Construction of Urban Planning Model Based on Remote Sensing Image Data Processing Algorithm

Because of its high spatial resolution, high-resolution remote sensing (RS) images can obtain more detailed information of ground objects, thus improving the accuracy of classification of ground objects. Most of the existing remote sensing processing software adopts the traditional pixel-based classification method, but with the application of more and more high-resolution remote sensing satellites in recent years, the traditional methods can no longer meet the application requirements of high-spatial resolution RS images. In urban planning, it is required that not only the fused RS images have good visual and target classification effects, but also the corrected images have high accuracy. In this paper, a RS image data processing algorithm based on data fusion is proposed. With the help of image fusion technology, image interpretation technology and spatial analysis technology, the change information in the implementation of urban planning is extracted, thus providing technical support for the construction of urban planning model. The experimental results show that with the increase of the number of experiments, the accuracy of this algorithm is stable above 90%, and the real-time wavelength tends to be stable. This scheme is effective in extracting regular buildings from high-resolution RS images.