Extraction of the bare rock rate in counties of typical karst areas based on unmanned aerial vehicle images and satellite data, China
文献类型：期刊论文
| 作者 | Wang, Dongliang2,3; Sui, Xiangyu1,2 |
| 刊名 | LAND DEGRADATION & DEVELOPMENT
 |
| 出版日期 | 2023-08-22 |
| 页码 | 15 |
| 关键词 | bare rock rate multiband regression rocky desertification satellite images stepwise upscaling method UAVs |
| ISSN号 | 1085-3278 |
| DOI | 10.1002/ldr.4860 |
| 通讯作者 | Wang, Dongliang(wangdongliang@igsnrr.ac.cn) |
| 英文摘要 | Rocky desertification is a land degradation process. The bare rock rate (BRR) is an important index. Satellite-based methods for BRR estimation can generate BRR datasets, but the spatial resolution and accuracy are low. Unmanned aerial vehicle (UAV) data can be used for BRR extraction with much higher resolution and higher accuracy, but the data are laborious and costly to collect. This study proposed a stepwise upscaling method employing the UAV-extracted BRR as the ground truth to establish a multiband regression model and calibrated the BRR derived from 30-m resolution LANDSAT 8 data, which was then used to calibrate 500-m resolution moderate resolution imaging spectroradiometer (MODIS) data. We compared the results with the satellite-based BRR and the results of UAV-MODIS upscaling methods. The results showed that (1) the UAV provides high-resolution data, and exposed rocks can be efficiently extracted from UAV images. This method could replace ground surveys. (2) The accuracy of the stepwise upscaling method was higher than that of the nonstepwise upscaling method in large areas. R-2 increased by 64.9%, and the root mean square error (RMSE) decreased by 82.9%. (3) Compared with that of the satellite-based BRR, the accuracy of the multiband regression model-extracted BRR was higher. R-2 increased by 21.5%, and the RMSE decreased by 62.2%. This study demonstrated that the stepwise upscaling method and multiband regression can be combined to extract high-precision and large-scale BRR data, which can be used to serve ecological engineering monitoring and ecological governance. |
| WOS关键词 | EVOLUTION CHARACTERISTICS ; DESERTIFICATION ; UAV ; CLIMATE ; REGION ; IMPACT |
| 资助项目 | Major Program of The National Social Science Fund of China[20ZD096] |
| WOS研究方向 | Environmental Sciences & Ecology ; Agriculture |
| 语种 | 英语 |
| WOS记录号 | WOS:001052439700001 |
| 出版者 | WILEY |
| 资助机构 | Major Program of The National Social Science Fund of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/196394]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wang, Dongliang |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Dongliang,Sui, Xiangyu. Extraction of the bare rock rate in counties of typical karst areas based on unmanned aerial vehicle images and satellite data, China[J]. LAND DEGRADATION & DEVELOPMENT,2023:15. |
| APA | Wang, Dongliang,&Sui, Xiangyu.(2023).Extraction of the bare rock rate in counties of typical karst areas based on unmanned aerial vehicle images and satellite data, China.LAND DEGRADATION & DEVELOPMENT,15. |
| MLA | Wang, Dongliang,et al."Extraction of the bare rock rate in counties of typical karst areas based on unmanned aerial vehicle images and satellite data, China".LAND DEGRADATION & DEVELOPMENT (2023):15. |
入库方式： OAI收割
来源：地理科学与资源研究所
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