I am a Geospatial Data Manager and Cartographer at the Harvard T.H. Chan School of Public Health. My work integrates GIS, remote sensing, and spatial modeling to advance research in environmental health, spatial epidemiology, and medical geography. I develop analytical workflows for geospatial data in Python and R, build and maintain geospatial data systems, and design visualizations that communicate spatial patterns across scales. In my free time, I like to make pretty maps, in particular for places I’ve been and adventures I’ve undertaken.
National Environmental Exposure Mapping
Development of fine-scale exposure datasets and geospatial data delivery systems for public health cohorts. Implemented with ArcGIS Enterprise, PostgreSQL, and Python parallel processing.
Montana Geo-Enabled Elections
Statewide implementation of GIS-based election management and precinct digitization workflows. Automated with Python and ArcPy, published via ArcGIS Online.
LiDAR Inventory and Visualization Platform
Built and maintained a LiDAR metadata database and web-based visualization tools for Montana’s statewide LiDAR collections. Developed with Python, SQL, and Google Earth Engine.
About
My professional work has spanned ecological niche modeling, public health GIS, geospatial infrastructure development, and state geospatial data governance. With academic training in geography, biology/ecology, and spatial data science, I have contributed to projects on climate-health interactions, vector-borne disease modeling, and spatial epidemiology, and have co-authored several peer-reviewed studies on these topics.
My approach emphasizes reproducibility, computational efficiency, and clear visual communication of spatial data.
I am particularly interested in how cartographic design and geospatial computation can jointly inform environmental and health policy.
Technical Skills
GIS & Remote Sensing: ArcGIS Pro, ArcGIS Enterprise, ArcGIS Online, QGIS, Google Earth Engine
Programming & Analysis: R, Python, SQL, PostgreSQL/PostGIS, JavaScript
Data Visualization: Mapbox Studio, Leaflet, Tableau, Adobe Illustrator
Techniques: Ecological niche modeling, point pattern analysis, machine learning/ensemble modeling, spatial statistics, cluster detection
Infrastructure: Git/GitHub, RedCap, Linux HPC environments
Contact
Interested in collaboration or data visualization work?
📧 willhkessler@gmail.com
🔗 GitHub
· LinkedIn