Global and Regional Trends and Drivers of Fire Under Climate Change

Reviews of Geophysics, Journal Year: 2022, Volume and Issue: 60(3)

Published: April 11, 2022

Abstract Recent wildfire outbreaks around the world have prompted concern that climate change is increasing fire incidence, threatening human livelihood and biodiversity, perpetuating change. Here, we review current understanding of impacts on weather (weather conditions conducive to ignition spread wildfires) consequences for regional activity as mediated by a range other bioclimatic factors (including vegetation biogeography, productivity lightning) ignition, suppression, land use). Through supplemental analyses, present stocktake trends in burned area (BA) during recent decades, examine how relates its drivers. Fire controls annual timing fires most regions also drives inter‐annual variability BA Mediterranean, Pacific US high latitude forests. Increases frequency extremity been globally pervasive due 1979–2019, meaning landscapes are primed burn more frequently. Correspondingly, increases ∼50% or higher seen some extratropical forest ecoregions including high‐latitude forests 2001–2019, though interannual remains large these regions. Nonetheless, can override relationship between weather. For example, savannahs strongly patterns fuel production fragmentation naturally fire‐prone agriculture. Similarly, tropical relate deforestation rates degradation than changing Overall, has reduced 27% past two part decline African savannahs. According models, prevalence already emerged beyond pre‐industrial Mediterranean change, emergence will become increasingly widespread at additional levels warming. Moreover, several major wildfires experienced years, Australian bushfires 2019/2020, occurred amidst were considerably likely Current models incompletely reproduce observed spatial based their existing representations relationships controls, historical vary across models. Advances observation controlling supporting addition optimization processes exerting upwards pressure intensity weather, this escalate with each increment global Improvements better interactions climate, extremes, humans required predict future mitigate against consequences.

Language: Английский

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Reviews and syntheses: Arctic fire regimes and emissions in the 21st century

Biogeosciences, Journal Year: 2021, Volume and Issue: 18(18), P. 5053 - 5083

Published: Sept. 15, 2021

Abstract. In recent years, the pan-Arctic region has experienced increasingly extreme fire seasons. Fires in northern high latitudes are driven by current and future climate change, lightning, fuel conditions, human activity. this context, conceptualizing parameterizing Arctic regimes will be important for land management as well understanding predicting emissions. The objectives of review were policy questions identified Monitoring Assessment Programme (AMAP) Working Group posed to its Expert on Short-Lived Climate Forcers. This synthesizes changing boreal regimes, particularly activity response change have consequences Council states aiming mitigate adapt north. conclusions from our synthesis following. (1) Current fires, adjacent region, natural (i.e. lightning) human-caused ignition sources, including fires caused timber energy extraction, prescribed burning landscape management, tourism activities. Little is published scientific literature about cultural Indigenous populations across pan-Arctic, remain source ignitions above 70∘ N Russia. (2) expected make more likely increasing likelihood weather, increased lightning activity, drier vegetative ground conditions. (3) To some extent, shifting agricultural use forest transitions forest–steppe steppe, tundra taiga, coniferous deciduous a warmer may increase decrease open biomass burning, depending addition climate-driven biome shifts. However, at country scales, these relationships not established. (4) black carbon PM2.5 emissions wildfires 50 65∘ larger than anthropogenic sectors residential combustion, transportation, flaring. Wildfire 2010 2020, 60∘ N, with 56 % 2020 attributed – indicating how wildfire season was severe seasons can potentially be. (5) What works zones prevent fight work Arctic. Fire need climate, economic development, local communities, fragile ecosystems, permafrost peatlands. (6) Factors contributing uncertainty quantifying include underestimation satellite systems, lack agreement between Earth observations official statistics, still needed refinements location, previous return intervals peat landscapes. highlights that much research order understand regional impacts regime global communities.

Language: Английский

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Towards an Integrated Approach to Wildfire Risk Assessment: When, Where, What and How May the Landscapes Burn

Fire, Journal Year: 2023, Volume and Issue: 6(5), P. 215 - 215

Published: May 22, 2023

This paper presents a review of concepts related to wildfire risk assessment, including the determination fire ignition and propagation (fire danger), extent which may spatially overlap with valued assets (exposure), potential losses resilience those (vulnerability). is followed by brief discussion how these can be integrated connected mitigation adaptation efforts. We then operational systems in place various parts world. Finally, we propose an system being developed under FirEUrisk European project, as example different components (including danger, exposure vulnerability) generated combined into synthetic indices provide more comprehensive but also consider where on what variables reduction efforts should stressed envisage policies better adapted future regimes. Climate socio-economic changes entail that wildfires are becoming even critical environmental hazard; extreme fires observed many areas world regularly experience fire, yet activity increasing were previously rare. To mitigate negative impacts responsible for managing must leverage information available through assessment process, along improved understanding targeted improve optimize strategies risk.

Language: Английский

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A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management

Information Fusion, Journal Year: 2024, Volume and Issue: 108, P. 102369 - 102369

Published: March 22, 2024

Wildfires have emerged as one of the most destructive natural disasters worldwide, causing catastrophic losses. These losses underscored urgent need to improve public knowledge and advance existing techniques in wildfire management. Recently, use Artificial Intelligence (AI) wildfires, propelled by integration Unmanned Aerial Vehicles (UAVs) deep learning models, has created an unprecedented momentum implement develop more effective Although survey papers explored learning-based approaches wildfire, drone disaster management, risk assessment, a comprehensive review emphasizing application AI-enabled UAV systems investigating role methods throughout overall workflow multi-stage including pre-fire (e.g., vision-based vegetation fuel measurement), active-fire fire growth modeling), post-fire tasks evacuation planning) is notably lacking. This synthesizes integrates state-of-the-science reviews research at nexus observations modeling, AI, UAVs - topics forefront advances elucidating AI performing monitoring actuation from pre-fire, through stage, To this aim, we provide extensive analysis remote sensing with particular focus on advancements, device specifications, sensor technologies relevant We also examine management approaches, monitoring, prevention strategies, well planning, damage operation strategies. Additionally, summarize wide range computer vision emphasis Machine Learning (ML), Reinforcement (RL), Deep (DL) algorithms for classification, segmentation, detection, tasks. Ultimately, underscore substantial advancement modeling cutting-edge UAV-based data, providing novel insights enhanced predictive capabilities understand dynamic behavior.

