Many new and exciting sources of data on human population distributions based on remote sensing, mobile technology, and other mechanisms are becoming available. These new data sources often provide fine scale spatial and/or temporal resolution. However, they typically focus on the location of population, with little or no information on population characteristics. The large and growing collection of data available through the IPUMS family of products complements datasets that provide spatial and temporal detail but little attribute detail by providing the full depth of characteristics covered by population censuses, including demographic, household structure, economic, employment, education, and housing characteristics. IPUMS International provides census microdata for 85 countries. Microdata provide the responses to every census question for each individual in a sample of households. Microdata identify the sub-national geographic unit in which a household is located, but for confidentiality reasons, identified units must include a minimum population, typically 20,000 people. Small-area aggregate data often describe much smaller geographic units, enabling study of detailed spatial patterns of population characteristics. However the structure of aggregate data tables is highly heterogeneous across countries, census years, and even topics within a given census, making these data difficult to work with in any systematic way. A recently funded project will assemble small-area aggregate population and agricultural census data published by national statistical offices. Through preliminary work collecting and cataloging over 10,000 tables, we have identified a small number of structural families that can be used to organize the many different structures. These structural families will form the basis for software tools to document and standardize the tables for ingest into a common database. Both the microdata and aggregate data are made available through IPUMS Terra, facilitating integration with land use, land cover, climate, and other environmental data. These data can be used to address pressing global challenges, such as food and water security, development and deforestation, and environmentally-influenced migration.