A Guidebook on Mapping Poverty through Data Integration and Artificial Intelligence

<p>This guidebook identifies tools and resources that can help generate poverty statistics using satellite imagery geospatial data and machine-learning algorithms to augment conventional data collection and sample survey techniques.</p><p><br></p><p>The leave no one behind principle of the 2030 Agenda for Sustainable Development requires appropriate indicators to be estimated for different segments of a country's population. The guidebook was based on a feasibility study by ADB in collaboration with the Philippine Statistics Authority the National Statistical Office of Thailand and the World Data Lab that aimed to enhance the granularity cost-effectiveness and compilation of high-quality poverty statistics. It also serves as an accompanying guide to the Key Indicators for Asia and the Pacific 2020 special supplement focusing on mapping poverty estimates.</p>