni G.

Nghiem, Son V., Sorichetta, Alessandro, Elvidge, Christopher D., Small, Christopher, Balk, Deborah, Deichmann, Uwe and Neumann, Gregory (2014) Urban environments, Beijing case study. In, Njoku, Eni G. (ed.) Encyclopedia of Remote Sensing. (Encyclopedia of Earth Sciences Series) Springer New York, NY, pp. 869-878. (doi:10.1007/978-0-387-36699-9_131).

Record type: Book Section

Abstract

Various remote sensing methods and demographic datasets are used in the Beijing case study to illustrate their capability to observed physical and demographic characteristics of the urban environment. NL data serve well to identify the outer limit of not only large urban areas but also small settlements. For each large urban contour limit from NL, DSM scatterometer data can detect urban extent and typology. Within each urban type classified by DSM data, Landsat spectral signatures can provide highresolution details of the urban land cover. It is found that DSM s0 has the highest correlation with ambient population of Beijing. To monitor urban change, data can be partitioned into different timescales. The combination of multiple remote sensing methods together with demographic measures is necessary to effectively observe urban environments, rather than each dataset standing alone - both by adding shape and contour to urban population estimates as well as to describe patterns of association between population models and those detecting the rapidly changing built environment. Although Beijing may have local characteristics in detail, it shares many issues of a megacity common to other megacities across the world, where methods and results in this Beijing study can be applicable.

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More information

Published date: 1 January 2014

Identifiers

Local EPrints ID: 430875
URI: http://eprints.soton.ac.uk/id/eprint/430875
ISSN: 1388-4360
PURE UUID: 61d73b2b-b697-46e7-8f72-65061a447fa1
ORCID for Alessandro Sorichetta: ORCID iD orcid.org/0000-0002-3576-5826

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Date deposited: 16 May 2019 16:30
Last modified: 17 Mar 2024 12:25

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Contributors

Author: Son V. Nghiem
Author: Christopher D. Elvidge
Author: Christopher Small
Author: Deborah Balk
Author: Uwe Deichmann
Author: Gregory Neumann
Editor: Eni G. Njoku

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