Title | Automatic alpine treeline extraction using high-resolution forest cover imagery 利用高分辨率森林覆盖影像实现高山林线的自动提取 |
Author | |
Corresponding Author | Zeng,Zhenzhong |
Publication Years | 2022-03-25
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DOI | |
Source Title | |
ISSN | 1007-4619
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Volume | 26Issue:3Pages:456-467 |
Abstract | Alpine treeline is not only an important source in calibrating global climate change but also a fundamental element in scientifically managing forest resources. Furthermore, the location, area size, and change patterns of forest lines are also used as essential information in monitoring and modeling the environment. The alpine forest line of the Qinling Mountains is located in the ecological staggered zone at high altitude, with an obvious distribution of altitudinal spectrum, which is an important north-south geographical dividing line in China. Therefore, a novel approach for the rapid and accurate identification of alpine treeline in the Qinling Mountains must be developed.We propose a remote-sensor-based algorithm for extracting alpine treelines in the Qinling Mountains by combining the high-resolution global forest cover data in 2000 with a digital elevation model and mountain distribution data. Specifically, tree cover is first extracted from the forest cover data. Next, the highest point of the study area is determined from the elevation data. Finally, the 8-connected domain search algorithm is employed to find the boundary between forest and non-forest covers to determine the alpine treeline. The algorithm is validated by high-resolution Google Earth images, GPS ground-based data, and the NDVI dataset. Further, we systematically investigate the relationship between the alpine treeline distribution and geographical factors (elevation, slope, and aspect) in the study area using the elevation data.The distribution of treelines in this paper is consistent with the actual treelines distribution in Google Earth images, further demonstrating the performance of the proposed algorithm. The elevation of treelines in the Qinling Mountains ranges from 2400 m to 3800 m. The treelines are concentrated in steep slope areas ranging from 15° to 55°. The distribution of alpine treeline elevation shows significant slope differences, with the treeline on the south slope being higher than those on the north slope, and the treelines on the east slope being higher than those on the west slope.The treelines obtained by our algorithm match the actual treelines in the Google Earth images of the study area well, showing an outstanding performance in the integrity and boundary connectivity of treelines. Given the capability of remote sensing technology to observe the Earth in a large scale and the high data quality and accessibility of satellite image data, the proposed algorithm for extracting alpine treelines can be further applied to global treeline mapping to provide technical support for global mountain ecosystem monitoring, conservation, and restoration. |
Keywords | |
URL | [Source Record] |
Indexed By | |
Language | Chinese
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SUSTech Authorship | First
; Corresponding
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Funding Project | National Natural Science Foundation of China[42071022];
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EI Accession Number | 20223412601491
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EI Keywords | Climate change
; Data mining
; Forestry
; Geographical distribution
; Global positioning system
; Landforms
; Search engines
; Surveying
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ESI Classification Code | Surveying:405.3
; Atmospheric Properties:443.1
; Geology:481.1
; Computer Software, Data Handling and Applications:723
; Data Processing and Image Processing:723.2
; Agricultural Equipment and Methods; Vegetation and Pest Control:821
; Engineering Graphics:902.1
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Scopus EID | 2-s2.0-85135772335
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Data Source | Scopus
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Citation statistics |
Cited Times [WOS]:0
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Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/382625 |
Department | School of Environmental Science and Engineering |
Affiliation | 1.School of Environmental Science and Engineering,South University of Science and Technology,Shenzhen,518055,China 2.School of Earth and Environment,University of Leeds,Leeds,LS29JT,United Kingdom |
First Author Affilication | School of Environmental Science and Engineering |
Corresponding Author Affilication | School of Environmental Science and Engineering |
First Author's First Affilication | School of Environmental Science and Engineering |
Recommended Citation GB/T 7714 |
Jiang,Xin,He,Xinyue,Wang,Dashan,等. Automatic alpine treeline extraction using high-resolution forest cover imagery 利用高分辨率森林覆盖影像实现高山林线的自动提取[J]. 遥感学报,2022,26(3):456-467.
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APA |
Jiang,Xin,He,Xinyue,Wang,Dashan,Zou,Junyu,&Zeng,Zhenzhong.(2022).Automatic alpine treeline extraction using high-resolution forest cover imagery 利用高分辨率森林覆盖影像实现高山林线的自动提取.遥感学报,26(3),456-467.
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MLA |
Jiang,Xin,et al."Automatic alpine treeline extraction using high-resolution forest cover imagery 利用高分辨率森林覆盖影像实现高山林线的自动提取".遥感学报 26.3(2022):456-467.
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