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Wildfire Burn Area Modeling in Colorado Using Multi-Layer Perceptron Classification

Wildfire Burn Area Modeling in Colorado Using Multi-Layer Perceptron Classification

Using the Google Earth Engine (GEE) JavaScript API to Examine Wildfire Severity

Team Member:

Mina Wei, Brenner Burkholder

Affiliation:

Clark University

Course:

GEOG296

Team Members:

Mina Wei, Brenner Burkholder

Affiliation:

Clark University

Course:

GEOG296

Project Description:

In the face of intensifying global climate change, wildfire risk modeling and analysis continues to be a vigorous area of research. Fire frequency in the US Mountain West appears to be increasing, so understanding variables that contribute to ignition, intensity and area is critical for preserving human life, conservation planning, and emergency management (Oliveira 2021). Thus, we plan on collecting and analyzing variables related to wildfire risk, as found in the literature and from applied models from organizations. Once we gather core variables of wildfire risk, we will create a categorical risk index; ideally, we will have sufficient time to test different models and variables against a burned-unburned binary image using TerrSet’s Multi-Layer-Perceptron tool.

Google Earth Engine Code:


Contact


please contact me at my email address


Email


Email: minaisweiii@gmail.com