2023 Hawaii Wildfire Cost-Effective Rapid Wildfire Analysis

Team member: Zongrong Li, Qiluo Li, Haiyang Li

This project presents a detailed analysis of the 2023 wildfires in Hawaii, particularly focusing on Maui Island, with the goal of developing a cost-effective and efficient wildfire assessment model.

Methodology: three-tiered approach, initiating with broad-scale fire detection using high-frequency FIRMS data at approximately 1-kilometer resolution. It then progresses to a more refined analysis using high-resolution Sentinel 2 data (20-meter resolution with a five-day revisit cycle) and Planet data (3-meter resolution), specifically targeting the evaluation of vegetation cover impact, employing the NDVI index for accurate and timely updates.

key advantages:

  • Integration of public and commercial satellite data ensures comprehensive coverage and targeted, cost-effective analysis.  
  • The combination of high-frequency and high-resolution data enables continuous monitoring and precise assessment of wildfire impacts.

The link of storymap: https://arcg.is/KOiqr0

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Zongrong(Jasper) Li
Student at USC

I am seeking a Ph.D. position that combines machine learning, GIS, and their applications in economics and finance.

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