Fusion of Remote Sensing and Internet Data to Calculate Urban Floor Area Ratio

Xiaoyong Zhang, Zhengchao Chen, Yuemin Yue, Xiangkun Qi and Charlie H. Zhang
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Xiaoyong Zhang: Beijing Key Laboratery of High Dynamic Navigation Technology, University of Beijing Information Science and Technology, Beijing 100101, China
Zhengchao Chen: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
Yuemin Yue: Key Laboratory for Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
Xiangkun Qi: Key Laboratory for Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
Charlie H. Zhang: Department of Geography & Geosciences, University of Louisville, Louisville, KY 40292, USA

Sustainability, 2019, vol. 11, issue 12, 1-18

Abstract: The floor area ratio is a comprehensive index that plays an important role in urban planning and sustainable development. Remote sensing data are widely used in floor area ratio calculations because they can produce both two-dimensional planar and three-dimensional stereo information on buildings. However, remote sensing is not adequate for calculating the number of floors in a building. In this paper, a simple and practical pixel-level model is established through defining a quantitative relationship among the floor area ratio, building density, and average number of floors (ANF). The floor area ratios are calculated by combining remote sensing data with publicly available Internet data. It incorporates supplemental map data and street-level views from Internet maps to confirm building types and the number of floors, thereby enabling more-accurate floor area ratio calculations. The proposed method is tested in the Tiantongyuan neighborhood, Changping District, Beijing, and the results show that it can accurately approximate the number of floors in buildings. Inaccuracies in the value of the floor area ratio were found to be primarily due to the uncertainties in building density calculations. After performing systematic error correction, the building density (BD) and floor area ratio were each calculated with the relative accuracy exceeding 90%. Moreover, the experiments verified that the fusion of internet map data with remote sensing data has innate advantages for floor area ratio calculations.

Keywords: floor area ratio; internet map; remote sensing; street-level view (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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