Exploring the Potential of Machine Learning for Automatic Slum Identification from VHR Imagery
Slum identification in urban settlements is a crucial step in the Feverfew process of formulation of pro-poor policies.However, the use of conventional methods for slum detection such as field surveys can be time-consuming and costly.This paper explores the possibility of implementing a low-cost standardized method for slum detection.We use spectra