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A Simple Method to Improve Estimates of County-Level Economics in China Using Nighttime Light Data and GDP Growth Rate

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Journal of Shandong University (Philosophy and Social Sciences) Editorial Department, Shandong University, Jinan 250013, China
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Institute of New Structural Economics, National School of Development, Peking University, Beijing 100871, China
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Department of Geography, Dartmouth College, Hanover, MA 03755, USA
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College of Tourism & Geography Science, Yunnan Normal University, Kunming 650500, China
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Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(9), 419; https://doi.org/10.3390/ijgi8090419
Received: 24 July 2019 / Revised: 13 September 2019 / Accepted: 16 September 2019 / Published: 18 September 2019
County-level economic statistics estimation using remotely sensed data, such as nighttime light data, has various advantages over traditional methods. However, uncertainties in remotely sensed data, such as the saturation problem of the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) NSL (nighttime stable lights) data, may influence the accuracy of this remote sensing-based method, and thus hinder its use. This study proposes a simple method to address the saturation phenomenon of nighttime light data using the GDP growth rate. Compared with other methods, the NSL data statistics obtained using the new method reflect the development of economics more accurately. We use this method to calibrate the DMSP-OLS NSL data from 1992 to 2013 to obtain the NSL density data for each county and linearly regress them with economic statistics from 2004 to 2013. Regression results show that lighting data is highly correlated with economic data. We then use the light data to further estimate the county-level GDP, and find that the estimated GDP is consistent with the authoritative GDP statistics. Our approach provides a reliable way to capture county-level economic development in different regions. View Full-Text
Keywords: DMSP-OLS data; NSL Saturation; GDP growth rate; County-level Economic Development; Long-term Time Series DMSP-OLS data; NSL Saturation; GDP growth rate; County-level Economic Development; Long-term Time Series
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Ji, X.; Li, X.; He, Y.; Liu, X. A Simple Method to Improve Estimates of County-Level Economics in China Using Nighttime Light Data and GDP Growth Rate. ISPRS Int. J. Geo-Inf. 2019, 8, 419.

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