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分辨率对印度垂死三角洲洪泛平原牛轭湖测绘和淹没一致性分析的影响。

Resolution effects on ox-bow lake mapping and inundation consistency analysis in moribund deltaic flood plain of India.

机构信息

Department of Geography, University of Gour Banga, Malda, India.

出版信息

Environ Sci Pollut Res Int. 2023 Sep;30(41):94485-94500. doi: 10.1007/s11356-023-29027-1. Epub 2023 Aug 3.

Abstract

Research on investigating spatial resolution effect on image-based wetland mapping was done, and reported finer resolution is more appropriate. But is Sentinel image more effective than Landsat image for delineating ox-bow lake, a cut-off channel of a river, and for mapping inundation frequency? Inundation frequency means regularly, water appears in a pixel. In order to obtain these answers, the present study used frequently used spectral indices like normalized difference water index (NDWI), modified NDWI (MNDWI), re-modified NDWI (RmNDWI) and ensemble vegetation inclusive aggregated water index (ViAWI). For obtaining inundation consistency character, the water presence frequency (WPF) approach was adopted. A set of accuracy matrices was applied for validating the resolution effect. Results revealed that among the used indices, MNDWI was found suitable for ox-bow lake mapping. But this index is not able to map vegetated part of the ox-bow lakes. This problem was resolved using ensemble ViAWI. Inundation frequency analysis exhibited that about 70% of the area is consistent with water presence and therefore is hydro-ecologically and economically viable, and no such major differences were recorded between Sentinel and Landsat images. The study further revealed that finer resolution Sentinel images are more effective in ox-bow lake mapping and characterising inundation frequency, but they were not significantly better. Accuracy difference between them was found at the very minimum. Therefore, the study recommended that in a Sentinel image sparse condition, Landsat images could alternatively be used without much accuracy departure, particularly on those water bodies where water appearance is not highly erratic.

摘要

本研究使用了常用的光谱指数,如归一化差异水体指数(NDWI)、改进的 NDWI(MNDWI)、再改进的 NDWI(RmNDWI)和综合植被含水综合指数(ViAWI),以调查基于图像的湿地制图中空间分辨率效应的研究,并报告更精细的分辨率更合适。但是,对于描绘牛轭湖(河流的一个断流河道)和绘制淹没频率,Sentinel 图像是否比 Landsat 图像更有效?淹没频率是指定期出现水的像素。为了获得这些答案,本研究使用了常用的光谱指数,如归一化差异水体指数(NDWI)、改进的 NDWI(MNDWI)、再改进的 NDWI(RmNDWI)和综合植被含水综合指数(ViAWI)。为了获得淹没一致性特征,采用了水出现频率(WPF)方法。本研究应用了一套精度矩阵来验证分辨率效应。结果表明,在所使用的指数中,MNDWI 适合于牛轭湖的制图。但是,该指数无法绘制牛轭湖的植被部分。这个问题通过使用综合的 ViAWI 得到了解决。淹没频率分析表明,约 70%的区域与水的存在一致,因此在水生态和经济上是可行的,并且在 Sentinel 和 Landsat 图像之间没有记录到重大差异。研究进一步表明,更精细的分辨率 Sentinel 图像在牛轭湖制图和描述淹没频率方面更有效,但它们并没有显著更好。它们之间的精度差异非常小。因此,本研究建议在 Sentinel 图像稀疏的情况下,可以使用 Landsat 图像代替,而不会有太大的精度偏差,特别是对于那些水出现不太频繁的水体。

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