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Proceedings Paper

Shanghai urban green landscape model system based on MapServer
Author(s): Jianxun Rui; Beiqi Shi; Di Shen; Weiqin Yao
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Paper Abstract

Based on RS and GIS, the 2003a's aerial image data of Shanghai is taken as data source. According to the urban green landscape theory, the green landscapes are well classified to park, street green landscape, affiliation green landscape, inhabited green landscape, production green landscape and defending green landscape, et al. Several spatio-temporal models including the space expansion models and ecological analyzing models for urban green landscape have been constructed and calculated. Then, based on the ORDBMS platform PostgreSQL and OGIS MapServer, the urban green landscape database including the above six types green landscapes spatial data and model system of Shanghai have been developed. At last, using the powerful statistics analysis function of the model system, this paper discusses and reveals the impacts of urban space development on green landscape pattern, structure and function. At the same time, the general distribution characteristics of green landscape pattern have been researched at three levels such as green patch level, type level and mosaics structure of different green landscapes. The urban green landscapes model system of Shanghai based on MapServer provides a powerful interactive and perfect platform for governments to make urban planning decisions and landscape study.

Paper Details

Date Published: 5 November 2008
PDF: 8 pages
Proc. SPIE 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics, 714415 (5 November 2008); doi: 10.1117/12.812736
Show Author Affiliations
Jianxun Rui, Shanghai Normal Univ. (China)
Beiqi Shi, Shanghai Institute of Tourism (China)
Di Shen, Shanghai Normal Univ. (China)
Weiqin Yao, Shanghai Normal Univ. (China)


Published in SPIE Proceedings Vol. 7144:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang; Xinhao Wang, Editor(s)

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