IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | |
Monitoring Spatial and Temporal Patterns of Rubber Plantation Dynamics Using Time-Series Landsat Images and Google Earth Engine | |
Jun Zhang1  Yuchen Li1  Ping Zhang1  Yufei Xue1  Chenli Liu2  | |
[1] School of Earth Sciences, Yunnan University, Kunming, China;State Key Laboratory of Grassland Agro-Ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, China; | |
关键词: Google Earth Engine (GEE); phenology; random forest (RF); rubber plantation; Xishuangbanna; | |
DOI : 10.1109/JSTARS.2021.3110763 | |
来源: DOAJ |
【 摘 要 】
Rubber plantation is an important strategic material related to the national economy and people's livelihoods. Up-to-date and accurate rubber plantation maps are critical for monitoring the area and spatial distribution of rubber plantations and assessing their impacts on society, the economy, and the environment. However, existing optical images are greatly limited by frequent cloud cover, which seriously affects the accuracy of rubber plantation area extraction. To overcome this issue, we used dense Landsat time series stacks based on Google Earth Engine, combined phenological features, and applied random forest algorithms to monitor rubber plantations in Xishuangbanna from 1987 to 2020. The results showed that
【 授权许可】
Unknown