全时间序列图像和全周期监测(FTSI-FCM)算法用于跟踪1986年至2022年越南橡胶种植园的动态

IF 10.6 1区 地球科学 Q1 GEOGRAPHY, PHYSICAL
Bangqian Chen, Jinwei Dong, Tran Thi Thu Hien, Tin Yun, Weili Kou, Zhixiang Wu, Chuan Yang, Guizhen Wang, Hongyan Lai, Ruijin Liu, Feng An
{"title":"全时间序列图像和全周期监测(FTSI-FCM)算法用于跟踪1986年至2022年越南橡胶种植园的动态","authors":"Bangqian Chen, Jinwei Dong, Tran Thi Thu Hien, Tin Yun, Weili Kou, Zhixiang Wu, Chuan Yang, Guizhen Wang, Hongyan Lai, Ruijin Liu, Feng An","doi":"10.1016/j.isprsjprs.2024.12.018","DOIUrl":null,"url":null,"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 (R<ce:sup loc=\"post\">2</ce:sup> = 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 (R<ce:sup loc=\"post\">2</ce:sup> = 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.","PeriodicalId":50269,"journal":{"name":"ISPRS Journal of Photogrammetry and Remote Sensing","volume":"27 8 1","pages":""},"PeriodicalIF":10.6000,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A full time series imagery and full cycle monitoring (FTSI-FCM) algorithm for tracking rubber plantation dynamics in the Vietnam from 1986 to 2022\",\"authors\":\"Bangqian Chen, Jinwei Dong, Tran Thi Thu Hien, Tin Yun, Weili Kou, Zhixiang Wu, Chuan Yang, Guizhen Wang, Hongyan Lai, Ruijin Liu, Feng An\",\"doi\":\"10.1016/j.isprsjprs.2024.12.018\",\"DOIUrl\":null,\"url\":null,\"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 (R<ce:sup loc=\\\"post\\\">2</ce:sup> = 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 (R<ce:sup loc=\\\"post\\\">2</ce:sup> = 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.\",\"PeriodicalId\":50269,\"journal\":{\"name\":\"ISPRS Journal of Photogrammetry and Remote Sensing\",\"volume\":\"27 8 1\",\"pages\":\"\"},\"PeriodicalIF\":10.6000,\"publicationDate\":\"2024-12-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISPRS Journal of Photogrammetry and Remote Sensing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1016/j.isprsjprs.2024.12.018\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISPRS Journal of Photogrammetry and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1016/j.isprsjprs.2024.12.018","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
引用次数: 0

摘要

准确绘制东南亚橡胶种植园地图对可持续种植园管理和生态环境影响评价至关重要。尽管对橡胶种植园测绘进行了广泛的研究,但研究主要局限于省级尺度,少数国家尺度的评估显示在空间分布和面积估计方面存在重大分歧。这些差异主要源于热带地区持续的云层覆盖以及数据集的有限时间分辨率,无法充分捕捉橡胶树的完整物候周期。为了解决这些问题,我们提出了全时间序列卫星图像和全周期监测(FTSI-FCM)算法来绘制越南橡胶种植园的空间分布和建立年份,越南在过去几十年中经历了显著的橡胶扩张。FTSI-FCM算法最初采用LandTrendr方法(一种已建立的森林干扰检测算法)来识别人工林建立阶段的土地利用变化。我们通过一个时空校正方案来增强这一过程,以准确地确定人工林的建立年份和成熟期。随后,该算法通过随机森林算法,综合三个时间阶段的特征,即橡胶幼苗到成熟人工林的冠层转变、成熟阶段的物候变化和制图年的物候光谱特征,识别橡胶人工林。该方法利用了可追溯到20世纪80年代末的大量Landsat图像时间序列,并辅以2015年以来的Sentinel-2图像。在测绘年,这些数据因包括PALSAR-2 l波段合成孔径雷达(SAR)和非常高分辨率的行星光学图像而进一步增强。当在越南(一个主要的橡胶生产国,具有复杂的种植条件)应用时,FTSI-FCM算法产生了高度可靠的橡胶分布图(总体精度,OA = 93.75%, f1得分= 0.93)和2022年(称为FTSI-FCM_2022)的建立年份(R2 = 0.99, RMSE = 0.25年)。这些结果在空间分布和面积估计上都优于先前的映射,如wanggr_2021 (OA = 75.00%, F1-score = 0.71)。FTSI-FCM_2022地图显示,橡胶种植总面积为754,482 ha,与报告统计数据727,900 ha非常吻合,省级统计数据具有很强的相关性(R2 = 0.99)。空间分析表明,90%以上的橡胶林分布在北纬15°、海拔600 m以下、坡度15°以下,且建立于2000年以后。值得注意的是,自20世纪90年代以来,橡胶种植园没有向更高海拔或更陡峭的斜坡上扩张,这表明越南可持续橡胶种植管理措施的有效性。FTSI-FCM算法显示了在东南亚等主要生产地区绘制橡胶种植园地图的巨大潜力,从而支持天然橡胶工业的可持续发展决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A full time series imagery and full cycle monitoring (FTSI-FCM) algorithm for tracking rubber plantation dynamics in the Vietnam from 1986 to 2022
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信