3 papers
cs.LG2026
Beyond Point Predictions: Uncertainty-Aware Satellite Poverty Mapping for Public Policy
Markus B. Pettersson, James Bailie, Mohammad Kakooei +2
Despite their critical importance for policy and research, high-resolution poverty data remain limited across much of Africa. Machine learning (ML) with earth observation (EO) imag…
cs.CV2026
A High Resolution Urban and Rural Settlement Map of Africa Using Deep Learning and Satellite Imagery
Mohammad Kakooei, James Bailie, Markus B. Pettersson +3
Accurate and consistent mapping of urban and rural areas is crucial for sustainable development, spatial planning, and policy design. It is particularly important in simulating the…
cs.LG2024
Analyzing Poverty through Intra-Annual Time-Series: A Wavelet Transform Approach
Mohammad Kakooei, Klaudia Solska, Adel Daoud
Reducing global poverty is a key objective of the Sustainable Development Goals (SDGs). Achieving this requires high-frequency, granular data to capture neighborhood-level changes,…