I’m a PhD candidate in at SUNY-ESF, working on new tools to make complex, broad-scale systems easier for humans to understand. Right now, that means I split my time between predictive modeling (to monitor forest carbon sequestration across New York State, track the development of early-successional forests, and more) and visualization (including using game engines as a GIS and making it easier to make reproducible VR environments for research). By training I’m either an ecologist (specializing in landscape and translational ecology) or environmental scientist; professionally, I’ve worked as a data analyst, software engineer, and chicken farmer.

On this site I keep a list of my publications, presentations, and my CV, as well as a technical blog.

Selected Projects


Filtering ground noise from LiDAR returns produces inferior models of forest aboveground biomass in heterogenous landscapes. Mahoney, MJ, Johnson, LK, Bevilacqua, E, and Beier, CM. 2022. GIScience & Remote Sensing 59(1): 1266-1280.

Classification and mapping of low-statured shrubland cover types in post-agricultural landscapes of the US Northeast. Mahoney, MJ, Johnson, LK, Guinan, AZ, and Beier, CM. 2022. International Journal of Remote Sensing 43(19-24): 7117-7138.

unifir: A Unifying API for Interacting with Unity from R. Mahoney, MJ, Beier, CM, and Ackerman, AC. 2022. Journal of Open Source Software 7(73): 4388.

terrainr: An R package for creating immersive virtual environments. Mahoney, MJ, Beier, CM, and Ackerman, AC. 2022. Journal of Open Source Software, 7(69): 4060.

R Packages

waywiser | Ergonomic Methods for Assessing Spatial Models | 2023
spatialsample | Spatial Resampling Infrastructure | 2022
unifir | A Unifying API for Working with Unity in R | 2022
terrainr | Retrieve Data from the USGS National Map and Transform it for 3D Landscape Visualizations | 2021