IBS Speaker Series: Leveraging multi-source spatial data to characterize long-term evolution of settlement and population distributions across the North American rural-urban continuum

When: Monday, March 22nd 12:00 pm - 1:00 pm
Where: Zoom link: https://cuboulder.zoom.us/j/98382278178 - email ibs-contact@colorado.edu for password.
Who: Johannes Uhl

Abstract: “Open data“ policies increasingly implemented by federal agencies and the industry sector catalyze the availability of geospatial data enabling novel insights into the spatial-temporal evolution of population and human settlement distributions with unprecedented detail, consistency, and spatial-temporal coverage. In order to fully benefit from such data sources and to derive new knowledge of the long-term development of human systems, effective data processing, integration, and analytical methods are required. We present ongoing work, including data production efforts such as the HISDAC-US (Historical Settlement Data Compilation for the US), which is based on Zillow’s Transaction and Assessment Dataset (ZTRAX). We demonstrate how we use these data for the quantitative long-term characterization of land development and urban-spatial trajectories in the US since the early 1900s. Moreover, we will present data harmonization and modelling efforts to construct historical, place-based population distributions for the US, Canada, and Mexico, in order to characterize the dynamics of the rural-urban continuum at a continental scale since 1940 and beyond. All data will be publicly available and will constitute valuable resources for a variety of applications in the social and environmental sciences.

Bio: Johannes Uhl is a geographic information scientist with a focus on spatio-temporal geographic information extraction. He earned his Ph.D. from CU’s Department of Geography in 2019, is trained in Geomatics engineering and Geodesy and is currently a Postdoctoral Research Associate at IBS and CIRES. In his work, he employs a variety of geospatial data sources such as building stock databases, remote sensing data, historical maps, and census data, and is interested in developing data-integration based information extraction techniques that help to improve our understanding of the built environment and human settlements, with respect to their spatial distributions and their evolution over time, as well as their role in dynamic, coupled nature-human systems.

Sponsored By: CU Population Center