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Analyzing Wildfire Patterns in Colorado, Montana, Utah, and Wyoming Using Spatio-Temporal Methods

Abstract Number:

1444 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Poster 

Participants:

Princess Tagoe (1), Mostafa Zahed (2)

Institutions:

(1) N/A, N/A, (2) East Tennessee State University, N/A

Co-Author:

Mostafa Zahed  
East Tennessee State University

First Author:

Princess Tagoe  
N/A

Presenting Author:

Princess Tagoe  
N/A

Abstract Text:

In recent times, wildfires have posed significant threats to forest ecosystems, human communities, and economic assets. This study applies spatio-temporal techniques to analyze and predict wildfire patterns in the forests of Colorado, Montana, Utah, and Wyoming. Utilizing historical wildfire data, weather conditions, vegetation types, and topographic features, we aim to develop comprehensive models to identify high-risk areas and forecast future wildfire events. By integrating remote sensing data and geographic information systems (GIS), we perform detailed spatio-temporal analyses to uncover underlying patterns and trends. The findings from this research provide valuable insights for forest management, risk assessment, and wildfire mitigation strategies, contributing to more effective resource allocation and community preparedness.

Keywords:

Spatio-temporal analysis|Wildfire patterns|Forest Ecosystems|Risk assessment|Predictive modeling|Remote sensing

Sponsors:

Section on Statistical Computing

Tracks:

Computationally Intensive Methods

Can this be considered for alternate subtype?

Yes

Are you interested in volunteering to serve as a session chair?

No

I have read and understand that JSM participants must abide by the Participant Guidelines.

Yes

I understand that JSM participants must register and pay the appropriate registration fee by June 3, 2025. The registration fee is non-refundable.

I understand