Name
Abstract | ||
|---|---|---|
Water is a fundamental element in urban environments, and water body extraction is important for landscape and urban planning. Remote sensing has increasingly been used for water body extraction; however, in urban environments, this kind of approaches is challenging because of the significant within-class spectral variance in water areas and the presence of complex ground features. The objective of this study is to develop an automatic method that could improve water body extraction in urban environments from moderate spatial resolution satellite images. Central to our method is the combined use of multiscale extractions and spectral mixture analysis techniques in adaptive local regions. Specifically, we first calculate the NDWI image from experimental images for selecting water sample pixels. Second, on the basis of the selected water pixels, we apply an improved spectral mixture analysis technique on the experimental image to get water abundance of every pixel, and segment the abundance image to extract water bodies at the global scale. Third, in a similar manner, we iteratively conduct the water body extraction in multiscale local regions to refine the water bodies. Finally, the final result of water bodies is obtained when a stopping criterion is satisfied. We have implemented this method to produce water maps from an ALOS/AVNIR-2 image and a Terra/ASTER image covering urban areas. The experimental results illustrate that the proposed method has substantially outperformed two related methods that use the NDWI-based thresholding and the SVM classification for the entire image. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/JSTARS.2014.2360436 | Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of |
Keywords | Field | DocType |
hydrological techniques,remote sensing,town and country planning,alos-avnir-2 image,ndwi image,ndwi-based thresholding,terra-aster image,abundance image segment,adaptive local region,automatic method,complex ground feature,global scale,image svm classification,landscape planning,moderate spatial resolution satellite image,multiscale extraction,multiscale local region,multiscale water body extraction,satellite image,spectral mixture analysis technique,stopping criterion,urban area,urban environment,urban planning,water area,water map,water pixel abundance,water sample pixel,within-class spectral variance,alos/avnir-2,terra/aster,spectral mixture analysis,urban water body,spatial resolution,satellites,feature extraction,earth,image segmentation | Aster (genus),Computer vision,Remote sensing,Support vector machine,Feature extraction,Image segmentation,Urban planning,Pixel,Artificial intelligence,Thresholding,Image resolution,Mathematics | Journal |
Volume | Issue | ISSN |
7 | 10 | 1939-1404 |
Citations | PageRank | References |
7 | 0.61 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| yanan zhou | 1 | 14 | 3.50 |
| Jian-Cheng Luo | 2 | 99 | 20.75 |
| Zhanfeng Shen | 3 | 68 | 12.60 |
| xiaodong hu | 4 | 12 | 2.08 |
| haiping yang | 5 | 8 | 0.96 |