Language: Английский

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Canadian forests are more conducive to high-severity fires in recent decades

Science, Journal Year: 2025, Volume and Issue: 387(6729), P. 91 - 97

Published: Jan. 2, 2025

Canada has experienced more-intense and longer fire seasons with more-frequent uncontrollable wildfires over the past decades. However, effect of these changes remains unknown. This study identifies driving forces burn severity estimates its spatiotemporal variations in Canadian forests. Our results show that fuel aridity was most influential driver severity, summer months were more prone to severe burning, northern areas influenced by changing climate. About 6% (0.54 14.64%) modeled significant increases number days conducive high-severity burning during 1981 2020, which found 2001 2020 spring autumn. The extraordinary 2023 season demonstrated similar spatial patterns but more-widespread escalations severity.

Language: Английский

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Fifty years of wildland fire science in Canada

Canadian Journal of Forest Research, Journal Year: 2020, Volume and Issue: 51(2), P. 283 - 302

Published: Nov. 5, 2020

We celebrate the 50th anniversary of Canadian Journal Forest Research by reflecting on considerable progress accomplished in select areas wildland fire science over past half century. Specifically, we discuss key developments and contributions creation Fire Danger Rating System; relationships between weather, climate, climate change; ecology; operational decision support; management. also evolution management Banff National Park as a case study. conclude discussing some possible directions future research including further evaluation severity measurements effects; efficacy fuel treatments; change effects mitigation; refinement models pertaining to risk analysis, behaviour, weather; integration forest ecological restoration with reduction. Throughout paper, reference many published Research, which has been at forefront international science.

Language: Английский

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The right to burn: barriers and opportunities for Indigenous-led fire stewardship in Canada

FACETS, Journal Year: 2022, Volume and Issue: 7, P. 464 - 481

Published: Jan. 1, 2022

Indigenous fire stewardship enhances ecosystem diversity, assists with the management of complex resources, and reduces wildfire risk by lessening fuel loads. Although Peoples have maintained practices for millennia continue to be keepers knowledge, significant barriers exist re-engaging in cultural burning. communities Canada unique vulnerabilities large high-intensity wildfires as they are predominately located remote, forested regions lack financial support at federal provincial levels mitigate risk. Therefore, it is critical uphold expertise leading effective socially just stewardship. In this perspective, we demonstrate benefits burning identify five key advancing Canada. We also provide calls action assist reducing preconceptions misinformation focus on creating space respect different knowledges experiences. Despite growing concerns over agency-stated intentions establish partners management, power imbalances still exist. The future coexistence needs a shared responsibility led within their territories.

Language: Английский

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FFYOLO: A Lightweight Forest Fire Detection Model Based on YOLOv8

Fire, Journal Year: 2024, Volume and Issue: 7(3), P. 93 - 93

Published: March 16, 2024

Forest is an important resource for human survival, and forest fires are a serious threat to protection. Therefore, the early detection of fire smoke particularly important. Based on manually set feature extraction method, accuracy machine learning method limited, it unable deal with complex scenes. Meanwhile, most deep methods difficult deploy due high computational costs. To address these issues, this paper proposes lightweight model based YOLOv8 (FFYOLO). Firstly, in order better extract features smoke, channel prior dilatation attention module (CPDA) proposed. Secondly, mixed-classification head (MCDH), new head, designed. Furthermore, MPDIoU introduced enhance regression classification model. Then, Neck section, GSConv applied reduce parameters while maintaining accuracy. Finally, knowledge distillation strategy used during training stage generalization ability false detection. Experimental outcomes demonstrate that, comparison original model, FFYOLO realizes mAP0.5 88.8% custom dataset, which 3.4% than 25.3% lower 9.3% higher frames per second (FPS).

Language: Английский

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Wildfire Susceptibility Mapping in Baikal Natural Territory Using Random Forest

Forests, Journal Year: 2024, Volume and Issue: 15(1), P. 170 - 170

Published: Jan. 13, 2024

Wildfires are a significant problem in Irkutsk Oblast. They caused by climate change, thunderstorms, and human factors. In this study, we use the Random Forest machine learning method to map wildfire susceptibility of Oblast based on data from remote sensing, meteorology, government forestry authorities, emergency situations. The main contributions paper following: an improved domain model that describes information about weather conditions, vegetation type, infrastructure region context possible risk wildfires; database wildfires 2017 2020; results analysis factors cause assessment form fire hazard mapping. paper, collected visualized influencing their occurrence: meteorological, topographic, characteristics vegetation, activity (social factors). Data sets describing two classes, “fire” “no fire”, were generated. We introduced classification according which probability each specific cell territory can be determined built. allowed us achieve following accuracy indicators: accuracy—0.89, F1-score—0.88, AUC—0.96. comparison with earlier ones obtained using case-based reasoning revealed application approach considered initial stage for deeper investigations more accurate forecasting.

Language: Английский

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Forest fire management and fire suppression strategies: a systematic literature review

Natural Hazards, Journal Year: 2025, Volume and Issue: unknown

Published: March 17, 2025

Language: Английский

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