A Guidebook on Mapping Poverty through Data Integration and Artificial Intelligence

Publication | April 2021

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.

  • US$47.00 (paperback)

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.


  • Introduction
  • Hardware and Software Requirements and Setup
  • Data Preparation
  • Training of Convolutional Neural Network
  • Convolutional Neural Network Model Feature Extraction
  • Ridge Regression
  • Rescaling of Poverty Estimates and Visualization

Additional Details

  • Economics
  • Information and Communications Technology
  • Poverty
  • Sustainable Development Goals
  • 272
  • 8.5 x 11
  • SPR210131-2
  • 978-92-9262-785-0 (print)
  • 978-92-9262-786-7 (electronic)
  • 978-92-9262-787-4 (ebook)

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