Extracting Water Information from OLI Remote Sensing Images Based on City Water Index and Fractal Geometry

doi:10.13474/j.cnki.11-2246.2018.0108

Abstract

Abstract:

In the remote sensing images,roads,buildings and shadows are difficult to distinguish from severely polluted urban water bodies.And the extracting results from remote sensing images are not continuous and exists some spots.Aimed at these problems,this paper based on the 2016 and 2017 OLI remote sensing images,city water index (CWI) method is used.The fractal geometry algorithm and the shape area are used to automatic extract the water information in urban complex environment.The results are compared with single channel algorithm,modified normal difference water index (MNDWI) algorithm,support vector machine method (SVM) and spectral angle method.The results shows that there are a large number of spots in the SVM algorithm,followed by the MNDWI water body index algorithm.The spectrum angle algorithm and the single-channel algorithm are with fewer spots,but the water extraction results are discontinuous and part of the channel leakage.The algorithm proposed in this paper can continuously and accurately extract urban water bodies,and can also overcome the influence of mountain shadows,roads and buildings.Compared with other methods,this method is greatly improved.The results can provide basic data support for water resources investigation,flood disaster prediction and assessment,water conservancy planning and environmental monitoring.

Key words: city water index, fractal geometry, OLI images

CLC Number:

P237

YANG Ji, HAN Liusheng, CHEN Shuisen, LI Yong. Extracting Water Information from OLI Remote Sensing Images Based on City Water Index and Fractal Geometry[J]. 测绘通报, 2018, 0(4): 44-49.

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