文献类型： 外文期刊

第一作者： Chen, Bangqian

作者： Chen, Bangqian;Wu, Zhixiang;Yang, Chuan;Wang, Guizhen;Lai, Hongyan;Liu, Ruijin;An, Feng;Dong, Jinwei;Hien, Tran Thi Thu;Yun, Tin;Kou, Weili

作者机构：

关键词： Rubber plantations; Landsat/Sentinel-2; Phenological features; Establishment year; Vietnam

期刊名称：ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING （ 影响因子：12.2； 五年影响因子：13.7 ）

ISSN： 0924-2716

年卷期： 2025 年 220 卷

页码：

收录情况： SCI

摘要： Accurate mapping of rubber plantations in Southeast Asia is critical for sustainable plantation management and ecological and environmental impact assessment. Despite extensive research on rubber plantation mapping, studies have largely been confined to provincial scales, with the few country-scale assessments showing significant disagreement in both spatial distribution and area estimates. These discrepancies primarily stem from persistent cloud cover in tropical regions and limited temporal resolution of datasets that inadequately capture the full phenological cycles of rubber trees. To address these issues, we propose the Full Time Series Satellite Imagery and Full-Cycle Monitoring (FTSI-FCM) algorithm for mapping spatial distribution and establishment year of rubber plantations in Vietnam, a country experienced significant rubber expansion over the past decades. The FTSI-FCM algorithm initially employs the LandTrendr approach-an established forest disturbance detection algorithm-to identify the land use changes during the plantation establishment phase. We enhance this process through a spatiotemporal correction scheme to accurately determine the establishment years and maturity phases of the plantations. Subsequently, the algorithm identifies rubber plantations through a random forest algorithm by integrating features from three temporal phases: canopy transitions from rubber seedlings to mature plantations, phenological changes during mature stages, and phenological-spectral characteristic during the mapping year. This approach leverages an extensive time series of Landsat images dating back to the late 1980s, complemented by Sentinel-2 images since 2015. For the mapping year, these data are further enhanced by the inclusion of PALSAR-2 L-band Synthetic-Aperture Radar (SAR) and very high-resolution Planet optical imagery. When applied in Vietnam-a leading rubber producer with complex cultivation conditions- the FTSIFCM algorithm yielded highly reliable maps of rubber distribution (Overall Accuracy, OA = 93.75%, F1score = 0.93) and establishment years (R2 = 0.99, RMSE = 0.25 years) for 2022 (referred to as FTSI-FCM_2022). These results outperformed previous mappings, such as WangR_2021 (OA = 75.00%, F1-score = 0.71), in both spatial distribution and area estimates. The FTSI-FCM_2022 map revealed a total rubber plantation area of 754,482 ha, closely matching reported statistics of 727,900 ha and showing strong correlation provincial statistics (R2 = 0.99). Spatial analysis indicated that over 90% of rubber plantations are located within 15 degrees N latitude, below 600 m in elevation, on slopes under 15 degrees, and were established after 2000. Notably, there has been no significant expansion of rubber plantations into higher elevations or steeper slopes since 1990s, suggesting the effectiveness of sustainable rubber cultivation management practices in Vietnam. The FTSI-FCM algorithm demonstrates substantial potential for mapping rubber plantations in major producing areas such as Southeast Asia, thereby supporting sustainable development decision-making in the natural rubber industry.

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