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Mapping and Monitoring Urban Ecosystem Services Using Multitemporal High-Resolution Satellite Data.

Authors :
Haas, Jan
Ban, Yifang
Source :
IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing; Jan2017, Vol. 10 Issue 2, p669-680, 12p
Publication Year :
2017

Abstract

This study aims at providing a new method to efficiently analyze detailed urban ecological conditions at the example of Shanghai, one of the world's most densely populated megacities. The main objective is to develop a method to effectively analyze high-resolution optical satellite data for mapping of ecologically important urban space and to evaluate ecological changes through the emerging ecosystem service supply and demand concept. Two IKONOS and GeoEye-1 scenes were used to determine land use/land cover change in Shanghai's urban core from 2000 to 2009. After preprocessing, the images were segmented and classified into seven distinct urban land use/land cover classes through SVM. The classes were then transformed into ecosystem service supply and demand budgets for regulating, provisioning and cultural services, and ecological integrity based on ecosystem functions. Decreases in continuous urban fabric and industrial areas in the favor of urban green sites and high-rise areas with commercial/residential function could be observed resulting in an increase of at least 20% in service supply budgets. Main contributor to the change is the decrease in continuous urban fabric and industrial areas. The overall results and outcome of the study strengthen the suggested application of the proposed method for urban ecosystem service budget mapping with hitherto for that purpose unutilized high-resolution data. The insights and results from this study might further contribute to sustainable urban planning, prove common grounds for interurban comparisons, or aid in enhancing ecological intraurban functionality by analyzing the distribution of urban ecospace and lead to improved accessibility and proximity to ecosystem services in urban areas. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
19391404
Volume :
10
Issue :
2
Database :
Complementary Index
Journal :
IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing
Publication Type :
Academic Journal
Accession number :
121012983
Full Text :
https://doi.org/10.1109/JSTARS.2016.2586582