Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.3390/f12020147 |
Using Sentinel-2 Images to Map the Populus euphratica Distribution Based on the Spectral Difference Acquired at the Key Phenological Stage | |
Li, Hao; Shi, Qingdong; Wan, Yanbo; Shi, Haobo; Imin, Bilal | |
通讯作者 | Shi, QD (corresponding author), Xinjiang Univ, Coll Resources & Environm Sci, Urumqi 830046, Peoples R China. ; Shi, QD (corresponding author), Xinjiang Univ, Inst Arid Ecol & Environm, Urumqi 830046, Peoples R China. ; Shi, QD (corresponding author), Xinjiang Univ, Key Lab Oasis Ecol, Urumqi 830046, Peoples R China. |
来源期刊 | FORESTS
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EISSN | 1999-4907 |
出版年 | 2021 |
卷号 | 12期号:2 |
英文摘要 | Populus euphratica is an important tree species in desert ecosystems. The protection and restoration of natural Populus euphratica forests requires accurate positioning information. The use of Sentinel-2 images to map the Populus euphratica distribution at a large scale faces challenges associated with discriminating between Populus euphratica and Tamarix chinensis. To address this problem, this study selected the Daliyabuyi Oasis in the hinterland of the Taklimakan Desert as the study site and sought to distinguish Populus euphratica from Tamarix chinensis. First, we determined the peak spectral difference period (optimal time window) between Populus euphratica and Tamarix chinensis within monthly Sentinel-2 time-series images. Then, an appropriate vegetation index was selected to represent the spectral difference between Populus euphratica and Tamarix chinensis within the key phenological stage. Finally, the maximum entropy method was used to automatically determine the threshold to map the Populus euphratica distribution. The results indicated that the period from 22 April to 1 May was the optimal time window for mapping the Populus euphratica distribution in the Daliyabuyi Oasis. The combination of the inverted red-edge chlorophyll index (IRECI) and the maximum entropy method can effectively distinguish Populus euphratica from Tamarix chinensis. The user's accuracy of the Populus euphratica distribution extraction from single-data Sentinel-2 images acquired within the optimal time window was 0.83, the producer's accuracy was 0.72, and the F1-score was 0.77. This study verified the feasibility of mapping Populus euphratica distribution based on Sentinel-2 images, and analyzed the validity of exploiting spectral differences within the key phenological stage from a single-data image to distinguish between the two species. The results can be used to extract the distribution of Populus euphratica and serve as an auxiliary variable for other plant classification methods, providing a reference for the extraction and classification of desert plants. |
英文关键词 | remote sensing desert plant tree species time window vegetation index |
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:000622528800001 |
WOS类目 | Forestry |
WOS研究方向 | Forestry |
来源机构 | 新疆大学 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/350243 |
作者单位 | [Li, Hao; Shi, Qingdong; Wan, Yanbo; Shi, Haobo; Imin, Bilal] Xinjiang Univ, Coll Resources & Environm Sci, Urumqi 830046, Peoples R China; [Li, Hao; Shi, Qingdong; Wan, Yanbo; Shi, Haobo; Imin, Bilal] Xinjiang Univ, Inst Arid Ecol & Environm, Urumqi 830046, Peoples R China; [Li, Hao; Shi, Qingdong; Wan, Yanbo; Shi, Haobo; Imin, Bilal] Xinjiang Univ, Key Lab Oasis Ecol, Urumqi 830046, Peoples R China |
推荐引用方式 GB/T 7714 | Li, Hao,Shi, Qingdong,Wan, Yanbo,et al. Using Sentinel-2 Images to Map the Populus euphratica Distribution Based on the Spectral Difference Acquired at the Key Phenological Stage[J]. 新疆大学,2021,12(2). |
APA | Li, Hao,Shi, Qingdong,Wan, Yanbo,Shi, Haobo,&Imin, Bilal.(2021).Using Sentinel-2 Images to Map the Populus euphratica Distribution Based on the Spectral Difference Acquired at the Key Phenological Stage.FORESTS,12(2). |
MLA | Li, Hao,et al."Using Sentinel-2 Images to Map the Populus euphratica Distribution Based on the Spectral Difference Acquired at the Key Phenological Stage".FORESTS 12.2(2021). |
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