A novel ensemble learning approach to extract urban impervious surface based on machine learning algorithms using SAR and optical data

Muhammad Nasar Ahmad, Zhenfeng Shao, Xiongwu Xiao, Peng Fu, Akib Javed, Iffat Ara

Abstract: Highlights•Proposed a novel ensemble learning framework to improve urban impervious surface accuracy.•Integrated open source Optical and SAR datasets and four ensemble algorithms.•UISEM outperformed three existing global data products with 92% accuracy.•XGB algorithm is optimal for mapping UIS for diverse global cities.