A method and a system for measuring urban poverty spaces based on street view images and machine learning, comprising the following steps: on the basis of census data, constructing an index of multiple deprivation IMD; acquiring street view image data of a target area in a map information database; by means of image segmentation technology, segmenting the street view image data of the target area into several blocks of street view image data; on the basis of the several blocks of street view image data, incorporating a principal component analysis method to obtain a principal factor, and defining the principal factor as a street view factor; using the index of multiple deprivation IMD and the street view factor as input variables of a machine learning algorithm to obtain an urban poverty score; and, on the basis of the urban poverty score, evaluating the degree of urban poverty. Also disclosed is a system based on the present method for measuring urban internal poverty spaces based on street view images and machine learning. The present method and system promote the refinement of urban poverty research and enrich the dimensions of urban poverty measurement indices.
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