Coupling an Intercalibration of Radiance-Calibrated Nighttime Light Images and Land Use/Cover Data for Modeling and Analyzing the Distribution of GDP in Guangdong, China

Spatialized GDP data is important for studying the relationships between human activities and environmental changes. Rapid and accurate acquisition of these datasets are therefore a significant area of study. Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) radiance-calibrated nighttime light (RC NTL) images exhibit the potential for providing superior estimates for GDP spatialization, as they are not restricted by the saturated pixels which exist in nighttime stable light (NSL) images. However, the drawback of light overflow is the limited accuracy of GDP estimation, and GDP data estimations based on RC NTL images cannot be directly used for temporal analysis due to a lack of on-board calibration. This study develops an intercalibration method to address the comparability problem. Additionally, NDVI images are used to reduce the light overflow effect. In this way, the secondary and tertiary industry outputs are estimated by using intercalibrated RC NTL images. Primary industry production is estimated by using land use/cover data. Ultimately, four 1 km gridded GDP maps of Guangdong for 2000, 2004, 2006 and 2010 are generated. The verification results of the proposed intercalibration method demonstrate that this method is reasonable and can be effectively implemented. These maps can be used to analyze the distribution and spatiotemporal changes of GDP density in Guangdong. © 2016 by the authors.