{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:14:54Z","timestamp":1774120494326,"version":"3.50.1"},"reference-count":82,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,16]],"date-time":"2019-09-16T00:00:00Z","timestamp":1568592000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation\uff0cMinistry of Land and Resources","award":["KF-2018-03-038"],"award-info":[{"award-number":["KF-2018-03-038"]}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["41361090"],"award-info":[{"award-number":["41361090"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Hainan Island is the second-largest island in China and has the most species-diverse mangrove forests in the country. To date, the height and aboveground ground biomass (AGB) of the mangrove forests on Hainan Island are unknown, partly as a result of the challenges faced during extensive field sampling in mangrove habitats (intertidal mudflats inundated by periodic seawater). Therefore, this study used a low-cost UAV-LiDAR (light detection and ranging sensor mounted on an unmanned aerial vehicle) system as a sampling tool and Sentinel-2 imagery as auxiliary data to estimate and map the mangrove height and AGB on Hainan Island. Hainan Island has 3697.02 hectares of mangrove forests with an average patch area of approximately 1 ha. The results show that the mangroves on whole Hainan Island have an average height of 6.99 m, a total AGB of 474,199.31 Mg and an AGB density of 128.27 Mg ha\u22121. The AGB hot spots are located in Qinglan Harbor and the south of Dongzhai Harbor. The proposed height model LiDAR-S2 performed well with an R2 of 0.67 and an RMSE (root mean square error) of 1.90 m; the proposed AGB model G~LiDAR~S2 performed better (an R2 of 0.62 and an RMSE of 50.36 Mg ha\u22121) than the traditional AGB model G~S2 that directly related ground plots and Sentinel-2 data. The results also indicate that the LiDAR metrics describing the canopy\u2019s thickness and its top and bottom characteristics are the most important variables for mangrove AGB estimation. For the Sentinel-2 indices, the red-edge and shortwave infrared features, especially the red-edge 1 and shortwave infrared Band 11 features, play the most important roles in estimating mangrove AGB and height. In conclusion, this paper presents the first mangrove height and AGB maps of Hainan Island and demonstrates the feasibility of using UAV-LiDAR as a sampling tool for mangrove forests.<\/jats:p>","DOI":"10.3390\/rs11182156","type":"journal-article","created":{"date-parts":[[2019,9,17]],"date-time":"2019-09-17T03:31:46Z","timestamp":1568691106000},"page":"2156","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["Mapping Height and Aboveground Biomass of Mangrove Forests on Hainan Island Using UAV-LiDAR Sampling"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9454-8314","authenticated-orcid":false,"given":"Dezhi","family":"Wang","sequence":"first","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), Lumo road 388, Wuhan 430074, China"},{"name":"National Engineering Research Center of Geographic Information System, Lumo road 388, Wuhan 430074, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2387-5419","authenticated-orcid":false,"given":"Bo","family":"Wan","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), Lumo road 388, Wuhan 430074, China"},{"name":"National Engineering Research Center of Geographic Information System, Lumo road 388, Wuhan 430074, China"}]},{"given":"Penghua","family":"Qiu","sequence":"additional","affiliation":[{"name":"College of Geography and Environmental Science, Hainan Normal University, Longkun South Street 99, Haikou 571158, China"}]},{"given":"Zejun","family":"Zuo","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), Lumo road 388, Wuhan 430074, China"},{"name":"National Engineering Research Center of Geographic Information System, Lumo road 388, Wuhan 430074, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5570-6391","authenticated-orcid":false,"given":"Run","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), Lumo road 388, Wuhan 430074, China"},{"name":"National Engineering Research Center of Geographic Information System, Lumo road 388, Wuhan 430074, China"}]},{"given":"Xincai","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Geography and Information Engineering, China University of Geosciences (Wuhan), Lumo road 388, Wuhan 430074, China"},{"name":"National Engineering Research Center of Geographic Information System, Lumo road 388, Wuhan 430074, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1111\/j.1466-8238.2010.00584.x","article-title":"Status and distribution of mangrove forests of the world using earth observation satellite data","volume":"20","author":"Giri","year":"2011","journal-title":"Glob. 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