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.
Urban environments, beijing case study / S.V. Nghiem, A. Sorichetta, C.D. Elvidge, C. Small, D. Balk, U. Deichmann, G. Neumann (ENCYCLOPEDIA OF EARTH SCIENCES). - In: Encyclopedia of Earth Sciences Series / [a cura di] E.G. Njoku. - [s.l] : Springer Netherlands, 2015 Dec 29. - ISBN 978-0-387-36699-9. - pp. 869-878 [10.1007/978-0-387-36699-9_131]
Urban environments, beijing case study
A. SorichettaSecondo
Formal Analysis
;
2014
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.File | Dimensione | Formato | |
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