Early identification of immature rubber plantations using Landsat and Sentinel satellite images
文献类型：期刊论文
| 作者 | Wang, Xincheng4,5; Chen, Bangqian4; Dong, Jinwei3; Gao, Yuanfeng4,5; Wang, Guizhen4; Lai, Hongyan4; Wu, Zhixiang4; Yang, Chuan4; Kou, Weili1,2; Yun, Ting5 |
| 刊名 | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
 |
| 出版日期 | 2024-09-01 |
| 卷号 | 133页码:13 |
| 关键词 | Immature rubber plantations Early identification Random forest Google Earth Engine |
| ISSN号 | 1569-8432 |
| DOI | 10.1016/j.jag.2024.104097 |
| 产权排序 | 3 |
| 英文摘要 | Early identification of rubber plantations holds significant importance for both optimal plantation management and scientific studies. Even though remote sensing techniques for mapping rubber plantations have evolved considerably since the 2000s, current methods are highly effective in detecting mature rubber plantations (MRPs), which have distinctive forest characteristics, but often fail to identify immature rubber plantations (IRPs) in a timely manner. This leads to an estimated lag of at least five years in the resulting rubber plantation maps. This paper presents a novel algorithm aimed at promptly pinpointing IRPs in the early planting stage by harnessing a composite of multi-source time series satellite imagery on Google Earth Engine (GEE) platform. Twelve scenarios with different time intervals (3 months, 6 months, and 12 months) and datasets (Landsat 8, Sentinel-2, and Sentinel-1) were tested to determine the most efficient strategy for identifying IRPs using a random forest algorithm. The results demonstrate that the data cube constructed from Landsat 8, Sentinel-2, and Sentinel-1 with 3-month time intervals yields the most accurate identification accuracy. Specifically, it achieves a remarkable overall accuracy of 0.78, 0.87, and 0.93 for plantations established during the second, third, and fourth years, respectively. When implemented on Hainan Island, China's second-largest natural rubber producing base, the algorithm unveiled a significant decline trend in rubber plantation areas since 2015. Additionally, the spatial distribution exhibited pronounced heterogeneity: while the western and northern regions saw dense immature plantation clusters, the eastern coastal regions hosted only sparse plantations. These up-to-date maps of IRPs are valuable in predicting rubber production, enhancing the monitoring and management practices, and promoting the sustainable development of natural rubber industry. |
| WOS关键词 | TIME-SERIES DATA ; MAPPING TROPICAL FORESTS ; HAINAN ISLAND ; INTEGRATING PALSAR ; NATURAL-RUBBER ; EXPANSION ; XISHUANGBANNA ; VEGETATION ; DYNAMICS ; CHINA |
| 资助项目 | Natural Science Foundation of Hainan Province[422CXTD527] ; National Natural Science Foundation of China[42071418] ; National Natural Science Foundation of China[32371876] ; Central Public-interest Scientific Institution Basal Research Fund[1630022023007] ; Earmarked Fund for China Agriculture Research System[CARS-33] |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:001297897000001 |
| 出版者 | ELSEVIER |
| 资助机构 | Natural Science Foundation of Hainan Province ; National Natural Science Foundation of China ; Central Public-interest Scientific Institution Basal Research Fund ; Earmarked Fund for China Agriculture Research System |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/208771]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Chen, Bangqian; Yun, Ting |
| 作者单位 | 1.Southwest Forestry Univ, Coll Forestry, Kunming 650233, Peoples R China 2.Southwest Forestry Univ, Coll Big Data & Intelligence Engn, Kunming 650224, Peoples R China 3.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 4.Chinese Acad Trop Agr Sci CATAS, Rubber Res Inst RRI, State Key Lab Incubat Base Cultivat & Physiol Trop, Hainan Danzhou Agroecosyst Natl Observat & Res Stn, Haikou 571101, Peoples R China 5.Nanjing Forestry Univ, Coinnovat Ctr Sustainable Forestry Southern China, Nanjing 210037, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Xincheng,Chen, Bangqian,Dong, Jinwei,et al. Early identification of immature rubber plantations using Landsat and Sentinel satellite images[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2024,133:13. |
| APA | Wang, Xincheng.,Chen, Bangqian.,Dong, Jinwei.,Gao, Yuanfeng.,Wang, Guizhen.,...&Yun, Ting.(2024).Early identification of immature rubber plantations using Landsat and Sentinel satellite images.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,133,13. |
| MLA | Wang, Xincheng,et al."Early identification of immature rubber plantations using Landsat and Sentinel satellite images".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 133(2024):13. |
入库方式： OAI收割
来源：地理科学与资源研究所
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