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Predicting and Mapping Potential Fire Severity for Risk Analysis at Regional Level Using Google Earth Engine

https://doi.org/10.3390/rs14194812

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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The role of fire in European Mediterranean ecosystems

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Alternative fire resistance strategies in savanna trees

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Fire Severity in a Large Fire in a Pinus pinaster Forest is Highly Predictable from Burning Conditions, Stand Structure, and Topography

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Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy

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An Implementation of the Rothermel Fire Spread Model in the R Programming Language

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Characterizing potential wildland fire fuel in live vegetation in the Mediterranean region

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Seasonal predictions of Fire Weather Index: Paving the way for their operational applicability in Mediterranean Europe

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Estimating the probability of wildfire occurrence in Mediterranean landscapes using Artificial Neural Networks

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Wildfire susceptibility mapping: Deterministic vs. stochastic approaches

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Fire resistance of European pines

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Environmental drivers of fire severity in extreme fire events that affect Mediterranean pine forest ecosystems

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Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems

inferredcites →https://doi.org/10.1016/j.jenvman.2019.01.056openalex-snapshot

Assessment of factors driving high fire severity potential and classification in a Mediterranean pine ecosystem

inferredcites →https://doi.org/10.1016/j.jenvman.2019.01.077openalex-snapshot

Fire and burn severity assessment: Calibration of Relative Differenced Normalized Burn Ratio (RdNBR) with field data

inferredcites →https://doi.org/10.1016/j.rse.2006.12.006openalex-snapshot

Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR)

inferredcites →https://doi.org/10.1016/j.rse.2008.10.011openalex-snapshot

GeoCBI: A modified version of the Composite Burn Index for the initial assessment of the short-term burn severity from remotely sensed data

inferredcites →https://doi.org/10.1016/j.rse.2008.11.009openalex-snapshot

Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA

inferredcites →https://doi.org/10.1016/j.rse.2010.03.013openalex-snapshot

Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada

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Cloud detection algorithm comparison and validation for operational Landsat data products

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Disentangling the role of prefire vegetation vs. burning conditions on fire severity in a large forest fire in SE Spain

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Fire regime dynamics in mainland Spain. Part 1: Drivers of change

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NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space

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A review of methods for the assessment of prediction errors in conservation presence/absence models

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Random Forests

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Human-ignited fires result in more extreme fire behavior and ecosystem impacts

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ERA5-based global meteorological wildfire danger maps

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Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data

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Fire intensity, fire severity and burn severity: a brief review and suggested usage

inferredcites →https://doi.org/10.1071/wf07151openalex-snapshot

Are wildfires a disaster in the Mediterranean basin? – A review

inferredcites →https://doi.org/10.1071/wf12077openalex-snapshot

The influence of fuel moisture content on the combustion of Eucalyptus foliage

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Estimation of fuel moisture content from multitemporal analysis of Landsat Thematic Mapper reflectance data: Applications in fire danger assessment

inferredcites →https://doi.org/10.1111/brv.12544openalex-snapshot

Fire as a key driver of Earth's biodiversity

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Assessing Climate Change Impacts on Wildfire Exposure in Mediterranean Areas

inferredcites →https://doi.org/10.1139/cjfr-2020-0353openalex-snapshot

Trends in wildfire burn severity across Canada, 1985 to 2015

inferredcites →https://doi.org/10.1371/journal.pone.0099699openalex-snapshot

Fire Activity and Severity in the Western US Vary along Proxy Gradients Representing Fuel Amount and Fuel Moisture

inferredcites →https://doi.org/10.1371/journal.pone.0150073openalex-snapshot

Modelling Variable Fire Severity in Boreal Forests: Effects of Fire Intensity and Stand Structure

inferredcites →https://doi.org/10.1525/california/9780520246058.003.0004openalex-snapshot

Fire as an Ecological Process

inferredcites →https://doi.org/10.18637/jss.v077.i01openalex-snapshot

ranger : A Fast Implementation of Random Forests for High Dimensional Data in C++ and R

inferredcites →https://doi.org/10.1890/11-1930.1openalex-snapshot

Uses and misuses of bioclimatic envelope modeling

inferredcites →https://doi.org/10.2737/rmrs-gtr-371openalex-snapshot

The Rothermel surface fire spread model and associated developments: A comprehensive explanation

inferredcites →https://doi.org/10.32614/rj-2017-016openalex-snapshot

pdp: An R Package for Constructing Partial Dependence Plots

inferredcites →https://doi.org/10.3390/atmos10110672openalex-snapshot

Development and Evaluation of a Reynolds-Averaged Navier–Stokes Solver in WindNinja for Operational Wildland Fire Applications

inferredcites →https://doi.org/10.3390/rs10060879openalex-snapshot

Mean Composite Fire Severity Metrics Computed with Google Earth Engine Offer Improved Accuracy and Expanded Mapping Potential

