UASsbs - Classifying UAS soil burn severity and scaling up to satellite with Python
June 17, 2024
Classifying UAS soil burn severity and scaling up to satellite with Python
Citation Information
Publication Year | 2024 |
---|---|
Title | UASsbs - Classifying UAS soil burn severity and scaling up to satellite with Python |
DOI | 10.5066/P9LTJQUC |
Authors | Joshua W. Von Nonn |
Product Type | Software Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | Western Geographic Science Center - Main Office |
Related Content
An open-source workflow for scaling burn severity metrics from drone to satellite to support post-fire watershed management
Wildfires are increasing in size and severity across much of the western United States, exposing vulnerable wildland-urban interfaces to post-fire hazards. The Mediterranean chaparral region of Northern California contains many high sloping watersheds prone to hazardous post-fire flood events and identifying watersheds at high risk of soil loss and debris flows is a priority for post-fire response
Authors
Joshua W. Von Nonn, Miguel L. Villarreal, Leonhard Blesius, Jerry D. Davis, Skye C. Corbett
Related Content
An open-source workflow for scaling burn severity metrics from drone to satellite to support post-fire watershed management
Wildfires are increasing in size and severity across much of the western United States, exposing vulnerable wildland-urban interfaces to post-fire hazards. The Mediterranean chaparral region of Northern California contains many high sloping watersheds prone to hazardous post-fire flood events and identifying watersheds at high risk of soil loss and debris flows is a priority for post-fire response
Authors
Joshua W. Von Nonn, Miguel L. Villarreal, Leonhard Blesius, Jerry D. Davis, Skye C. Corbett