Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 1341-1348, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-1341-2017
© 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, 1341-1348, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-1341-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Sep 2017

14 Sep 2017

ANALYSIS OF HUMAN ACTIVITIES IN NATURE RESERVES BASED ON NIGHTTIME LIGHT REMOTE SENSING AND MICROBLOGGING DATA –ILLUSTRATED BY THE CASE OF NATIONAL NATURE RESERVES IN JIANGXI PROVINCE

F. Shi1, X. Li2, and H. Xu3 F. Shi et al.
  • 1School of Remote Sensing and Information Engineering, Wuhan University, China
  • 2State Key Laboratory of Information Engineering in Surveying ,Wuhan University, China
  • 3School of Economics, Wuhan Donghu University, China

Keywords: The study used the mainstream social media in china - Sina microblogging data combined with nighttime light remote sensing and various geographical data to reveal the pattern of human activities and light pollution of the Jiangxi Provincial National Natur

Abstract. The study used the mainstream social media in china - Sina microblogging data combined with nighttime light remote sensing and various geographical data to reveal the pattern of human activities and light pollution of the Jiangxi Provincial National Nature Reserves. Firstly, we performed statistical analysis based on both functional areas and km-grid from the perspective of space and time, and selected the key areas for in-depth study. Secondly, the relationship between microblogging data and nighttime light remote sensing, population, GDP, road coverage, road distance and road type in nature reserves was analyzed by Spearman correlation coefficient method, so the distribution pattern and influencing factors of the microblogging data were explored. Thirdly, a region where the luminance value was greater than 0.2 was defined as a light region. We evaluated the management status by analyzing the distribution of microblogging data in both light area and non-light area. Final results showed that in all nature reserves, the top three were the Lushan Nature Reserve, the Jinggangshan Nature Reserve, the Taohongling National Nature Reserve of Sikas both on the total number and density of microblogging ; microblogging had a significant correlation with nighttime light remote sensing , the GDP, population, road and other factors; the distribution of microblogging near roads in protected area followed power laws; luminous radiance of Lushan Nature Reserve was the highest, with 43 percent of region was light at night; analysis combining nighttime light remote sensing with microblogging data reflected the status of management of nature reserves.