Monitoring the light pollution changes of China’s mangrove forests from 1992-2020 using nighttime light data
Mangrove forests are one of the most biologically diverse and productive ecosystems on Earth. They are important breeding and nursing grounds for amphibians, invertebrates, birds, fish, etc. Light pollution may cause serious degradation of biodiversity in the ecosystem. A report of the long-term hol...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-05-01
|
| Series: | Frontiers in Marine Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2023.1187702/full |
| _version_ | 1797821976091295744 |
|---|---|
| author | Haihang Zeng Haihang Zeng Mingming Jia Mingming Jia Rong Zhang Zongming Wang Dehua Mao Chunying Ren Chuanpeng Zhao |
| author_facet | Haihang Zeng Haihang Zeng Mingming Jia Mingming Jia Rong Zhang Zongming Wang Dehua Mao Chunying Ren Chuanpeng Zhao |
| author_sort | Haihang Zeng |
| collection | DOAJ |
| description | Mangrove forests are one of the most biologically diverse and productive ecosystems on Earth. They are important breeding and nursing grounds for amphibians, invertebrates, birds, fish, etc. Light pollution may cause serious degradation of biodiversity in the ecosystem. A report of the long-term holistic views of light pollution changes is essential for sustainable management of mangrove ecosystems. However, to date, such studies have rarely been carried out. This study aimed to monitor the long-term light pollution changes of China’s mangrove forests. To achieve this goal, we used time-series nighttime light (NTL) data to build continuous light pollution data. NTL maps made with DMSP-OLS (DNL) or NPP-VIIRS (VNL) are widely utilized in research on human activity. However, DMSP and VIIRS images are different in spatial resolution, radiation resolution, and data saturation. Thus, this study innovatively set an optimal threshold for generating consistent light pollution data in mangrove areas from 1992-2020. The results showed that: (1) the proportion of light-polluted mangrove forests in China increased from 12% in 1992 to 52% in 2020; (2) the largest net increase occurred in Guangxi with an area of 4,086 ha, followed by Guangdong (3,365 ha) and Hainan (2,944 ha); (3) Zhejiang had the largest proportion of net growth (from 0% in 1992 to 99% in 2020), followed by Hainan (66%) and Fujian (59%). Mangrove forests have been protected and restored for decades in China; this study indicates that the establishment of nature reserves is effective in preventing the light pollution of mangroves and provides the first long-term multi-temporal dataset of light pollution in China’s mangrove forests. This comprehensive information could support related studies and facilitate the development of applicable coastal management strategies in China. |
| first_indexed | 2024-03-13T10:01:59Z |
| format | Article |
| id | doaj.art-374784b0767e4685b0cffeee1b449740 |
| institution | Directory Open Access Journal |
| issn | 2296-7745 |
| language | English |
| last_indexed | 2024-03-13T10:01:59Z |
| publishDate | 2023-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Marine Science |
| spelling | doaj.art-374784b0767e4685b0cffeee1b4497402023-05-23T04:48:58ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452023-05-011010.3389/fmars.2023.11877021187702Monitoring the light pollution changes of China’s mangrove forests from 1992-2020 using nighttime light dataHaihang Zeng0Haihang Zeng1Mingming Jia2Mingming Jia3Rong Zhang4Zongming Wang5Dehua Mao6Chunying Ren7Chuanpeng Zhao8Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, ChinaCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing, ChinaKey Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, ChinaInternational Research Center of Big Data for Sustainable Development Goals, Beijing, ChinaKey Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, ChinaKey Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, ChinaKey Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, ChinaKey Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, ChinaKey Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, ChinaMangrove forests are one of the most biologically diverse and productive ecosystems on Earth. They are important breeding and nursing grounds for amphibians, invertebrates, birds, fish, etc. Light pollution may cause serious degradation of biodiversity in the ecosystem. A report of the long-term holistic views of light pollution changes is essential for sustainable management of mangrove ecosystems. However, to date, such studies have rarely been carried out. This study aimed to monitor the long-term light pollution changes of China’s mangrove forests. To achieve this goal, we used time-series nighttime light (NTL) data to build continuous light pollution data. NTL maps made with DMSP-OLS (DNL) or NPP-VIIRS (VNL) are widely utilized in research on human activity. However, DMSP and VIIRS images are different in spatial resolution, radiation resolution, and data saturation. Thus, this study innovatively set an optimal threshold for generating consistent light pollution data in mangrove areas from 1992-2020. The results showed that: (1) the proportion of light-polluted mangrove forests in China increased from 12% in 1992 to 52% in 2020; (2) the largest net increase occurred in Guangxi with an area of 4,086 ha, followed by Guangdong (3,365 ha) and Hainan (2,944 ha); (3) Zhejiang had the largest proportion of net growth (from 0% in 1992 to 99% in 2020), followed by Hainan (66%) and Fujian (59%). Mangrove forests have been protected and restored for decades in China; this study indicates that the establishment of nature reserves is effective in preventing the light pollution of mangroves and provides the first long-term multi-temporal dataset of light pollution in China’s mangrove forests. This comprehensive information could support related studies and facilitate the development of applicable coastal management strategies in China.https://www.frontiersin.org/articles/10.3389/fmars.2023.1187702/fullnighttime lightlight pollutionmangrove forestsnature reservesChina |
| spellingShingle | Haihang Zeng Haihang Zeng Mingming Jia Mingming Jia Rong Zhang Zongming Wang Dehua Mao Chunying Ren Chuanpeng Zhao Monitoring the light pollution changes of China’s mangrove forests from 1992-2020 using nighttime light data Frontiers in Marine Science nighttime light light pollution mangrove forests nature reserves China |
| title | Monitoring the light pollution changes of China’s mangrove forests from 1992-2020 using nighttime light data |
| title_full | Monitoring the light pollution changes of China’s mangrove forests from 1992-2020 using nighttime light data |
| title_fullStr | Monitoring the light pollution changes of China’s mangrove forests from 1992-2020 using nighttime light data |
| title_full_unstemmed | Monitoring the light pollution changes of China’s mangrove forests from 1992-2020 using nighttime light data |
| title_short | Monitoring the light pollution changes of China’s mangrove forests from 1992-2020 using nighttime light data |
| title_sort | monitoring the light pollution changes of china s mangrove forests from 1992 2020 using nighttime light data |
| topic | nighttime light light pollution mangrove forests nature reserves China |
| url | https://www.frontiersin.org/articles/10.3389/fmars.2023.1187702/full |
| work_keys_str_mv | AT haihangzeng monitoringthelightpollutionchangesofchinasmangroveforestsfrom19922020usingnighttimelightdata AT haihangzeng monitoringthelightpollutionchangesofchinasmangroveforestsfrom19922020usingnighttimelightdata AT mingmingjia monitoringthelightpollutionchangesofchinasmangroveforestsfrom19922020usingnighttimelightdata AT mingmingjia monitoringthelightpollutionchangesofchinasmangroveforestsfrom19922020usingnighttimelightdata AT rongzhang monitoringthelightpollutionchangesofchinasmangroveforestsfrom19922020usingnighttimelightdata AT zongmingwang monitoringthelightpollutionchangesofchinasmangroveforestsfrom19922020usingnighttimelightdata AT dehuamao monitoringthelightpollutionchangesofchinasmangroveforestsfrom19922020usingnighttimelightdata AT chunyingren monitoringthelightpollutionchangesofchinasmangroveforestsfrom19922020usingnighttimelightdata AT chuanpengzhao monitoringthelightpollutionchangesofchinasmangroveforestsfrom19922020usingnighttimelightdata |