Raster Tools
Raster Tools is a python package that facilitates a wide range of spatial, statistical, machine learning analyses using delayed and automated parallel processing. Our library focuses on significantly reducing processing time and storage space associated with analyzing large spatial datasets while also introducing new spatial, statistical, machine learning concepts into an easy-to-use python based API.
Applicability and Overview
Key Uses
Fire
Scale
Mid-Scale
User Experience Level
Advanced
What do you need to get started?
A background in geospatial, statistics, machine learning, and scripting
Outputs
Raster, vector, machine learning surfaces, models, reports, and visualizations
Strengths
It can be used to inform decision making in a spatially explicit manner.
Limitations
It requires advanced knowledge and scripting skills.
Online Resources
People
- Person
John S. Hogland, PhD
Research Foresterhttps://research.fs.usda.gov/about/people/john.s.hogland
Related Data and Tools
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Tool
https://research.fs.usda.gov/rmrs/products/dataandtools/fire-resilient-landscapes-raster-tools
Webinars
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Webinars
https://research.fs.usda.gov/rmrs/products/multimedia/webinars/wildfire-and-resilient-landscapes-new-tools-detailed-analyses
Related Programs
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Center or Group
https://research.fs.usda.gov/rmrs/centers/wrmsStation -
Program
https://research.fs.usda.gov/rmrs/programs/humandimensionsStation
Science Summaries
- Annabelle Moore, John S. Hogland. 2026. Raster Tools: Leveraging spatial analysis and AI towards a fire-resilient future, in minutes
Publications
- Nathaniel Anderson, John S. Hogland. 2022. Resources to improve the efficiencies of forest operations
- John S. Hogland, Nathaniel Anderson. 2017. Function modeling improves the efficiency of spatial modeling using big data from remote sensing
Last updated May 7, 2026