John S. Hogland, PhD

Treesearch Publications

• Fredrick Bunt, Jesse Johnson, John S. Hogland. 2026. Raster Tools: An open source toolbox for raster processing
• John S. Hogland. 2026. AI in forestry—Raster Tools integrates machine learning and geospatial analysis at scale
• Annabelle Moore, John S. Hogland. 2026. Raster Tools: Leveraging spatial analysis and AI towards a fire-resilient future, in minutes
• Lindsay Wiard-Greene, Jesse Johnson, John S. Hogland, Fredrick Bunt, Jake Bova. 2025. Investigating the impact of aerial firefighting on rate of wildfire spread
• Melissa Reynolds-Hogland, Carly Brooks, Alan B. Ramsey, John S. Hogland, Kristine L. Pilgrim, Cory L. Engkjer, Philip W. Ramsey. 2024. Long-term video and genetic data yield insights into complex sociality of a solitary large carnivore
• Jesse V. Johnson, Anthony Marcozzi, Frederick Bunt, Jacob Bova, John S. Hogland. 2022. Predicting fire severity in Montana using a random forest classification scheme
• Fredrick Bunt, Jesse V. Johnson, John S. Hogland. 2022. A platform for large scale application of remote sensed data to wildland fire management
• Nathaniel Anderson, John S. Hogland. 2022. Resources to improve the efficiencies of forest operations
• Andrea Watts, Nathaniel Anderson, Woodam (Woody) Chung, John S. Hogland, Robert Keefe, Ryer Becker, John Twitchell. 2022. There’s more to harvesting than green timber and sawlogs: Engineering forest operations for 21st-century forest management
• John S. Hogland, David L. R. Affleck. 2021. Improving estimates of natural resources using model-based estimators: Impacts of sample design, estimation technique, and strengths of association
• John S. Hogland, Christopher J. Dunn, James D. Johnston. 2021. 21st century planning techniques for creating fire-resilient forests in the American West
• John S. Hogland, David L. R. Affleck, Nathaniel Anderson, Carl Seielstad, Solomon Dobrowski, Jon Graham, Robert Smith. 2020. Estimating forest characteristics for longleaf pine restoration using normalized remotely sensed imagery in Florida USA
• Palaiologos Palaiologou, Maureen Essen, John S. Hogland, Kostas Kalabokidis. 2020. Locating forest management units using remote sensing and geostatistical tools in North-Central Washington, USA
• John S. Hogland, Nathaniel Anderson. 2019. The big picture: New perspectives on restoring landscapes
• Matthew P. Thompson, Yu Wei, Dave E. Calkin, Christopher D. O'Connor, Christopher Dunn, Nathaniel Anderson, John S. Hogland. 2019. Risk management and analytics in wildfire response
• John S. Hogland, Nathaniel Anderson, David Affleck, Joseph St. Peter. 2019. Using forest inventory data with Landsat 8 imagery to map longleaf pine forest characteristics in Georgia, USA
• John S. Hogland, David L. R. Affleck. 2019. Mitigating the impact of field and image registration errors through spatial aggregation
• Robert Ahl, John S. Hogland, Steve Brown. 2019. A comparison of standard modeling techniques using digital aerial imagery with national elevation datasets and airborne LiDAR to predict size and density forest metrics in the Sapphire Mountains MT, USA
• Joseph St. Peter, John S. Hogland, Mark Hebblewhite, Mark A. Hurley, Nicole Hupp, Kelly Proffitt. 2018. Linking phenological indices from digital cameras in Idaho and Montana to MODIS NDVI
• Joseph St. Peter, John S. Hogland, Nathaniel Anderson, Jason Drake, Paul Medley. 2018. Fine resolution probabilistic land cover classification of landscapes in the southeastern United States
• John S. Hogland, Nathaniel Anderson, Joseph St. Peter, Jason Drake, Paul Medley. 2018. Mapping forest characteristics at fine resolution across large landscapes of the southeastern United States using NAIP imagery and FIA field plot data
• John S. Hogland, Nathaniel Anderson, Woodam Chung. 2018. New geospatial approaches for efficiently mapping forest biomass logistics at high resolution over large areas
• John S. Hogland, Nathaniel Anderson. 2017. Function modeling improves the efficiency of spatial modeling using big data from remote sensing
• Lucas A. Wells, Woodam Chung, Nathaniel Anderson, John S. Hogland. 2016. Spatial and temporal quantification of forest residue volumes and delivered costs
• John S. Hogland, Nathaniel Anderson. 2015. Estimating FIA plot characteristics using NAIP imagery, function modeling, and the RMRS raster utility coding library
• John S. Hogland, Nathaniel Anderson. 2015. Estimating FIA plot characteristics using NAIP imagery, function modeling, and the RMRS Raster Utility coding library
• Sue Miller, Maureen Essen, Nathaniel Anderson, Woody Chung, William J. Elliot, Deborah S. Page-Dumroese, Han-Sup Han, John S. Hogland, Christopher R. Keyes. 2014. Burgeoning biomass: Creating efficient and sustainable forest biomass supply chains in the Rockies
• Robert Keefe, Nathaniel Anderson, John S. Hogland, Ken Muhlenfeld. 2014. Woody biomass logistics [Chapter 14]
• John S. Hogland, Nathaniel Anderson, Woodam Chung, Lucas Wells. 2014. Estimating forest characteristics using NAIP imagery and ArcObjects
• John S. Hogland, Nathaniel Anderson. 2014. Improved analyses using function datasets and statistical modeling
• John S. Hogland, Nedret Billor, Nathaniel Anderson. 2013. Comparison of standard maximum likelihood classification and polytomous logistic regression used in remote sensing
• John S. Hogland, Nathaniel Anderson, Greg G. Jones. 2013. Function modeling: improved raster analysis through delayed reading and function raster datasets

