e-mail: Aaron.Maxwell@mail.wvu.edu or maxwellgeospatial@gmail.com

Phone: (304) 293-2026


Brooks Hall Room 141

West Virginia University

My interests include:


Spatial analysis

Image classification

Object-based image analysis

Machine learning

Geospatial education

Education through travel


I am currenlty an Assistant Professor of Geography in the Department of Geology and Geography at West Virginia University. I teach mainly geospatial and physical geography courses for both undergraduates and graduates. 


Prior to coming to West Virginia University, I was an Assistant Professor at Alderson Broaddus University. As AB is primarily a teaching institution, I taught a wide variety of coursework related to GIS/remote sensing, environmental science, and geology.

Prior to teaching, I worked as a Remote Sensing Analyst at the Natural Resource Analysis Center (NRAC) at West Virginia University. There I was tasked with mapping and geospatial modeling tasks related to natural resource management. 


I am a graduate of Alderson Broaddus where I received bachelor degrees in biology, chemistry, and environmental science. I then attended West Virginia University where I earned a master degree in geology followed by a PhD in geology. I also hold a geographic information systems professional (GISP) certification from the GIS Certification Institute.


I am a native of West Virginia. I grew up in Preston County, where my parents still live. I have a twin sister, who is a school teacher in Morgantown, WV and a younger brother, who is a software engineer in Charleston, WV. 

My research interests include land cover mapping, machine learning, LiDAR, image analysis, geomorphology, and landscape change. I am also very interested in geospatial education and effective teaching techniques.

Current Research Projects
  • Statewide object-based land cover mapping in West Virginia

  • Mapping forest types using spectral and terrain data

  • Mapping wetlands with spectral and terrain data using machine learning

  • Modeling fire induced forest canopy loss

  • Slope failure predictions using machine learning

Past Projects

  • Importance of DEM source for wetland mapping

  • Practical considerations when using machine learning for remote sensing image classification

  • Review of NAIP orthophotography for land cover mapping

  • Land cover mapping of Preston County, WV using object-based image analysis, mulitple data sets, and machine learning

  • Land cover mapping in the southern coalfields of West Virginia using RapidEye satellite data and LiDAR

  • Mapping forest stand types in the Monongahelia National Forest

  • Wetland topographic probabalistic modeling using random forests

  • Separating mine reclamation from spectrally similar cover types using terrain characteristics