干旱区生态环境知识资源中心(Arid): Temporal Information Extraction for Afforestation in the Middle Section of the Yarlung Zangbo River Using Time-Series Landsat Images Based on Google Earth Engine

Arid

DOI	10.3390/rs13234785
	Temporal Information Extraction for Afforestation in the Middle Section of the Yarlung Zangbo River Using Time-Series Landsat Images Based on Google Earth Engine
	Fu, Hao; Zhao, Wei; Zhan, Qiqi; Yang, Mengjiao; Xiong, Donghong; Yu, Daijun
通讯作者	Zhao, W (corresponding author), Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China. ; Zhao, W (corresponding author), Chinese Acad Sci Tribhuvan Univ, Kathmandu Ctr Res & Educ, Beijing 100101, Peoples R China.
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2021
卷号	13 期号:23
英文摘要	Afforestation is one of the most efficient ways to control land desertification in the middle section of the Yarlung Zangbo River (YZR) valley. However, the lack of a quantitative way to record the planting time of artificial forest (AF) constrains further management for these forests. The long-term archived Landsat images (including the Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI)) provide a good opportunity to capture the temporal change information about AF plantations. Under the condition that there would be an abrupt increasing trend in the normalized difference vegetation index (NDVI) time-series curve after afforestation, and this characteristic can be thought of as the indicator of the AF planting time. To extract the indicator, an algorithm based on the Google Earth Engine (GEE) for detecting this trend change point (TCP) on the maximum NDVI time series within the growing season (May to September) was proposed. In this algorithm, the time-series NDVI was initially smoothed and segmented into two subspaces. Then, a trend change indicator S-diff was calculated with the difference between the fitting slopes of the subspaces before and after each target point. A self-adaptive method was applied to the NDVI series to find the right year with the maximum TCP, which is recorded as the AF planting time. Based on the proposed method, the AF planting time of the middle section of the YZR valley from 1988 to 2020 was derived. The detected afforestation temporal information was validated by 222 samples collected from the field survey, with a Pearson correlation coefficient of 0.93 and a root mean squared error (RMSE) of 2.95 years. Meanwhile, the area distribution of the AF planted each year has good temporal consistency with the implementation of the eco-reconstruction project. Overall, the study provides a good way to map AF planting times that is not only helpful for sustainable management of AF areas but also provides a basis for further research on the impact of afforestation on desertification control.
英文关键词	artificial forest planting time Google Earth Engine Landsat time series analysis
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000734729400001
WOS关键词	RANDOM FOREST ; SURFACE TEMPERATURE ; VEGETATION DYNAMICS ; SOUTH-AFRICA ; NDVI ; DESERTIFICATION ; REACHES ; REGION ; MODIS ; ALGORITHM
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/373938
作者单位	[Fu, Hao; Zhao, Wei; Zhan, Qiqi; Yang, Mengjiao; Xiong, Donghong] Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China; [Fu, Hao; Yu, Daijun] Chengdu Univ Technol, Coll Earth Sci, Chengdu 610059, Peoples R China; [Zhao, Wei; Xiong, Donghong] Chinese Acad Sci Tribhuvan Univ, Kathmandu Ctr Res & Educ, Beijing 100101, Peoples R China; [Zhan, Qiqi; Yang, Mengjiao] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Fu, Hao,Zhao, Wei,Zhan, Qiqi,et al. Temporal Information Extraction for Afforestation in the Middle Section of the Yarlung Zangbo River Using Time-Series Landsat Images Based on Google Earth Engine[J],2021,13(23).
APA	Fu, Hao,Zhao, Wei,Zhan, Qiqi,Yang, Mengjiao,Xiong, Donghong,&Yu, Daijun.(2021).Temporal Information Extraction for Afforestation in the Middle Section of the Yarlung Zangbo River Using Time-Series Landsat Images Based on Google Earth Engine.REMOTE SENSING,13(23).
MLA	Fu, Hao,et al."Temporal Information Extraction for Afforestation in the Middle Section of the Yarlung Zangbo River Using Time-Series Landsat Images Based on Google Earth Engine".REMOTE SENSING 13.23(2021).