Urban Sustainability Evaluation Based on Remote Sensing and Network Data Support: Progress and Prospect |
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| Authors: | Xiaoyu Song Jun Gao Xin Li Weiyue Li Zhonghao Zhang Liangxu Wang Jing Fu Chunlin Huang Feng Gao |
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| Institution: | 1.Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000,China;2.Institute of Urban Study, Shanghai Normal University, Shanghai 200234,China;3.Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101,China |
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| Abstract: | The sustainable development of the city is the key to the realization of the global sustainable development goals. Urban sustainability evaluation is a measure to the sustainable development of cities, and basis of sustainable urban development. The current evaluation method is based on statistical data which is low spatial resolution, long period and high cost. In recent years, remote sensing data, network data and the multivariate data have been used for the evaluation for the sustainable development of cities, and there have been many related research cases, which provides a new idea and method to carry out the high resolution evaluation of urban sustainable development rapidly, accurately and cheaply. This article reviewed the remote sensing data and network data in the progress of the application in the evaluation to the sustainable development of cities, and discussed the advantages of remote sensing and network big data in the objectivity, accuracy, and timeliness of evaluation compared with traditional data. Based on the sustainable urban development indicators of the United Nations Sustainable Development Goals (SDG), a basic framework for the evaluation of sustainable development of cities with high temporal and spatial resolution of big data such as remote sensing data and network big data was proposed. The introduction of remote sensing and network big data will change the inherent paradigm of sustainability assessment, make high-resolution real-time evaluation possible, further innovate analytical techniques, improve data accuracy, and make clear the alternative relationship with traditional data being the focus and the only way to realize the replacement of traditional data by remote sensing and network big data. |
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| Keywords: | Sustainable development goals Urban sustainable development Remote sensing data Network big data |
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