Research on a Random Forest Regression Model for Climate Prediction in the Context of Wildfires

Junru Lou

2025

Abstract

Until now, research has sometimes used the survivorship curves which is generated by statistics on tree age to estimate the fire frequency. However, due to the infrequency of fires, it is hard to infer the existing woodland studies about he relationship between fire occurrence and extent and short-term climate change. This paper has an in-depth analysis of the quantitative relationship between fire size and greenhouse gas emissions with the integrating global fire scale data, greenhouse gas emissions data and global temperature change data. Random forest regression algorithm is used on this research and supports the analysis of the quantitative relationship between fire size and greenhouse gas emissions. At last, the emission levels of greenhouse gases will be analyzed, and the impact of greenhouse gas emissions on global warming will be discussed. This paper has a goal of building a prediction model based on the wildfire burning scale. It will be used to predict the level of impact on global warming. It is expected here to provide new insights into the mechanisms of global climate change and provide a scientific basis for formulating effective environmental protection and fire management policies.

Paper Citation

in Harvard Style

Lou J. (2025). Research on a Random Forest Regression Model for Climate Prediction in the Context of Wildfires. In Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE; ISBN 978-989-758-765-8, SciTePress, pages 392-399. DOI: 10.5220/0013698100004670

in Bibtex Style

@conference{icdse25,
author={Junru Lou},
title={Research on a Random Forest Regression Model for Climate Prediction in the Context of Wildfires},
booktitle={Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE},
year={2025},
pages={392-399},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013698100004670},
isbn={978-989-758-765-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE
TI - Research on a Random Forest Regression Model for Climate Prediction in the Context of Wildfires
SN - 978-989-758-765-8
AU - Lou J.
PY - 2025
SP - 392
EP - 399
DO - 10.5220/0013698100004670
PB - SciTePress