Assessing Data Integrity of OpenStreetMap Based on Night Lights
Fei Liu1,Xiaoqiang Cheng2,4(),Huayi Wu1,3
1 State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China 2 Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China 3 Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China 4 Key Laboratory of Regional Development and Environmental Response, Wuhan 430062, China
[Objective] This paper aims to address data integrity issues facing the OpenStreetMap (OSM) datasets. [Methods] First, we retrieved the remote censor images of night-lighting brightness as an indicator for cities with strong comprehensive competitiveness. Then, we studied the correlation between night-lighting brightness and OSM completeness, which identified the distribution patterns of high quality data. [Results] We established a regression model for OSM building density and night-lighting brightness. The correlation coefficient was 0.8522. We also found that 84.2% of Chinese cities in our study had building densities closed to the predicted values (the discrepancy was less than 0.5%). The building densities in the other cities were 2% to 7% lower than the expected values. [Limitations] More research is needed to evaluate the performance of this model with other cities. [Conclusions] The remote sensing images help us assess quality of OSM data, which also identifies the “ghost or empty cities”.
刘菲,成晓强,吴华意. 基于夜间灯光亮度的OpenStreetMap数据完整性检验 *[J]. 数据分析与知识发现, 2019, 3(9): 36-44.
Fei Liu,Xiaoqiang Cheng,Huayi Wu. Assessing Data Integrity of OpenStreetMap Based on Night Lights. Data Analysis and Knowledge Discovery, 2019, 3(9): 36-44.
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