High Resolution Remote Sensing Based Ecological Indicators for Evaluating Urban Ecological Quality

Authors: Huiping Huang*, (1) Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, (2) University of Illinois at Urban and Champaign, Zhe Zhang*, University of Illinois at Urban and Champaign, Qiangzi Li, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Yuan Zhang, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Shaowen Wang*, University of Illinois at Urbana-Champaign
Topics: Remote Sensing, Geography and Urban Health, Spatial Analysis & Modeling
Keywords: Remote Sensing, Ecological Indicators, Urban Ecological Quality
Session Type: Paper
Day: 4/11/2018
Start / End Time: 8:00 AM / 9:40 AM
Room: Astor Ballroom I, Astor, 2nd Floor
Presentation File: No File Uploaded


Urbanization is one of the greatest challenges of the society. It causes a series of problems including biodiversity loss, lengthy drought, heat island effect, water quality deterioration, atmospheric pollution, disease spreading, and other negative effects. Therefore, urban land use and ecosystem planning need to be integrated into a green framework by developing ecological indicators to evaluate urban ecological quality and promote ecologically sustainable development. Various types of remote sensing based ecological indicators have been developed for monitoring ecological status of urban area with advantages of performing large area, rapid, and periodically repeated earth observations. However, most remote sensing based ecological indicators are based on low spatial resolution data and ignore the landscape pattern, which causes imprecise ecological evaluation. In this article, we developed high resolution remote sensing based ecological indicators using 4 meters GaoFen-2 high resolution remote sensing data. Based on this high-resolution dataset, we present innovative ecological indicators that take into consideration both landscape pattern and vegetation condition of urban area of Haidian District, Beijing. Factor analysis was used to analyze the correlations between six ecological indicators and get factor scores for the evaluation of urban ecological quality. The comprehensive urban ecological quality evaluation method proposed in this article can be easily extended to other urban areas, and can be flexibly applied using either high or low resolution remote sensing images, and therefore is expected to contribute to the community of urban ecological quality evaluation.

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