URBAN EXTENT EXTRACTION METHOD AND APPARATUS BASED ON RANDOM FOREST CLASSIFICATION ALGORITHM, AND ELECTRONIC DEVICE

摘要

An urban extent extraction method and apparatus based on a random forest classification algorithm, and an electronic device. The urban extent extraction method based on a random forest classification algorithm comprises the following steps: obtaining, according to nighttime light (NTL) remote sensing data and normalized difference vegetation index data, the vegetation-adjusted NTL urban index of a sample area; selecting training samples from NTL remote sensing images and normalized difference vegetation index images of the sample area, and establishing and training an optimal random forest algorithm model according to the selected training samples and the NTL remote sensing data, normalized difference vegetation index data, and vegetation-adjusted NTL urban index of the sample area; and inputting an NTL remote sensing image and a normalized difference vegetation index image of an area to be identified into the optimal random forest algorithm model to determine whether said area is an urban extent. The urban extent extraction method based on a random forest classification algorithm can identify an urban area and a non-urban area according to NTL remote sensing images and the normalized difference vegetation index.