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

Ziyang Cao,Meng Wang,Yaoqiu Kuang,Zhifeng Wu,Ningsheng Huang

doi:10.3390/su8020108

Abstract

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.

Highlights

With the intensification of research on global change, increasing attention has been paid to the interaction mechanism between human activities and the environment [1]
In order to verify the results of the intercalibration of radiance-calibrated nighttime light (RC nighttime light (NTL)) time series images for Guangdong, the sum of light intensity (DN values) are compared between the RC NTL and IC-RC NTL images
This comparison was done for both the RC NTL images that were subjected to intercalibration and light overflow correction (T-IC-RC NTL images) (Figure 4a,c,e,g), and RC NTL images that were subjected to intercalibration, light overflow correction, and outlier removal (RO-T-IC-RC NTL images)

Summary

Introduction

With the intensification of research on global change, increasing attention has been paid to the interaction mechanism between human activities and the environment [1]. As the largest developing country, China has undergone a period of rapid development in the last thirty years During this period, the relationships between human activities (including expansion of urban areas, economies, and populations) and environmental change have gradually intensified, and an increasing number of studies have focused on this problem [2,3]. The first type of data is usually provided on the basis of administrative units, and the second type of data is usually available in grid or raster formats. This causes a spatial mismatch between these datasets [5,6]. Rasterizing GDP data has become a core issue in the related literature

Methods

Results

Conclusion