2 citations · 3 across the 3 of their papers we have counts for
3 papers
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…
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,…
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…