inferredcites →https://doi.org/10.3390/rs12091499openalex-snapshot

Identifying Post-Fire Recovery Trajectories and Driving Factors Using Landsat Time Series in Fire-Prone Mediterranean Pine Forests

inferredcites →https://doi.org/10.3390/rs13040780openalex-snapshot

A Framework for Multi-Dimensional Assessment of Wildfire Disturbance Severity from Remotely Sensed Ecosystem Functioning Attributes

inferredcites →https://doi.org/10.3390/rs13081448openalex-snapshot

On the Use of Standardized Multi-Temporal Indices for Monitoring Disturbance and Ecosystem Moisture Stress across Multiple Earth Observation Systems in the Google Earth Engine

inferredcites →https://doi.org/10.3390/rs13091658openalex-snapshot

Machine Learning Techniques for Fine Dead Fuel Load Estimation Using Multi-Source Remote Sensing Data

inferredcites →https://doi.org/10.3390/rs13183726openalex-snapshot

Empirical Models for Spatio-Temporal Live Fuel Moisture Content Estimation in Mixed Mediterranean Vegetation Areas Using Sentinel-2 Indices and Meteorological Data

inferredcites →https://doi.org/10.5194/nhess-18-847-2018openalex-snapshot

Extreme wildfire events are linked to global-change-type droughts in the northern Mediterranean

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Improved Fire Severity Prediction Using Pre-Fire Remote Sensing and Meteorological Time Series: Application to the French Mediterranean Area

inferred← citeshttps://doi.org/10.2139/ssrn.4829301openalex-extracted

Improved Fire Severity Prediction Using Pre-Fire Remote Sensing and Meteorological Time Series: Application to the French Mediterranean Area

inferred← citeshttps://doi.org/10.1007/978-3-031-84698-4_21openalex-snapshot

Applications of Geospatial Technology in Wildfire Studies

inferred← citeshttps://doi.org/10.1007/s00477-024-02820-1openalex-snapshot

Predicting potential fire severity in Türkiye’s diverse forested areas: a SHAP-integrated random forest classification approach

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Investigation of wildfire risk and its mapping using GIS-integrated AHP method: a case study over Hoshangabad Forest Division in Central India

inferred← citeshttps://doi.org/10.1016/j.agrformet.2025.110588openalex-snapshot

Improved fire severity prediction using pre-fire remote sensing and meteorological time series: Application to the French Mediterranean area

inferred← citeshttps://doi.org/10.1016/j.ecoinf.2025.103446openalex-snapshot

Advancing forest fire burn severity and vegetation recovery assessments using remote sensing and machine learning approaches

inferred← citeshttps://doi.org/10.1016/j.envsoft.2023.105685openalex-snapshot

Contrasting patterns and interpretations between a fire spread simulator and a machine learning model when mapping burn probabilities: A case study for Mediterranean areas

inferred← citeshttps://doi.org/10.1016/j.ijdrr.2023.104056openalex-snapshot

On the emergence of geospatial cloud-based platforms for disaster risk management: A global scientometric review of google earth engine applications

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

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BAM: A physics-informed self-supervised framework for near-real-time wildfire burned area mapping from multi-source earth observation

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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

inferred← citeshttps://doi.org/10.1016/j.tfp.2024.100520openalex-snapshot

Digital Mapping Burn Severity in Agricultural and Forestry Land over a Half-Decade Using Sentinel Satellite Images on the Google Earth Engine Platform: A Case Study in Isparta Province

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A novel proxy for energy flux in multi-era wildfire reconstruction

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Linking crown fire likelihood with post-fire spectral variability in Mediterranean fire-prone ecosystems

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Fire severity shows limited dependence on fuel structure under adverse fire weather conditions: a case study of two extreme wildfire events

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Fuel biophysical variables retrieved from satellite optical data combined with Prometheus fuel types allow for accurate prediction of potential fire severity

inferred← citeshttps://doi.org/10.3390/f15122192openalex-snapshot

Evaluation of Correction Algorithms for Sentinel-2 Images Implemented in Google Earth Engine for Use in Land Cover Classification in Northern Spain

inferred← citeshttps://doi.org/10.3390/f17030289openalex-snapshot

Wildfire Risk Assessment of a Restricted Military–Civilian Interface: A Multi-Model Analytical Framework from the Korean DMZ

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Multi-Temporal Assessment of Soil Erosion After a Wildfire in Tuscany (Central Italy) Using Google Earth Engine

inferred← citeshttps://doi.org/10.3390/rs15143458openalex-snapshot

A New Approach Based on TensorFlow Deep Neural Networks with ADAM Optimizer and GIS for Spatial Prediction of Forest Fire Danger in Tropical Areas

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Google Earth Engine Since 2022: A Structured Bibliometric Review of GeoAI-Driven Trends and Applications

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Mapping wildfire impacts on aboveground biomass and soil loss: The Yamanlar fire, Türkiye

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