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Mapping global mangrove canopy height by integrating Ice, Cloud, and Land Elevation Satellite-2 photon-counting LiDAR data with multi-source images.
Yu, Jianan; Nie, Sheng; Liu, Wenjie; Zhu, Xiaoxiao; Sun, Zhongyi; Li, Jiatong; Wang, Cheng; Xi, Xiaohuan; Fan, Hongchao.
Afiliação
  • Yu J; Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province, School of Ecology, Hainan University, Haikou 570228, China; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Scienc
  • Nie S; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China. Electronic address: niesheng@aircas.ac.cn.
  • Liu W; Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province, School of Ecology, Hainan University, Haikou 570228, China. Electronic address: liuwj@hainanu.edu.cn.
  • Zhu X; Key Laboratory of Seismic and Volcanic Hazards, Institute of Geology, China Earthquake Administration, Beijing 100029, China.
  • Sun Z; Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province, School of Ecology, Hainan University, Haikou 570228, China.
  • Li J; Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province, School of Ecology, Hainan University, Haikou 570228, China.
  • Wang C; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.
  • Xi X; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China.
  • Fan H; Department of Civil and Environmental Engineering, The Norwegian University of Science and Technology, Trondheim 7491, Norway.
Sci Total Environ ; 939: 173487, 2024 Aug 20.
Article em En | MEDLINE | ID: mdl-38810758
ABSTRACT
Large-scale and precise measurement of mangrove canopy height is crucial for understanding and evaluating wetland ecosystems' condition, health, and productivity. This study generates a global mangrove canopy height map with a 30 m resolution by integrating Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) photon-counting light detection and ranging (LiDAR) data with multi-source imagery. Initially, high-quality mangrove canopy height samples were extracted using meticulous processing and filtering of ICESat-2 data. Subsequently, mangrove canopy height models were established using the random forest (RF) algorithm, incorporating ICESat-2 canopy height samples, Sentinel-2 data, TanDEM-X DEM data and WorldClim data. Furthermore, a global 30 m mangrove canopy height map was generated utilizing the Google Earth Engine platform. Finally, the global map's accuracy was evaluated by comparing it with reference canopy heights derived from both space-borne and airborne LiDAR data. Results indicate that the global 30 m resolution mangrove height map was found to be consistent with canopy heights obtained from space-borne (r = 0.88, Bisa = -0.07 m, RMSE = 3.66 m, RMSE% = 29.86 %) and airborne LiDAR (r = 0.52, Bisa = -1.08 m, RMSE = 3.39 m, RMSE% = 39.05 %). Additionally, our findings reveal that mangroves worldwide exhibit an average height of 12.65 m, with the tallest mangrove reaching a height of 44.94 m. These results demonstrate the feasibility and effectiveness of using ICESat-2 data integrated with multi-source imagery to generate a global mangrove canopy height map. This dataset offers reliable information that can significantly support government and organizational efforts to protect and conserve mangrove ecosystems.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article