Earth and Environmental Sciences Poster Session

Title

A Multi-Criteria Approach to Identify Areas at Risk to Megafires in Mendocino National Forest, California

Presenter Information

Logan McGowanFollow

Academic Level at Time of Presentation

Junior

Major

Earth & Environmental Science/ Geography & GIS

List all Project Mentors & Advisor(s)

Dr. Haluk Cetin

Presentation Format

Poster Presentation

Abstract/Description

A Multi-Criteria Approach to Identify Areas at Risk to Megafires in Mendocino National Forest, California

Due to Anthropogenic climate change, wildfire behavior has changed drastically across the world. These “Megafires” (wildfires that burn 100,000 acres or more) are more frequent and intense in their behavior than ever (Weber & Yadav, 2020). Planning and mitigation of wildfire hazards are an important step in protecting economic assets, ecosystems, and most importantly humans. A Geographic Information System (GIS) is a key component for modeling spatial and temporal behaviors in wildfire. Previous studies have used similar techniques for creating fire risk models. However, more research on the validity of these models is needed. This project used the combination of GIS, remotely sensed imagery, and historical wildfire data to create a fire risk and susceptibility model. Multiple variables were selected to model fire risk. These variables include aspect, climate, elevation, slope, fuels (land cover), and historical data interpolation (Burapapol & Nagasawa, 2017). Landsat 8 and National Agriculture Imagery Program (NAIP) imagery was used in a stratified random sample for the study areas in Mendocino National Forest in California, United States. Furthermore, historical wildfire data from the study area were utilized as calibration and validation to the types of fire risk. In the GIS the variables were put into the calculation as follows: Fire risk = (Aspect + Climate + Elevation + Slope + Land cover). The result of the calculation was then reclassified to delineate high, moderate, or low risk for wildfires based on the criteria. Initial results of the Multi-Criteria Fire Risk Model (MCFRM) provided details of the risk level in acres. The results revealed areas in the low risk level at 34,525.09 acres, approximately 22% of the study area. Areas in the moderate risk level were measured at 100,436.63 acres, approximately 64% of the study area. Finally, areas in the high-risk level were measured at 15,693.22 acres, approximately 10% of the study area. As a result, the study area has a moderate risk for a “Megafire”. The Multi-Criteria Fire Risk Model and similar models are helpful for wildland firefighters, fire managers, politicians, citizens, and much more for a better understanding of areas at risk to wildfires.

Keywords: GIS, megafires, wildfires.

Location

Waterfield Gallery

Start Date

November 2021

End Date

November 2021

Fall Scholars Week 2021 Event

EES Poster Session

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Nov 19th, 1:30 PM Nov 19th, 3:30 PM

A Multi-Criteria Approach to Identify Areas at Risk to Megafires in Mendocino National Forest, California

Waterfield Gallery

A Multi-Criteria Approach to Identify Areas at Risk to Megafires in Mendocino National Forest, California

Due to Anthropogenic climate change, wildfire behavior has changed drastically across the world. These “Megafires” (wildfires that burn 100,000 acres or more) are more frequent and intense in their behavior than ever (Weber & Yadav, 2020). Planning and mitigation of wildfire hazards are an important step in protecting economic assets, ecosystems, and most importantly humans. A Geographic Information System (GIS) is a key component for modeling spatial and temporal behaviors in wildfire. Previous studies have used similar techniques for creating fire risk models. However, more research on the validity of these models is needed. This project used the combination of GIS, remotely sensed imagery, and historical wildfire data to create a fire risk and susceptibility model. Multiple variables were selected to model fire risk. These variables include aspect, climate, elevation, slope, fuels (land cover), and historical data interpolation (Burapapol & Nagasawa, 2017). Landsat 8 and National Agriculture Imagery Program (NAIP) imagery was used in a stratified random sample for the study areas in Mendocino National Forest in California, United States. Furthermore, historical wildfire data from the study area were utilized as calibration and validation to the types of fire risk. In the GIS the variables were put into the calculation as follows: Fire risk = (Aspect + Climate + Elevation + Slope + Land cover). The result of the calculation was then reclassified to delineate high, moderate, or low risk for wildfires based on the criteria. Initial results of the Multi-Criteria Fire Risk Model (MCFRM) provided details of the risk level in acres. The results revealed areas in the low risk level at 34,525.09 acres, approximately 22% of the study area. Areas in the moderate risk level were measured at 100,436.63 acres, approximately 64% of the study area. Finally, areas in the high-risk level were measured at 15,693.22 acres, approximately 10% of the study area. As a result, the study area has a moderate risk for a “Megafire”. The Multi-Criteria Fire Risk Model and similar models are helpful for wildland firefighters, fire managers, politicians, citizens, and much more for a better understanding of areas at risk to wildfires.

Keywords: GIS, megafires, wildfires.