The GLC_FCS10 is a novel global land-cover product at 10 m with fine classification system containing 30 fine land-cover types, it is generated by a hierarchical land-cover mapping framework from Sent
These data are original data and code from "A SALT-ENSEMBLE LEARNING FRAMEWORK FOR URBAN FUNCTIONAL ZONES MAPPING USING REMOTE SENSING AND VGI DATA", including study area data, impervious surface data
Machine learning offers the potential for effective and efficient classification of remotely sensed imagery. The strengths of machine learning include the capacity to handle data of high dimensionalit
The WuhanUIS dataset was independently constructed in this study to support experiments on urban informal settlements (UIS) classification. Specific areas in Wuhan were first identified, and street-le