GDP estimation model of county areas based on NPP/VIIRS satellite nighttime light data
Chenyang QU1,2,3, Li ZHANG2,3, Mingquan WANG2,3, Maohua WANG2,3
1. School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China 2. Key Laboratory of Low-Coal Conversion Science and Engineering, Chinese Academy of Sciences, Shanghai 201210, China 3. Shanghai Carbon Data Research Center, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China
Based on the NPP/VIIRS nighttime lighting data, the authors constructed a panel regression model to estimate the county GDP of some counties where the new high-speed railway was located in 2013—2018. In this paper, the NPP/VIIRS data was firstly based on the maximum estimation of the correction process, and the night light-GDP panel regression model was established for GDP estimation. The results show that, among the 25 counties, 16 counties have a correlation coefficient R2 of 0.9 or more. The R2 of the six county-level regions is between 0.85 and 0.9, which confirms that the NPP/VIIRS satellite nighttime lighting data changes and the economic growth of the county where the new high-speed railway station is located shows a good and long-term stable positive correlation. At the same time, the authors made a brief analysis of the impact of high-speed rail and county-level economic development, and argued that it is feasible for the panel data model to fit the NPP/VIIRS satellite nighttime lighting data and to estimate the GDP of the counties where the new high-speed railway is located.
屈辰阳, 张莉, 汪鸣泉, 王茂华. 基于NPP/VIIRS卫星夜光数据的新建高铁站所在县域的GDP估算模型[J]. 国土资源遥感, 2020, 32(2): 81-87.
Chenyang QU, Li ZHANG, Mingquan WANG, Maohua WANG. GDP estimation model of county areas based on NPP/VIIRS satellite nighttime light data. Remote Sensing for Land & Resources, 2020, 32(2): 81-87.
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2020, Vol. 32 
