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Research on Desertification Monitoring and Vegetation Refinement Extraction Methods Based on the Synergy of Multisource Remote Sensing Imagery

文献类型：期刊论文

作者Song, Zhenqi6; Lu, Yuefeng3,4,5,6; Yuan, Jinhui6; Lu, Miao1,2; Qin, Yong6; Sun, Dengkuo6; Ding, Ziqi6
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
出版日期2025
卷号63页码:4404819
关键词Desertification difference index (DDI) hue-saturation-lightness greenway enhanced vegetation index (HSLGEVI) multisource remote sensing collaborative monitoring normalized difference vegetation index (NDVI)- albedo feature space normalized difference vegetation index (NDVI)- albedo feature space vegetation refinement extraction vegetation refinement extraction vegetation refinement extraction
ISSN号0196-2892
DOI10.1109/TGRS.2025.3542800
产权排序3
文献子类Article
英文摘要Due to over-exploitation by humans and global climate change, desertification has become an increasingly severe issue, seriously threatening the stability of ecosystems and the sustainable development of resources. Therefore, this study focuses on the Hangjin Banner region in Inner Mongolia, using satellite remote sensing and remote aerial vehicles (RAV) remote sensing technology. Through wide-area coverage, long-term monitoring, multiscale analysis, and high-precision interpretation, the study demonstrates the strong synergistic effects of multiscale interpretation and data fusion applications, systematically carrying out desertification monitoring grading and refined vegetation extraction. First, to address the problem that the information dimension of a single index is insufficient and it is difficult to reflect the development trend of desertification, the normalized difference vegetation index (NDVI)-albedo feature space applicable to the desert environment is inversely performed based on Landsat 8 satellite images from 2009 to 2023. Then, on the basis of the feature space, the desertification difference index (DDI), which realizes the wide-area desertification monitoring grading and spatio-temporal evolution analysis of the study area, and the hue-saturation-lightness greenway enhanced vegetation index (HSLGEVI), which has stronger applicability and stability in desert environments, were constructed based on the HSL color space and the hue tuning algorithm. This index can effectively overcome the limitations of the RGB vegetation index, clearly delineate the canopy edge of desert vegetation, and accurately extract surface meadow vegetation with lower chlorophyll content. To test the effectiveness of the HSLGEVI, the widely used and validated excess green index (EXG), vegetation difference vegetation index (VDVI), modified green-red vegetation index (MGRVI), and red-green-blue vegetation index (RGBVI) were selected for comparison. The results show that the accuracy of HSLGEVI is better than that of other indices, with overall accuracy and ${F}1$ -score remaining above 90%. It reduces the impact of the RGB color space vegetation index on the accuracy of vegetation extraction, effectively overcoming misclassification and omission issues, and providing a reliable monitoring mechanism for desertification control in the Hangjin Banner area.
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WOS关键词COVER CLASSIFICATION ; REFLECTANCE SPECTRA ; LAND DEGRADATION ; RANDOM FOREST ; INTEGRATION ; ACCURACY ; ALBEDO ; FIELD ; AREA ; US
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001439569700024
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://ir.igsnrr.ac.cn/handle/311030/213353]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Lu, Yuefeng; Lu, Miao
作者单位1.Natl Ctr Technol Innovat Comprehens Utilizat Salin, Dongying 257300, Peoples R China
2.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Aridand Semiarid, Beijing 100081, Peoples R China;
3.Chinese Acad Sci, Nat Resources Res, Beijing 100101, Peoples R China;
4.Inst Geog Sci & Nat Resources Res, Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China;
5.Natl Ctr Technol Innovat Comprehens Utilizat Salin, Dongying 257300, Peoples R China;
6.Shandong Univ Technol, Sch Civil Engn & Geomat, Zibo 255049, Peoples R China;
推荐引用方式
GB/T 7714		 Song, Zhenqi,Lu, Yuefeng,Yuan, Jinhui,et al. Research on Desertification Monitoring and Vegetation Refinement Extraction Methods Based on the Synergy of Multisource Remote Sensing Imagery[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2025,63:4404819.
APA Song, Zhenqi.,Lu, Yuefeng.,Yuan, Jinhui.,Lu, Miao.,Qin, Yong.,...&Ding, Ziqi.(2025).Research on Desertification Monitoring and Vegetation Refinement Extraction Methods Based on the Synergy of Multisource Remote Sensing Imagery.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,63,4404819.
MLA Song, Zhenqi,et al."Research on Desertification Monitoring and Vegetation Refinement Extraction Methods Based on the Synergy of Multisource Remote Sensing Imagery".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 63(2025):4404819.

入库方式： OAI收割

来源：地理科学与资源研究所

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