Knowledge Management System Of Institute Of Botany,CAS
| Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery | |
Wang, Dezhi1; Wan, Bo1; Liu, Jing2,3; Su, Yanjun4; Guo, Qinghua4 ; Qiu, Penghua5; Wu, Xincai1
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| 2020 | |
| 发表期刊 | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
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| ISSN | 1569-8432 |
| 卷号 | 85 |
| 摘要 | The mangrove forests of northeast Hainan Island are the most species diverse forests in China and consist of the Dongzhai National Nature Reserve and the Qinglan Provincial Nature Reserve. The former reserve is the first Chinese national nature reserve for mangroves and the latter has the most abundant mangrove species in China. However, to date the aboveground ground biomass (AGB) of this mangrove region has not been quantified due to the high species diversity and the difficulty of extensive field sampling in mangrove habitat. Although three-dimensional point clouds can capture the forest vertical structure, their application to large areas is hindered by the logistics, costs and data volumes involved. To fill the gap and address this issue, this study proposed a novel upscaling method for mangrove AGB estimation using field plots, UAV-LiDAR strip data and Sentinel-2 imagery (named G similar to LiDAR similar to S2 model) based on a point-line-polygon framework. In this model, the partial-coverage UAV-LiDAR data were used as a linear bridge to link ground measurements to the wall-to-wall coverage Sentinel-2 data. The results showed that northeast Hainan Island has a total mangrove AGB of 312,806.29 Mg with a mean AGB of 119.26 Mg ha(-1). The results also indicated that at the regional scale, the proposed UAV-LiDAR linear bridge method (i.e., G similar to LiDAR similar to S2 model) performed better than the traditional approach, which directly relates field plots to Sentinel-2 data (named the G similar to S2 model) (R-2 = 0.62 > 0.52, RMSE = 50.36 Mg ha(-1) < 56.63 Mg ha(-1)). Through a trend extrapolation method, this study inferred that the G similar to LiDAR similar to S2 model could decrease the number of field samples required by approximately 37% in comparison with those required by the G similar to 52 model in the study area. Regarding the UAV-LiDAR sampling intensity, compared with the original number of LiDAR plots, 20% of original linear bridges could produce an acceptable accuracy (R-2 = 0.62, RMSE = 51.03 Mg ha(-1)). Consequently, this study presents the first investigation of AGE for the mangrove forests on northeast Hainan Island in China and verifies the feasibility of using this mangrove AGB upscaling method for diverse mangrove forests. |
| 关键词 | Mangroves Aboveground biomass UAV-LiDAR Sentinel-2 Random forest |
| 学科领域 | Remote Sensing |
| DOI | 10.1016/j.jag.2019.101986 |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS关键词 | OBJECT-BASED APPROACH ; GROWING STOCK VOLUME ; AIRBORNE LIDAR ; ALLOMETRIC MODELS ; SPECTRAL INDEXES ; CANOPY COVER ; CARBON STOCK ; RED-EDGE ; HEIGHT ; LEAF |
| WOS研究方向 | Remote Sensing |
| WOS记录号 | WOS:000501621200004 |
| 出版者 | ELSEVIER |
| 文献子类 | Article |
| 出版地 | AMSTERDAM |
| EISSN | 1872-826X |
| 资助机构 | National Key Research & Development (R&D) Plan of China [2017YFB0503600] ; National Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41361090] ; China University of Geosciences (Wuhan) |
| 作者邮箱 | magicwan1105@163.com |
| 作品OA属性 | gold |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ibcas.ac.cn/handle/2S10CLM1/21964 |
| 专题 | 植被与环境变化国家重点实验室 |
| 作者单位 | 1.China Univ Geosci Wuhan, Fac Informat Engn, Lumo Rd 388, Wuhan 430074, Hubei, Peoples R China 2.Natl Engn Res Ctr Geog Informat Syst, Lumo Rd 388, Wuhan 430074, Hubei, Peoples R China 3.Nanjing Normal Univ, Key Lab Virtual Geog Environm, Minist Educ, Nanjing, Jiangsu, Peoples R China 4.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Jiangsu, Peoples R China 5.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China 6.Hainan Normal Univ, Coll Geog & Environm Sci, Longkun South St 99, Haikou 571158, Hainan, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Dezhi,Wan, Bo,Liu, Jing,et al. Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2020,85. |
| APA | Wang, Dezhi.,Wan, Bo.,Liu, Jing.,Su, Yanjun.,Guo, Qinghua.,...&Wu, Xincai.(2020).Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,85. |
| MLA | Wang, Dezhi,et al."Estimating aboveground biomass of the mangrove forests on northeast Hainan Island in China using an upscaling method from field plots, UAV-LiDAR data and Sentinel-2 imagery".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 85(2020). |
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