AI-Driven Wildfire Prediction and Response in Portugal

Advances in environmental engineering and green technologies book series, Journal Year: 2025, Volume and Issue: unknown, P. 115 - 144

Published: Jan. 24, 2025

Wildfires increasingly threaten Portugal's ecosystem and population, with climate change intensifying fire seasons. AI has emerged as a powerful tool for predicting responding to wildfires, offering improved accuracy speed over traditional methods. This paper examines AI's role in wildfire management Portugal, focusing on machine learning, image recognition, real-time data analytics, IoT integration. It addresses potential enhance emergency responses, reduce environmental damage, optimize firefighting resources. Case studies, including the Bee2FireDetection system sensor networks, highlight impact, concluding strategic recommendations future AI-driven mitigation Portugal.

Language: Английский

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Floristic Morpho-Ecological Strategies: Methodological Approach to Characterize Robustness of Vegetation

IntechOpen eBooks, Journal Year: 2025, Volume and Issue: unknown

Published: March 19, 2025

Resistance and resilience are usually applied to discuss the functionality of systems, once both describe responses biological units environmental alterations. With this purpose, an analytical methodology focused on description functional vegetation, their potential correlation with matrices, was elaborated in present work. Comparison between amplitudes averages morpho-ecological variables, here analyzed by Fluctuation Asymmetries (FAs), fundament methodology, three different areas Portugal similar extensions from north, center, south (designed as MB, CP, FS). The results obtained described very for these study areas. discussion explained them high resistance areas, lower one (CP), recently exposed intensive forest fires. So, robustness will be sustained relevant resistance, where variability (geomorphology climatology) cause associated. In context, increases production pressions higher frequencies fires climate changes trigger significant vegetation. Changes necessary order maintain

Language: Английский

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Spatially explicit assessment of carbon storage and sequestration in forest ecosystems

Remote Sensing Applications Society and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 101544 - 101544

Published: April 1, 2025

Language: Английский

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Coupled Atmosphere–Fire Modelling of Pyroconvective Activity in Portugal

Fire, Journal Year: 2025, Volume and Issue: 8(4), P. 153 - 153

Published: April 10, 2025

This study investigates the physical interactions and between forest fires atmosphere, which often lead to conditions favourable instability formation of pyrocumulus (PyCu). Using coupled atmosphere–fire spread modelling framework, WRF-SFIRE, Portuguese October 2017 Quiaios wildfire, in association with tropical cyclone Ophelia, was simulated. Fire imposed via burnt area data, fire’s influence on vertical surface atmosphere analysed. Simulated local atmospheric were influenced by warm dry air advection near surface, moist mid high levels, displaying an inverted “V” profile thermodynamic diagrams. These created a near-neutrally unstable layer first 3000 m, associated low-level jet above 1000 m. Results showed that wind shear tilted plume, resulting intermittent, high-based, shallow pyroconvection, zero convective available potential energy environment (CAPE). Lifted parcels from fire lost their buoyancy shortly after condensation, presence PyCu governed output its updrafts. Clouds formed lifted condensation level (LCL) as moisture fluxes released combustion along plume. primarily composed liquid water (1 g/kg) smaller traces ice, graupel, snow (up 0.15 g/kg). The representation pyroconvective dynamics models is cornerstone understanding phenomena field applications computation capability increases provides firefighters real time extreme or predicting ahead time.

Language: Английский

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Recovery Following Recurrent Fires Across Mediterranean Ecosystems

Global Change Biology, Journal Year: 2024, Volume and Issue: 30(12)

Published: Dec. 1, 2024

ABSTRACT In fire‐prone regions such as the Mediterranean biome, fire seasons are becoming longer, and fires more frequent severe. Post‐fire recovery dynamics is a key component of ecosystem resilience stability. Even though ecosystems can tolerate high exposure to extreme temperatures recover from fire, changes in climate conditions intensity or frequency might contribute loss increase potential for irreversible vegetation communities. this study, we assess rates burned after recurrent across globally, based on remotely sensed Enhanced Vegetation Index (EVI) data, proxy status, 2001 2022. Recovery quantified through statistical model EVI time‐series. This approach allows resolving time space, overcoming limitations space‐for‐time approaches typically used study remote sensing. We focus pixels burning repeatedly over period evaluate how severity, pre‐fire greenness, post‐fire modulate different types. detect large contrasts between rates, mostly explained by regional differences type. Particularly, needle‐leaved forests tend faster following second event, contrasting with shrublands that first event. Our results also show severity promote forested ecosystems. An important modulating role fuel detected, higher before resulting stronger relative greenness loss. addition, conditions, particularly air temperature precipitation, were found speed all regions, highlighting direct impacts compound anomalies likely destabilise under changing conditions.

