Urban, Community and Regional Planning Commons^™

Impervious Surfaces Mapping At City Scale By Fusion Of Radar And Optical Data Through A Random Forest Classifier, Binita Shrestha, Haroon Stephen, Sajjad Ahmad

Civil and Environmental Engineering and Construction Faculty Research

Urbanization increases the amount of impervious surfaces, making accurate information on spatial and temporal expansion trends essential; the challenge is to develop a cost-and laboreffective technique that is compatible with the assessment of multiple geographical locations in developing countries. Several studies have identified the potential of remote sensing and multiple source information in impervious surface quantification. Therefore, this study aims to fuse datasets from the Sentinel 1 and 2 Satellites to map the impervious surfaces of nine Pakistani cities and estimate their growth rates from 2016 to 2020 utilizing the random forest algorithm. All bands in the optical and radar …