{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:17:58Z","timestamp":1760149078646,"version":"build-2065373602"},"reference-count":82,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2023,7,7]],"date-time":"2023-07-07T00:00:00Z","timestamp":1688688000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hainan Province Science and Technology Special Found","award":["ZDYF2021SHFZ257","422CXTD527","2019RC329","42071418","CARS-33","202210298044Z"],"award-info":[{"award-number":["ZDYF2021SHFZ257","422CXTD527","2019RC329","42071418","CARS-33","202210298044Z"]}]},{"name":"Natural Science Foundation","award":["ZDYF2021SHFZ257","422CXTD527","2019RC329","42071418","CARS-33","202210298044Z"],"award-info":[{"award-number":["ZDYF2021SHFZ257","422CXTD527","2019RC329","42071418","CARS-33","202210298044Z"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["ZDYF2021SHFZ257","422CXTD527","2019RC329","42071418","CARS-33","202210298044Z"],"award-info":[{"award-number":["ZDYF2021SHFZ257","422CXTD527","2019RC329","42071418","CARS-33","202210298044Z"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010038","name":"Earmarked Fund for China Agriculture Research System","doi-asserted-by":"publisher","award":["ZDYF2021SHFZ257","422CXTD527","2019RC329","42071418","CARS-33","202210298044Z"],"award-info":[{"award-number":["ZDYF2021SHFZ257","422CXTD527","2019RC329","42071418","CARS-33","202210298044Z"]}],"id":[{"id":"10.13039\/501100010038","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Innovation and Entrepreneurship Training Project for Undergraduates in Jiangsu Province","award":["ZDYF2021SHFZ257","422CXTD527","2019RC329","42071418","CARS-33","202210298044Z"],"award-info":[{"award-number":["ZDYF2021SHFZ257","422CXTD527","2019RC329","42071418","CARS-33","202210298044Z"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rubber (Hevea brasiliensis Muell.) plantations are among the most critical agricultural ecosystems in tropical regions, playing a vital role in regional carbon balance. Accurate large-scale biomass estimation for these plantations remains a challenging task due to the severe signal saturation problem. Recent advances in remote sensing big data, cloud platforms, and machine learning have facilitated the precise acquisition of key physiological variables, such as stand age (A) and canopy height (H), which are critical parameters for biomass estimation but have been underutilized in prior studies. Using Hainan Island\u2014the second-largest rubber planting base in China\u2014as a case study, we integrated extensive ground surveys, maps of stand age and canopy height, remote sensing indicators (RSIs), and geographical and climate indicators (ECIs) to ascertain the optimal method for estimating rubber plantation biomass. We compared different inputs and estimation approaches (direct and indirect) using the random forest algorithm and analyzed the spatiotemporal characteristics of rubber plantation biomass on Hainan Island. The results indicated that the traditional model (RSIs + ECIs) had low accuracy and significant estimation bias (R2 = 0.24, RMSE = 38.36 mg\/ha). The addition of either stand age or canopy height considerably enhance model accuracy (R2 = 0.77, RMSE \u2248 21.12 mg\/ha). Moreover, incorporating the DBH obtained through indirect inversion yielded even greater predictive accuracy (R2 = 0.97, RMSE = 7.73 mg\/ha), outperforming estimates derived from an allometric equation model input with the DBH (R2 = 0.67, RMSE = 25.43 mg\/ha). However, augmenting the model with stand age, canopy height, or their combination based on RSIs, ECIs, and DBH only marginally improved the accuracy. Consequently, it is not recommended in scenarios with limited data and computing resources. Employing the optimal model, we generated biomass maps of rubber plantations on Hainan Island for 2016 and 2020, revealing that the spatiotemporal distribution pattern of the biomass is closely associated with the establishment year of the rubber plantations. While average biomass in a few areas has undergone slight decreases, total biomass has exhibited significant growth, reaching 5.46 \u00d7 107 mg by the end of 2020, underscoring its considerable value as a carbon sink.<\/jats:p>","DOI":"10.3390\/rs15133447","type":"journal-article","created":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T00:47:35Z","timestamp":1688950055000},"page":"3447","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Comparison of Different Important Predictors and Models for Estimating Large-Scale Biomass of Rubber Plantations in Hainan Island, China"],"prefix":"10.3390","volume":"15","author":[{"given":"Xin","family":"Li","sequence":"first","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Xincheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"},{"name":"Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS), Hainan Danzhou Agro-Ecosystem National Observation and Research Station, State Key Laboratory Incubation Base for Cultivation & Physiology of Tropical Crops, Haikou 571101, China"}]},{"given":"Yuanfeng","family":"Gao","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"},{"name":"Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS), Hainan Danzhou Agro-Ecosystem National Observation and Research Station, State Key Laboratory Incubation Base for Cultivation & Physiology of Tropical Crops, Haikou 571101, China"}]},{"given":"Jiuhao","family":"Wu","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Renxi","family":"Cheng","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Donghao","family":"Ren","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Qing","family":"Bao","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4294-8337","authenticated-orcid":false,"given":"Ting","family":"Yun","sequence":"additional","affiliation":[{"name":"Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7344-8717","authenticated-orcid":false,"given":"Zhixiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS), Hainan Danzhou Agro-Ecosystem National Observation and Research Station, State Key Laboratory Incubation Base for Cultivation & Physiology of Tropical Crops, Haikou 571101, China"}]},{"given":"Guishui","family":"Xie","sequence":"additional","affiliation":[{"name":"Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS), Hainan Danzhou Agro-Ecosystem National Observation and Research Station, State Key Laboratory Incubation Base for Cultivation & Physiology of Tropical Crops, Haikou 571101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0209-4285","authenticated-orcid":false,"given":"Bangqian","family":"Chen","sequence":"additional","affiliation":[{"name":"Rubber Research Institute (RRI), Chinese Academy of Tropical Agricultural Sciences (CATAS), Hainan Danzhou Agro-Ecosystem National Observation and Research Station, State Key Laboratory Incubation Base for Cultivation & Physiology of Tropical Crops, Haikou 571101, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"112307","DOI":"10.1016\/j.rse.2021.112307","article-title":"Individual tree crown segmentation from airborne LiDAR data using a novel Gaussian filter and energy function minimization-based approach","volume":"256","author":"Yun","year":"2021","journal-title":"Remote Sens. 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