Language: Английский

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Exploring Drivers of Wildfires in Spain

Land, Journal Year: 2024, Volume and Issue: 13(6), P. 762 - 762

Published: May 28, 2024

Wildfires play a dual role in ecosystems by providing ecological benefits while posing catastrophic events; they also inflict non-catastrophic damage and yield long-term effects on biodiversity, soil quality, air among other factors, including public health. This study analysed the key determinants of wildland fires Spain using openly available spatial data from 2008 to 2021, fire perimeters, bioclimatic variables, topography, socioeconomic datasets, at resolution 1 km2. Our methodology combined principal component analysis (PCA), linear regression analysis, one-way variance (ANOVA). findings show that scrub/herbaceous vegetation (average 63 ± 1.45% SE) forests 19 0.76% have been highly susceptible wildfires. The population density exhibited robust positive correlation with wildfire frequency (R2 = 0.88, p < 0.0001). Although provides insights into some fire-related climatic drivers over Spain, it includes only temperature- precipitation-based variables does not explicitly consider fuel dynamics. Therefore, more advanced should be applied future understand local specifics regional identified areas near densely populated regions prioritised for management particularly under changing climate conditions.

Language: Английский

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Next-gen regional fire risk mapping: Integrating hyperspectral imagery and National Forest Inventory data to identify hot-spot wildland-urban interfaces

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 940, P. 173568 - 173568

Published: May 31, 2024

The increasing threat of high-severity wildfires in Mediterranean Wildland-Urban Interface (WUI) areas demands to develop effective fire risk assessment and management strategies. Simultaneously, the newfound accessibility spaceborne hyperspectral data represents a significant potential for generating severity assessments, whereas National Forest Inventories (NFI) offer vast dataset related vegetation fuel loads, which is essential shaping planning strategies forest services. This research work aims advance state-of-the-art WUI mapping western Basin by combining PRISMA Spanish NFI data. proposed methodology had three main stages: (i) at local scale (a wildfire) using Multi-Endmember Spectral Mixture Analysis (MESMA) leveraging field-based measurements Composite Burn Index (70 plots); (ii) development high probability map regional from extrapolation Random predictive model calibrated estimates, topo-climatic variables (overall accuracy = 92 %; Kappa 0.8); (iii) identification characterization zones that concentrate WUIs with if event occurs (hot-spot WUIs) crossing information previous cartography developed scale. Study area was Castilla y León Autonomous Region (larger region, 94,226 km

Language: Английский

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The Influence of Wildfire Climate on Wildfire Incidence: The Case of Portugal

Fire, Journal Year: 2024, Volume and Issue: 7(7), P. 234 - 234

Published: July 3, 2024

Although the influence of climate on fire regime is unanimously recognized, most publications and studies this are a global scale. Therefore, study aims to demonstrate role in wildfire incidence at country regional scale using multivariate statistical analysis machine learning methods (clustering classification algorithms). Mainland Portugal was chosen as case due its because it European region affected by wildfires. The results signature spatial temporal distribution incidence. conclusions include (i) existence two pyro-regions, with different types (Csb Csa) composed NUTS II regions: northern Norte Centro regions southern Alentejo Algarve; (ii) intra-annual variability incidence, characterized peaks, one spring other summer, consequence country’s type climate; (iii) how annual cycle varies over years depends weather conditions throughout each year. These fundamental importance for managers, especially context change.

Language: Английский

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Exploring Land System Options to Enhance Fire Resilience under Different Land Morphologies

Fire, Journal Year: 2023, Volume and Issue: 6(10), P. 382 - 382

Published: Oct. 7, 2023

Fire is the origin of serious environmental and social impacts in Mediterranean-like landscapes, such as those California, Australia, southern Europe. Portugal one European countries most affected by fire, which has increased intensity extent recent decades response to variations climate, but mostly due changes land systems (LSs), characterized use cover also factors management intensity, livestock composition, ownership structure, demography. Agricultural activities, contributed fuel overall landscape, were allocated productive areas, while steepest areas occupied extensive shrubland monospecific forests, creating landscapes high fire-proneness. These challenging circumstances call for landscape transformation actions focusing on reducing burned area, spatial distribution LS highly conditioned morphology (LM), limits (e.g., farming operations) that can be taken. Considering constraints posed LM, this study investigates whether there a possibility transforming single modifying from more less fire prone. To better understand landscape–fire relationships, individual interactive effects LM analyzed. Even fire-prone types, 40% proportion agricultural uses results an effective reduction area.

Language: Английский

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Revealing Dynamics of Carbon Storage and Sequestration in Forest Ecosystems: A Downscaling Approach to Support Monitoring Progress Towards Sustainable Management

Published: Jan. 1, 2024

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Language: Английский

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