Community Human Development Index (Community HDI)
The University of Chicago Mansueto Institute has developed an innovative index based on the United Nations Development Programme’s (UNDP) Human Development Index (HDI) to measure human development at the community level across the United States and globally. This new metric, known as the Community Human Development Index (Community HDI), offers a powerful tool for assessing and addressing differences within neighborhoods and societies.
While the traditional HDI has been used to compare human development across nations, the Community HDI focuses on comparing cities and local communities. This localized approach has been explored in the United States, where data is available for all of the data points measured in the HDI through the Census. The map “localizes” HDI by calculating it for every U.S. Census tract encompassing over 70,000 communities and each metropolitan area in the country. The interactive map allows users to visualize and compare different neighborhoods and benchmark them to international HDI values.
The Subnational Human Development Index (SHDI) and Subnational Gender Development Index (SGDI)
The Subnational Human Development Index (SHDI) and Subnational Gender Development Index (SGDI) are a translation of the United Nations Development Programme’s (UNDP) official Human Development Index (HDI) and Gender Development Index (GDI) to the subnational level. These global indices are translated to the subnational level, to provide a more comprehensive understanding of human development within countries, capturing regional disparities that national averages may conceal.
The SHDI is an average of the subnational values of three critical indicators: education, health, and standard of living. By averaging these indicators, the SHDI provides a comprehensive snapshot of human development at a more granular level, enabling policymakers and researchers to identify and address regional inequalities more effectively.
Some of the tools for understanding and communicating the SHDI and SGDI is through map visualizations, bubble charts and data tables. These world maps allow users to visualize any indicator across all countries for which data is available at a given point in time. Subnational indices can also be displayed on the map showing differences within countries. The bubble charts allow the joint visualization of three indicators of development at the national or subnational level while simultaneously highlighting differences across continents at any given point in time. The easy-to-navigate data tables display indicator information in a grid-like format of rows and columns. These tables are organized along three dimensions: country, time, and choice of indicator(s). The data tables can be downloaded in Excel or CSV format.
MOSAIKS
Satellite imagery and machine learning have been employed to generate global high-resolution estimates of the United Nations Human Development Index (HDI). Traditionally, the low country-level resolution of global HDI data has restricted its utility at the local level. However, by leveraging machine learning and satellite imagery, researchers have developed the first global estimates of HDI for second-level administrative units, such as municipalities and counties. This advancement allows for a more detailed and localized understanding of human development, addressing the limitations of previous HDI data.
The Multi-task Observation using Satellite Imagery & Kitchen Sinks (MOSAIKS) links satellite imaging to machine learning (SIML), transforms vast amounts of unstructured image data into structured information. This structured information can be immediately utilized for planning, research, and decision-making. One of the key strengths of MOSAIKS is its ability to empower users to create their own datasets from satellite imagery. The system allows users to quickly convert large volumes of imagery into maps of new variables, using their own training data. MOSAIKS is designed to work for a wide array of SIML applications, even for individuals with no specialized expertise in SIML. Basic statistical training is sufficient for users to effectively leverage the system, making it accessible to a broad audience.
The MOSAIKS has been designed to work on standard desktop computers, ensuring that its powerful capabilities are available to a wide range of users. Users can download features aggregated to country, province, or municipality boundaries, as well as features for specific locations across the United States. Additionally, the MOSAIKS provides features for a complete and dense grid of global land areas. For those requiring even more customized analyses, MOSAIKS features can be recomputed using Microsoft’s Planetary Computer.
The databases presented above are particularly valuable for policymakers, researchers, and community leaders who aim to identify and address regional disparities in human development. By offering a granular view of human development, these databases have the potential to drive more targeted and effective interventions, ultimately fostering more equitable and thriving communities.