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Non-additive effects of leaf-litter flammability on eight subtropical tree species: Implications for forest species composition and fire susceptibility.
J Environ Manage
January 2025
Department of Forestry, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan, 430070, Hubei, China. Electronic address:
The readiness of leaf-litter to burn in the presence of fire differs greatly between species. Thus, forests composed of different species vary in their susceptibility to fire. Fire susceptibility of forests may also differ from the arithmetic means of flammability of their component species, i.
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Universidade Federal de São Paulo, Departamento de Pediatria - Disciplina de Alergia, Imunologia Clínica e Reumatologia, São Paulo, Brazil.
Objective: Air pollution emission associated with wildfires is a global concern, contributing to air quality deterioration and severely impacting public health. This narrative review aims to provide an overview of wildfire smoke (WFS) characteristics and associated impacts on adults' and children's health.
Data Source: Literature review based on a bibliographic survey in PubMed (National Library of Medicine, United States), SciELO (Scientific Electronic Library Online), and Google Scholar databases.
Iterative smoothing for change-point regression function estimation.
J Appl Stat
May 2024
Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia, Kelowna, British Columbia, Canada.
Understanding wildfire spread in Canada is critical to promoting forest health and protecting human life and infrastructure. Quantifying fire spread from noisy images, where change-point boundaries separate regions of fire, is critical to accurately estimating fire spread rates. The challenge lies in denoising the fire images and accurately identifying highly non-linear fire lines without smoothing over boundaries.
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PNAS Nexus
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Department of Economics and Finance, University of Rome "Tor Vergata", Rome 00133, Italy.
This study uses Earth observation data to measure illegal activities and investigates possible relationships with local governments. We have collected satellite images, digital maps, and geospatial data for over a decade to detect potential illegal constructions in protected burned forest areas in Sardinia, Italy. We create a database of buildings erected in these protected areas and connect it to administrative data on local election results.
View Article and Find Full Text PDFWildfire spread prediction using geostationary satellite observation data and directional ROS adjustment factor.
J Environ Manage
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Department of Civil and Environmental Engineering, Seoul National University, Seoul, South Korea. Electronic address:
Article Synopsis
- This paper presents a new data-driven method to boost the accuracy of wildfire spread predictions using satellite wildfire detection data.
- It introduces an improved algorithm that uses a genetic algorithm to optimize the Rate of Spread (ROS) adjustment factor, making predictions more precise in the FARSITE wildfire simulator.
- The methodology, tested during the 2020 Creek Fire in California, shows that the innovative Directional ROS approach outperforms traditional methods, aiding in better wildfire response strategies and resource allocation.
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