Accession Number:

AD1173498

Title:

A Spatial-Temporal Point Process Model for Estimating Probability of Wildfires in Los Angeles County

Descriptive Note:

[Technical Report, Master's Thesis]

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

• Yi, Wook

Report Date:

2022-03-01

Pagination or Media Count:

59

Abstract:

In Los Angeles County, wildfires are among the most catastrophic environmental events caused by regional characteristics and climate change. In this study, we develop a point process model to estimate the probability of wildfires based on historical weather data and past wildfires data from Los Angeles County from 2004 to 2018. First, we partition Los Angeles County into small rectangular regions, called voxels, with daily temporal resolution. Then, we use random forests and generalized additive models to obtain estimated probabilities on a training data set. In addition to daily weather and fuel-condition measurements, our models incorporate seasonal and geographical effects. Because measurements on weather and fuel conditions are available only from a fixed set of remote automated weather stations, their data must be averaged to relate them to the voxel level, and the way this is done is a factor in modeling. Through the developed model, it is possible to obtain localized, estimated probabilities of wildfires. Ultimately, this tool can aid Los Angeles County Fire Department in improving its capability and effectiveness.

Descriptors:

• data sets
• operations research
• probability
• weather stations
• additives (chemicals)
• climate change
• fires
• machine learning
• training
• warning systems
• forest fires
• information science
• literature surveys
• test sets
• wildfires
• air force
• data analysis

Subject Categories:

• Meteorology
• Forestry

Distribution Statement:

[A, Approved For Public Release]