Fires are a growing concern, especially in regions with longer fire seasons, expanded wildland/urban interfaces, and severe and frequent droughts. Anthropogenic fires are commonly used to clear grassland and agricultural land prior to the planting season, and forests are often cleared using fires so the land can be repurposed for other uses. Whether naturally-occurring or anthropogenic, fires produce a significant change in the structure and reflectance of vegetation and soil properties and atmospheric chemistry. Remote sensing can be used to monitor pre-, during-, and post-fire conditions; including weather and climate conditions, fuel characterization, fire risk, smoke detection, monitoring, and forecasting, fire behavior, and the post-fire landscape. This 6-part, intermediate training will provide lectures and case studies focused on the use of Earth observations for operational fire monitoring: pre-, during-, and post-event.
The online training will be into six parts and two seperate sessions, which take place at different times. Each session will be two hours long. The Fundamentals of Remote Sensing training and the Introduction to Remote Sensing for Wildfire Applications training are advised prerequisites. The first session will be conducted in English and the second session will conducted be in Spanish.
The online training will take place on May 11th, 13th, 18th, 20th, 25th, & 27th, 2021.
- The first session will be offered from 11:00 am - 01:00 pm EDT (English)
- The second session will be offered from 3:00 pm - 5:00 pm EDT (Spanish)
By the end of this training attendees will understand:
- Terminology regarding type and components of fire (pre, during, post)
- Climatic and biophysical conditions pre-, during-, and post-fire
- The satellites and instruments used in conducting fire science
- The applications of passive and active remote sensing for fires
- How to visualize fire emissions and particulate matter
- The use of tools for active fires, emissions, and burned areas
- How to acquire data for conducting analysis in a given study area