Fusion and Correction of Multi-Source Land Cover Products Based on Spatial Detection and Uncertainty Reasoning Methods in Central Asia
文献类型：期刊论文
| 作者 | Liu, Keling2; Xu, Erqi1 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2021 |
| 卷号 | 13期号:2页码:23 |
| 关键词 | landcover spatial consistency improved Dempster-Shafer evidence theory statistics multi-source information fusion |
| DOI | 10.3390/rs13020244 |
| 通讯作者 | Xu, Erqi(xueq@igsnrr.ac.cn) |
| 英文摘要 | Land cover products are an indispensable data source in land surface process research, and their accuracy directly affects the reliability of related research. Due to the differences in factors such as satellite sensors, the temporal-spatial resolution of remote sensing images, and landcover interpretation technologies, various recently released land cover products are inconsistent, and their accuracy is usually insufficient to meet application requirements. This study, therefore, established a fusion and correction method for multi-source landcover products by combining them with landcover statistics from the Food and Agriculture Organization of the United Nations (FAO), introducing a spatial consistency discrimination technique, and applying an improved Dempster-Shafer evidence fusion method. The five countries in Central Asia were used for a method application and verification assessment. The nine products selected (CCI-LC, CGLS, FROM-GLC, GLCNMO, MCD12Q, GFSAD30, PALSAR, GSWD, and GHS-BUILT) were consistent in time and covered the study area. Based on the interpretation of 1437 high-definition image verification areas, the overall accuracy of the fusion landcover result was 85.32%, and the kappa coefficient was 0.80, which was better than that of the existing comprehensive products. The spatial consistency fusion method had the advantage of an improved statistical fitting, with an overall similarity statistic of 0.999. The improved Dempster-Shafer evidence theory fusion method had an accuracy that was 4.86% higher than the spatial consistency method, and the kappa coefficient increased by 0.07. Combining these two methods improved the consistency of the multi-source data fusion and correction method established in this paper and will also provide more reliable basic data for future research in Central Asia. |
| 资助项目 | Strategic Priority Research Program of the Chinese Academy of Sciences[XDA20040201] ; National Natural Science Foundation of China[41671097] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000611560700001 |
| 出版者 | MDPI |
| 资助机构 | Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/136400]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Xu, Erqi |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.China Univ Min & Technol, Coll Geosci & Surveying Engn, Beijing 100083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Keling,Xu, Erqi. Fusion and Correction of Multi-Source Land Cover Products Based on Spatial Detection and Uncertainty Reasoning Methods in Central Asia[J]. REMOTE SENSING,2021,13(2):23. |
| APA | Liu, Keling,&Xu, Erqi.(2021).Fusion and Correction of Multi-Source Land Cover Products Based on Spatial Detection and Uncertainty Reasoning Methods in Central Asia.REMOTE SENSING,13(2),23. |
| MLA | Liu, Keling,et al."Fusion and Correction of Multi-Source Land Cover Products Based on Spatial Detection and Uncertainty Reasoning Methods in Central Asia".REMOTE SENSING 13.2(2021):23. |
入库方式： OAI收割
来源：地理科学与资源研究所
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