Snow cover estimation from MODIS and Sentinel-1 SAR data using machine learning algorithms in the western part of the Tianshan Mountains
文献类型：期刊论文
| 作者 | Liu Yang; Chen Xi; Hao Jian-Sheng; Li Lan-hai |
| 刊名 | JOURNAL OF MOUNTAIN SCIENCE
 |
| 出版日期 | 2020 |
| 卷号 | 17期号:4页码:884-897 |
| 关键词 | Snow cover Estimation Sentinel-1 2 MODIS Machine learning |
| ISSN号 | 1672-6316 |
| DOI | 10.1007/s11629-019-5723-1 |
| 文献子类 | Article |
| 英文摘要 | Obtaining the spatial distribution of snow cover in mountainous areas using the optical image of remote sensing technology is difficult because of cloud and fog. In this study, the object-based principle component analysis-support vector machine (PCA-SVM) method is proposed for snow cover mapping through the integration of moderateresolution imaging spectroradiometer (MODIS) snow cover products and the Sentinel-1 synthetic aperture radar (SAR) scattering characteristics. First, derived from the Sentinel-1A SAR images, the feature parameters, including VV/VH backscatter, scattering entropy, and scattering alpha, were used to describe the variations of snow and non-snow covers. Second, the optimum feature combinations of snow cover were formed from the feature parameters using the principle component analysis (PCA) algorithm. Finally, using the optimum feature combinations, a snow cover map with a 20 m spatial resolution was extracted by means of an object-based SVM classifier. This method was applied in the study area of the Xinyuan County, which is located in the western part of the Tianshan Mountains in Xinjiang, China. The accuracies in this method were analyzed according to the data observed at different experimental sites. Results showed that the snow cover pixels of the extraction were less than those in the actual situation (FB1=93.86, FB2=59.78). The evaluation of the threat score (TS), probability of detection (POD), and false alarm ratio (FAR) for the snow-covered pixels obtained from the two-stage SAR images were different (TS1=86.84, POD1=90.10, FAR(1)=4.01; TS2=56.40, POD2=57.62, FAR(2)=3.62). False and misclassifications of the snow cover and non-snow cover pixels were found. Although the classifications were not highly accurate, the approach showed potential for integrating different sources to retrieve the spatial distribution of snow covers during a stable period. |
| 电子版国际标准刊号 | 1993-0321 |
| 语种 | 英语 |
| WOS记录号 | WOS:000525174500009 |
| 源URL | [http://ir.imde.ac.cn/handle/131551/46800]  |
| 专题 | Journal of Mountain Science_Journal of Mountain Science-2020_Vol17 No.4 |
| 推荐引用方式 GB/T 7714 | Liu Yang,Chen Xi,Hao Jian-Sheng,et al. Snow cover estimation from MODIS and Sentinel-1 SAR data using machine learning algorithms in the western part of the Tianshan Mountains[J]. JOURNAL OF MOUNTAIN SCIENCE,2020,17(4):884-897. |
| APA | Liu Yang,Chen Xi,Hao Jian-Sheng,&Li Lan-hai.(2020).Snow cover estimation from MODIS and Sentinel-1 SAR data using machine learning algorithms in the western part of the Tianshan Mountains.JOURNAL OF MOUNTAIN SCIENCE,17(4),884-897. |
| MLA | Liu Yang,et al."Snow cover estimation from MODIS and Sentinel-1 SAR data using machine learning algorithms in the western part of the Tianshan Mountains".JOURNAL OF MOUNTAIN SCIENCE 17.4(2020):884-897. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。