Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 1237-1243, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-1237-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 1237-1243, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-1237-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Sep 2017

14 Sep 2017

NIGHT TIME LIGHT SATELLITE DATA FOR EVALUATING THE SOCIOECONOMICS IN CENTRAL ASIA

S. Li1, T. Zhang1, Z. Yang1, X. Li2, and H. Xu3 S. Li et al.
  • 1School of Remote Sensing and Information Engineering, Wuhan University, 430079 Wuhan, China
  • 2State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 430079, Wuhan, China
  • 3School of Economics, Wuhan Donghu University, Wuhan, China

Keywords: Night Light, Remote Sensing, Central Asia, Laws of Social and Economic Development

Abstract. Using nighttime lights data combined with LandScan population counts and socioeconomic statistics, dynamic change was monitored in the social economy of the five countries in Central Asia, from 1993 to 2012. In addition, the spatial pattern of regional historical development was analyzed, using this data. The countries included in this study were Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan and Turkmenistan. The economic development in these five Central Asian countries, the movement of the economic center, the distribution of poor areas and the night light development index (NLDI) were studied at a relatively fine spatial scale. In addition, we studied the relationship between the per capita lighting and per capita GDP at the national scale, finding that the per capital lighting correlated with per capita GDP. The results of this study reflect the socioeconomic development of Central Asia but more importantly, show that nighttime light satellite images are an effective tool for monitoring spatial and temporal social economic parameters.