A full time series imagery and full cycle monitoring (FTSI-FCM) algorithm for tracking rubber plantation dynamics in the Vietnam from 1986 to 2022

IF 10.6 1区 地球科学 Q1 GEOGRAPHY, PHYSICAL ISPRS Journal of Photogrammetry and Remote Sensing Pub Date : 2024-12-30 DOI:10.1016/j.isprsjprs.2024.12.018
Bangqian Chen, Jinwei Dong, Tran Thi Thu Hien, Tin Yun, Weili Kou, Zhixiang Wu, Chuan Yang, Guizhen Wang, Hongyan Lai, Ruijin Liu, Feng An
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引用次数: 0

Abstract

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 FTSI-FCM algorithm yielded highly reliable maps of rubber distribution (Overall Accuracy, OA = 93.75%, F1-score = 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°N latitude, below 600 m in elevation, on slopes under 15°, 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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来源期刊
ISPRS Journal of Photogrammetry and Remote Sensing
ISPRS Journal of Photogrammetry and Remote Sensing 工程技术-成像科学与照相技术
CiteScore
21.00
自引率
6.30%
发文量
273
审稿时长
40 days
期刊介绍: The ISPRS Journal of Photogrammetry and Remote Sensing (P&RS) serves as the official journal of the International Society for Photogrammetry and Remote Sensing (ISPRS). It acts as a platform for scientists and professionals worldwide who are involved in various disciplines that utilize photogrammetry, remote sensing, spatial information systems, computer vision, and related fields. The journal aims to facilitate communication and dissemination of advancements in these disciplines, while also acting as a comprehensive source of reference and archive. P&RS endeavors to publish high-quality, peer-reviewed research papers that are preferably original and have not been published before. These papers can cover scientific/research, technological development, or application/practical aspects. Additionally, the journal welcomes papers that are based on presentations from ISPRS meetings, as long as they are considered significant contributions to the aforementioned fields. In particular, P&RS encourages the submission of papers that are of broad scientific interest, showcase innovative applications (especially in emerging fields), have an interdisciplinary focus, discuss topics that have received limited attention in P&RS or related journals, or explore new directions in scientific or professional realms. It is preferred that theoretical papers include practical applications, while papers focusing on systems and applications should include a theoretical background.
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