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Characterizing Light Pollution Trends across Protected Areas in China Using Nighttime Light Remote Sensing Data

1,2, 1,3,4,*, 1,2, 1,3,4,*, 1,3,4, 1,3,4, 1,3,4, 1,2 and 1,2
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
University of Chinese Academy of Sciences, Beijing 100049, China
Key Laboratory of Earth Observation Hainan Province, Sanya 572029, China
Sanya Institute of Remote Sensing, Sanya 572029, China
Authors to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(7), 243;
Received: 27 April 2018 / Revised: 13 June 2018 / Accepted: 18 June 2018 / Published: 22 June 2018
PDF [5653 KB, uploaded 22 June 2018]


Protected areas (PAs) with natural, ecological, and cultural value play important roles related to biological processes, biodiversity, and ecosystem services. Over the past four decades, the spatial range and intensity of light pollution in China has experienced an unprecedented increase. Few studies have been documented on the light pollution across PAs in China, especially in regions that provide a greater amount of important biodiversity conservation. Here, nighttime light satellite images from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) were selected to characterize light pollution trends across PAs using nighttime light indexes and hot spot analysis, and then the light pollution changes in PAs were classified. Furthermore, the causes of light pollution changes in PAs were determined using high-resolution satellite images and statistical data. The results showed the following: (1) Approximately 57.30% of PAs had an increasing trend from 1992 to 2012, and these PAs were mainly located in the eastern region, the central region, and a small part of the western region of China. Hot spot analysis showed that the patterns of change for the total night light and night light mean had spatial agglomeration characteristics; (2) The PAs affected by light pollution changes were divided into eight classes, of which PAs with stable trends accounted for 41%, and PAs with high increasing trends accounted for 10%. PAs that had high increasing trends with low density accounted for the smallest amount, i.e., only 1%; (3) The factors influencing light pollution changes in PAs included the distance to urban areas, mineral exploitation, and tourism development and the migration of residents. Finally, based on the status of light pollution encroachment into PAs, strategies to control light pollution and enhance the sustainable development of PAs are recommended. View Full-Text
Keywords: protected areas; light pollution; time series; DMSP-OLS; sustainable development; China protected areas; light pollution; time series; DMSP-OLS; sustainable development; China

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Jiang, W.; He, G.; Leng, W.; Long, T.; Wang, G.; Liu, H.; Peng, Y.; Yin, R.; Guo, H. Characterizing Light Pollution Trends across Protected Areas in China Using Nighttime Light Remote Sensing Data. ISPRS Int. J. Geo-Inf. 2018, 7, 243.

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