An integrated methodology for estimation of forest fire-loss using geospatial information

Area of Science:

• Forestry
• Remote Sensing
• Geospatial Analysis

Background:

• Wildfires are a global concern, necessitating accurate damage assessment.
• Traditional methods for estimating wildfire losses are often labor-intensive and less precise.
• Advancements in satellite imagery and geospatial datasets offer new possibilities for wildfire analysis.

Purpose of the Study:

• To develop and present a detailed method for estimating wildfire losses using geospatial datasets.
• To apply and validate the proposed method using a case study of the 2005 Kang-Won-Do wildfire in the Republic of Korea.
• To demonstrate the advantages of the proposed method over conventional approaches in terms of accuracy and efficiency.

Main Methods:

• Utilized infrared (IR) aerial images to delineate wildfire-damaged areas.
• Integrated Korean national forest inventory GIS layers for forest type, diameter, age, and canopy density data.
• Employed airborne and ground LIDAR (Light Detection and Ranging) datasets to compute tree heights.
• Calculated stand volumes using tree volume equations (TVE).

Main Results:

• The proposed method estimated the total fire loss at $5.9 million for the case study.
• This estimate is more accurate compared to the conventional approach, which yielded $4.5 million.
• The integration of aerial imagery, LIDAR, and national forest inventory data proved effective.

Conclusions:

• The developed algorithm efficiently estimates fire loss using comprehensive geospatial information.
• The method offers a powerful alternative for wildfire damage assessment, ensuring consistent and comprehensive analysis.
• The use of LIDAR and national forest inventory data significantly reduces the need for extensive fieldwork.