ACTIVE DATE
2019-2021
PROJECT TYPE
PHASE II
CLIENT / PARTNER
AFIMSC
Project Summary
The goal of this project was to provide the Air Force with a Proof-of-Concept for an automated and inexpensive methodology for early detection of tree disease outbreaks, including bark beetles, across thousands of forested acres at bases across the country.
This enables targeting and mitigation of disease outbreaks before large areas of trees begin to die, thus helping to control wildfires, mudslides, and flooding.
Completed as part of USAF SBIR Phase II (2019 – 2021). Reducing cost and time for environmental monitoring with machine learning.
PROJECT DETAILS
- Collected UAV-based hyperspectral and multispectral imagery at the USAF Academy in Colorado Springs.
- Collected reference data composed of trees in various stages of health.
- Trained random forest model to automatically identify healthy, stressed, and dying trees.
- Can be used with newly collected imagery for automated forest management.
L: Collecting Ground Control Points in Colorado with Mapware (formerly Aerial Applications) team members
R: Setting up the hyperspectral sensor before flight
L: The field team
R: Collecting imagery in Colorado
L: Technical workflow summary
R: Final classified hyperspectral maps at our two study areas
