A New Remote Sensing Desert Vegetation Detection Index
文献类型：期刊论文
| 作者 | Song, Zhenqi; Lu, Yuefeng4,5; Ding, Ziqi; Sun, Dengkuo; Jia, Yuanxin3; Sun, Weiwei2 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-12-01 |
| 卷号 | 15期号:24页码:5742 |
| 关键词 | HSV color space channel enhancement UAV visible imagery desert vegetation extraction land desertification monitoring HSVGVI |
| DOI | 10.3390/rs15245742 |
| 文献子类 | Article |
| 英文摘要 | Land desertification is a key environmental problem in China, especially in Northwest China, where it seriously affects the sustainable development of natural resources. In this paper, we combine high-resolution satellite remote sensing images and UAV (unmanned aerial vehicle) visible light images to extract desert vegetation data and quickly locate and accurately monitor land desertification in relevant areas according to changes in vegetation coverage. Due to the strong light and dry climate of deserts in Northwest China, which results in deeper vegetation shadow texture and mostly dry shrubs with fewer stems and leaves, the accuracy of the vegetation index commonly used in visible remote sensing image classification is not able to meet the requirements for monitoring and evaluating land desertification. For this reason, in this paper, we took the Hangjin Banner in Bayannur as an example and constructed a new vegetation index, the HSVGVI (hue-saturation-value green enhancement vegetation index), based on the HSV (hue-saturation-value) color space using channel enhancement that can improve the extraction accuracy of desert vegetation and reduce misclassification. In addition, in order to further test the extraction accuracy, samples of densely vegetated and multi-shaded areas were divided in the study area according to the accuracy-influencing factors. At the same time, the HSVGVI was compared with the vegetation indices EXG (excess green index), RGBVI (red-green-blue vegetation index), MGRVI (modified green-red vegetation index), NGBDI (normalized green-red discrepancy index), and VDVI (visible-band discrepancy vegetation index) constructed based on the RGB (red-green-blue) color space. The experimental results show that the extraction accuracy of the EXG and other vegetation indices constructed in RGB color space can only reach 70%, while the extraction accuracy of the HSVGVI can reach more than 95%. In summary, the HSVGVI proposed in this paper can better realize the extraction of desert vegetation data and can provide a reliable technical tool for monitoring and evaluating land desertification. |
| WOS关键词 | CLASSIFICATION |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:001130956800001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/201581]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Shandong Zhengyuan Digital City Construct Co Ltd, Yantai 264670, Peoples R China 2.Natl Forestry & Grassland Adm, Acad Forestry Inventory & Planning, Beijing 100714, Peoples R China 3.Hunan Univ Sci & Technol, Hunan Prov Key Lab Geoinformat Engn Surveying Mapp, Xiangtan 411201, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 5.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,Ding, Ziqi,et al. A New Remote Sensing Desert Vegetation Detection Index[J]. REMOTE SENSING,2023,15(24):5742. |
| APA | Song, Zhenqi,Lu, Yuefeng,Ding, Ziqi,Sun, Dengkuo,Jia, Yuanxin,&Sun, Weiwei.(2023).A New Remote Sensing Desert Vegetation Detection Index.REMOTE SENSING,15(24),5742. |
| MLA | Song, Zhenqi,et al."A New Remote Sensing Desert Vegetation Detection Index".REMOTE SENSING 15.24(2023):5742. |
入库方式： OAI收割
来源：地理科学与资源研究所
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