Data and Tools

• Tool
  

  Fire Resilient Landscapes - Raster Tools

  https://research.fs.usda.gov/rmrs/products/dataandtools/fire-resilient-landscapes-raster-tools
• Decision Support System
  

  Raster Tools

  https://research.fs.usda.gov/rmrs/products/dataandtools/raster-tools
• Tool
  

  RMRS Raster Utility

  https://research.fs.usda.gov/rmrs/products/dataandtools/rmrs-raster-utility

• Program
  

  Human Dimensions

  https://research.fs.usda.gov/rmrs/programs/humandimensions
  Station

  Rocky Mountain Research Station
• Project
  

  Wildfire risk reduction in priority firesheds using Potential Operational Delineations (PODs)

  https://research.fs.usda.gov/rmrs/projects/bil-wildfire-risk-reduction-priority-firesheds-using-potential-operational
  Station

  Rocky Mountain Research Station
• Project
  

  FastFuels: 3D Fuels for Next Generation Fire Models

  https://research.fs.usda.gov/firelab/projects/fastfuels
• Center or Group
  

  Wildfire Risk Management Science Team

  https://research.fs.usda.gov/rmrs/centers/wrms
  Station

  Rocky Mountain Research Station

Articles

• Article
  

  New science-based model helps forest managers target fuels treatments where they make the most sense

  https://research.fs.usda.gov/rmrs/articles/new-science-based-model-helps-forest-managers-target-fuels-treatments-where-they-make

Multimedia

• Video

  Meet John Hogland: Forest Service Researcher

  https://research.fs.usda.gov/rmrs/products/multimedia/videos/meet-john-hogland-forest-service-researcher
• Webinars
  

  Wildfire and resilient landscapes: New tools for detailed analyses

  https://research.fs.usda.gov/rmrs/products/multimedia/webinars/wildfire-and-resilient-landscapes-new-tools-detailed-analyses

• University of Montana, Ph.D, Forestry & Conservation Sciences, 2019
• School of Forestry and Wildlife Sciences, Auburn University, M.S. Minor Statistics, Forestry, landscape ecology, remote sensing, spatial modeling, and statistices., 2005
• School of Forestry and Wildlife Sciences, Auburn University, B.S., Forest Resources and Spatial Analysis, 2001