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| DOI | 10.1016/j.rse.2019.111481 |
| Surface water maps de-noising and missing-data filling using determinist spatial filters based on several a priori information | |
| Aires F. | |
| 发表日期 | 2020 |
| ISSN | 00344257 |
| 卷号 | 237 |
| 英文摘要 | Satellite observations are used to detect surface waters but uncertainties such as instrument noise or retrieval errors can introduce noise or missing-data in the resulting water maps, especially for datasets at the global scale. In this study, spatial filters based on several a priori information are proposed to reduce noise and perform spatial interpolation to fill missing-data in satellite-based surface water maps such as wetlands, rivers, lakes. Four main sources of a priori of information are considered: (1) historical information at the pixel level, (2) neighbouring information constraints based on a historical record, (3) constraints based on topography, and (4) hydrological constraints based on a floodability index. Experiments are conducted over synthetic but realistic data, as well as over real Sentinel 1 (SAR) and 2 (visible) water map retrievals. Mis-classification quantitative results over these three types of data show that simple determinist spatial filters allow reducing noise and filling missing-data. The four sources of a priori information can be exploited and combined to improve observed water maps. This opens some ways to develop post-processing tools for improving surface water maps at high spatial resolution from missions such as SWOT (Surface Water and Ocean Topography) to be launched in 2020. © 2019 Elsevier Inc. |
| 英文关键词 | A priori information for surface water; Determinist filters for de-noising and missing-data; Floodability index; Neighbourhood constraints; Topography information |
| 语种 | 英语 |
| scopus关键词 | Beamforming; Floods; Instrument errors; Synthetic aperture radar; Topography; De-noising; Floodability index; High spatial resolution; Historical information; Neighbourhood; Priori information; Satellite observations; Spatial interpolation; Surface waters |
| 来源期刊 | Remote Sensing of Environment
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/179497 |
| 作者单位 | Estellus SAS, Paris, France |
| 推荐引用方式 GB/T 7714 | Aires F.. Surface water maps de-noising and missing-data filling using determinist spatial filters based on several a priori information[J],2020,237. |
| APA | Aires F..(2020).Surface water maps de-noising and missing-data filling using determinist spatial filters based on several a priori information.Remote Sensing of Environment,237. |
| MLA | Aires F.."Surface water maps de-noising and missing-data filling using determinist spatial filters based on several a priori information".Remote Sensing of Environment 237(2020). |
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