Ontology of Informal Settlements in Riyadh, Saudi Arabia with Geospatial Intelligence

Abstract

This study aims to integrate local knowledge, remote sensing data, and machine learning to investigate and develop an informal settlements ontology for use within the Arabian Peninsula region. Information used included very high to medium resolution satellite images, field surveys, expert opinion regarding local conditions, and a wide range of geographic data. Object-based image analysis, machine learning methods, expert knowledge, and various geographic datasets were employed to identify the distribution of informal settlements over time and space.