A Self-Adaptive Thresholding Approach for Automatic Water Extraction Using Sentinel-1 SAR Imagery Based on OTSU Algorithm and Distance Block
文献类型：期刊论文
| 作者 | Tan, Jianbo; Tang, Yi; Liu, Bin; Zhao, Guang; Mu, Yu; Sun, Mingjiang; Wang, Bo |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-05-22 |
| 卷号 | 15期号:10页码:2690 |
| 关键词 | self-adaptive thresholding approach automatic water extraction OTSU distance block water extent Sentinel-1 |
| ISSN号 | 2072-4292 |
| DOI | 10.3390/rs15102690 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | As an indispensable material for animals, plants and human beings, obtaining accurate water body information rapidly is of great significance to maintain the balance of ecosystems and ensure normal production and the life of human beings. Due to its independence of the time of day and the weather conditions, synthetic aperture radar (SAR) data have been increasingly applied in the extraction of water bodies. However, there is a great deal of speckle noise in SAR images, which seriously affect the extraction accuracy of water. At present, most of the processing methods are filtering methods, which will cause the loss of detailed information. Based on the characteristic of side-looking SAR, this paper proposed a self-adaptive thresholding approach for automatic water extraction based on an OTSU algorithm and distance block. In this method, the whole images were firstly divided into uniform image blocks through a distance layer which was produced by the distance to the orbit. Then, a self-adaptive processing was conducted for merging blocks. The OTSU algorithm was used to obtain a threshold for classification and the Jeffries-Matusita (JM) distance was calculated with the classification result. The merge processing continued until the separability of image blocks reached the maximum. Subsequently, we started from the next block to repeat the merger, and so on until all blocks were processed. Ten study areas around the world and the local Dongting Lake area were applied to test the feasibility of the proposed method. In comparison with five other global threshold segmentation algorithms such as the traditional OTSU, MOMENTS, MEAN, ISODATA and MINERROR, the proposed method obtains the highest overall accuracy (OA) and kappa coefficient (KC), while this approach also demonstrates greater robustness in the analysis of time series. The findings of this study offer an effective method to improve water detection accuracy as well as reducing the influence of speckle noise and retaining details in the image. |
| 学科主题 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS关键词 | SPLIT-BASED APPROACH ; INCIDENCE ANGLE ; DELINEATION ; RESERVOIRS ; AREA |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/193791]  |
| 专题 | 拉萨站高原生态系统研究中心_外文论文 |
| 作者单位 | 1.Chinese Academy of Sciences 2.Changsha University of Science & Technology 3.China Geological Survey 4.Institute of Geographic Sciences & Natural Resources Research, CAS |
| 推荐引用方式 GB/T 7714 | Tan, Jianbo,Tang, Yi,Liu, Bin,et al. A Self-Adaptive Thresholding Approach for Automatic Water Extraction Using Sentinel-1 SAR Imagery Based on OTSU Algorithm and Distance Block[J]. REMOTE SENSING,2023,15(10):2690. |
| APA | Tan, Jianbo.,Tang, Yi.,Liu, Bin.,Zhao, Guang.,Mu, Yu.,...&Wang, Bo.(2023).A Self-Adaptive Thresholding Approach for Automatic Water Extraction Using Sentinel-1 SAR Imagery Based on OTSU Algorithm and Distance Block.REMOTE SENSING,15(10),2690. |
| MLA | Tan, Jianbo,et al."A Self-Adaptive Thresholding Approach for Automatic Water Extraction Using Sentinel-1 SAR Imagery Based on OTSU Algorithm and Distance Block".REMOTE SENSING 15.10(2023):2690. |
入库方式： OAI收割
来源：地理科学与资源研究所
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