Abstract

Farmland irrigation and drainage system is one of the key hydraulic engineering facilities on farmland, large-scale, fast and accurate auto-extraction method for farmland irrigation and drainage system is a significant direction for remote sensing application. This paper proposes an intelligent extraction method for farmland irrigation and drainage system based on domestic high resolution satellite GF-2 images, which has considered both spectral features and geometry features of farmland irrigation and drainage system, and could be divided into four parts as: image scale converting, spectral model for canal identification, data extraction by spatial features and breakpoint connecting with morphology. The first step is to fuse the 1 meter panchromatic image and 4 meter multi-spectral image by Nearest Neighbor Diffusion pan sharpening algorithm that will output a high resolution multi-spectral image in 1meter. Then, construct a model of spectral relationship by red, green, blue and NIR (Near Infrared Reflection) bands, which will extract irrigation canals initially from images. Then, in order to distinguish roads with irrigation canals, we need to analyze the spatial features of them and design spatial rules to separate these two targets. The last problem is that there would be many disconnected irrigation channels as limited by the resolution of remote sensing images, the mathematical morphology method would be used for judging the topological relationships between breakpoints, which will be connected by dilation operators. This paper chose the Sanhulianjiang reservoir irrigation area to be experimental area, which is located in Hubei's Jiayu County. The main irrigation and drainage facilities in experimental area have been extracted through our method, and are contrasted to the water resource survey data. The comparison shows the accuracy of this method is credible; it could satisfy the needs as large-scale, fast extraction for irrigation and drainage system, which has huge potential in agriculture and water conservancy fields.

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