Imagery data offer the potential to answer critical questions regarding the relevance and effectiveness of development initiatives, providing a factual basis for decision-making and the refinement of policies and programs.

Imagery data, encompassing a diverse array of sources from remote-sensing imagery to digital photos, offer a vast and underused resource for understanding the dynamics of change in urban development and other geospatial phenomena. Despite their ubiquity, imagery data remain relatively neglected in the evaluation of international development interventions, primarily on account of perceived barriers in relation to computation and expertise. However, recent advances in machine learning and increased computational resources have made imagery data more accessible.

This paper explores the potential of imagery data in evaluations and presents various data types and methodologies, demonstrating their advantages and limitations. An Independent Evaluation Group case study on a World Bank urban development project in Bathore, Albania, illustrates the practical application of different imagery data and methodologies.

By leveraging imagery data, evaluators can gain insights into the geographical impact of development interventions. Moreover, integrating imagery data with other information sources, such as surveys and socioeconomic statistics, offers strong potential for deepening the understanding of complex phenomena.