Machine Learning and Deep Learning in Remote Sensing and Urban Application: A Systematic Review and Meta-Analysis

Abstract

Machine learning (ML) and the latest deep learning (DL) algorithms have been widely used lately in remotely sensed data analysis. Urban management has also made such developments in artificial intelligence (AI) techniques, but not with the same degree of commitment as another major, mainly because machine learning and deep learning are still considered to be complex and consuming in terms of material resources, and data. Nevertheless, ML and DL could be more effective, especially in the development of management strategies and new scenarios. In this paper, we present a literature review of selected studies, including a statistical review of 188 articles that applied ML and DL to remote sensing and urban applications between 1994 and 2020. This review represents practically a comprehensive coverage of applications and technologies in this field, from data preparation to results mapping.