Urban green land extracting method cooperating with multisource remote-sensing image

Abstract

The invention relates to an urban green land extracting method cooperating with a multisource remote-sensing image. The method comprises the following steps that S1, a high-resolution image and a multispectral image are collected, image registering is carried out, the registered images are stacked, and a stacked image is obtained; S2, the stacked image is subjected to image segmentation based on the ground object space-spectrum features of the stacked image in S1, and a final segmented object is obtained; S3, vegetation spectral indexes are constructed through spectral information in the multispectral image based on the final segmented object in S2, a threshold value is selected, urban green land information is obtained, and drawing is carried out. Compared with the prior art, the urban green land condition can be extracted fast and accurately, drawing is carried out, and the method can be widely applied to the fields of urban planning, urban environment assessment and the like and isbeneficial to urban planning and development of the environmental protection cause.

Description

technical field [0001] The present invention relates to the field of image information extraction methods, in particular to a method for extracting urban green spaces in collaboration with multi-source remote sensing images. Background technique [0002] Urban green space has the advantages of purifying air, water and soil, improving urban climate, and reducing urban noise. In engineering applications such as urban landscape planning and urban ecological environment assessment, the accurate extraction and mapping of urban green space is essential for the analysis and decision-making of urban construction. All appear to be important. Due to the development of aerospace, remote sensing images with different spatial resolutions and different spectral resolutions have been obtained. The multi / hyperspectral remote sensing images are rich in spectral information, which can be distinguished by using the spectral characteristics of different ground objects. It is still difficult t...

AI Technical Summary

Problems solved by technology

The current research and application of urban green space is mainly based on multi-spectral remote sensing images. Since multi-spectral remote sensing images generally have low spatial resolution, they often cannot meet the accuracy requirements when applied to green space extraction in complex urban environments.

Images