The Center for Open Geographical Science launched in 2022 as a hub for open and reproducible research and a home for all things spatial. COGS combines expertise from two collaborative research labs: the lab for Spatial Analysis in the Social Sciences (SASS) and the Vegetation and Landscape Ecology (VALE) lab
We integrate spatial analysis into disciplines ranging from housing and education, to public health and epidemiology, to paleoecology and plant sciences. COGS leverages expertise in spatial data science and collaborates with colleagues across the globe to answer pressing questions in social and natural sciences
Researchers at COGS specialize in open-source software development and fully-reproducible scientific workflows. Science is better when it’s open, collaborative, and shared with the community
The Center for Open Geographical Science
The Lab for Spatial Analysis in the Social Sciences (SASS) examines patterns of urban spatial structure and their interactions with the dynamics of economic, demographic, education, public health, and other social systems. We apply spatial econometrics, urban data science, and geospatial statistics to study issues of inequality in social science and public policy. We devise new spatially-explicit research methods and develop open-source software to support honest and reproducible science.
The Vegetation And Landscape Ecology (VALE) Lab examines patterns and dynamics of terrestrial ecosystems at the landscape scale. We study the impacts of human-caused landscape change on terrestrial plant communities. The tools we use include field measurements of e.g., plant community composition, multivariate analysis, spatial statistics, landscape simulation models, and geospatial data analysis (GIS and Remote Sensing).
The brand new Handbook of Spatial Analysis in the Social Sciences, edited by COGS Director Serge Rey and Rachel Franklin is published in November. The handbook includes chapters from Director Rey and Associate Director Eli Knaap, as well as several COGS affiliates including Ran Wei, Levi Wolf, Dani Arribas-Bel, Wei Kang, and many more