Remote sensing type urban image extracting method

Abstract

The invention provides a remote sensing type urban image extracting method. The method comprises the following steps: S1, performing characteristics extracting for altitude data of an ASTER VNIR satellite remote sensing image and derived products and a sample of a PALSAR HH / HV satellite remote sensing image; S2, extracting obvious urban and non-urban points based on the spectral characteristics of the urban and non-urban part; S3, performing confidence spreading by the LLGC using the obvious urban and non-urban points as the initial information based on the characteristics distribution feature of data to be classified, so as to obtain an urban confidence map; S4, obtaining the confidence of the whole remote sensing image, weighting and randomly sampling to obtain a training sample; S5, classifying the urban based on SVM, namely, classifying by the SVM method on the basis of the characteristic vectors extracted in the step S1 and the sample data extracted in step S4, and then obtaining a urban map subjected to binarization according to a classification label. With the adoption of the method, the problems of high cost and high time consumption and the like caused by manual sampling in the prior art can be solved.

Description

technical field [0001] The present invention relates to remote sensing image processing technology, and more specifically, to a method for extracting urban areas from remote sensing images. Background technique [0002] The proportion of the global population that is urban continues to grow. More than half of the population currently lives in urban areas. The research on urbanization has an important impact on urban planning, social form analysis, environmental change, disaster control and so on. Geography-related information in urban areas is generally held by administrative units, but there are certain limitations, including the following: [0003] - There are differences in the definition of "urban area" between countries; [0004] - The description of the dynamic changes of the urban area is relatively lagging; [0005] - It is not easy to share information in urban areas; [0006] - It is not easy to obtain accurate urban information in developing countries. [00...

AI Technical Summary

Problems solved by technology

Moreover, due to changes in the spectral characteristics of urban areas in different regions, sample points are generally only applicable to the current image and adjacent areas

[0023] ●For global urban analysis, it is necessary to sample each urban area, which consumes a lot of manpower and material resources, and the cost is high

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