To help the U.S. Bureau of Land Management understand the vulnerability to wildfire on 15 of its remote parcels in northeast Minnesota, AES collected aerial imagery, and applied remote sensing and GIS techniques, to generate high-resolution data and GIS models that estimated wildfire vulnerability.
AES flights to collect high-resolution multispectral imagery were strategically timed in October to maximize the diversity of spectral reflection provided by fall colors, thus improving the automated classification of vegetation cover.
Geospatial specialists processed data into four spectral bands (red, green, blue, and near infrared) stacked as one data layer to further refine the classification of land cover and assist with interpreting vegetation community types, such as deciduous forest, grassland, herbaceous wetland, etc.
Using the aerial imagery data, AES developed a GIS-based wildfire vulnerability model comprised of three interrelated parts: 1) potential fuel source for ignition (ignition potential model); 2) potential fuel load of vegetation cover; and 3) connectivity between ignition sources and fuel loads.
The final report to BLM provided a Wildfire Vulnerability Score for each parcel and its adjacent half-mile perimeter buffer.
- Remote Sensing + Analysis
- Aerial Imagery
- GIS Modeling
- Land/Vegetation Classification
BLM Wildfire Vulnerability Study