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Projecting live fuel moisture content via deep learning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/hyp.3360070205openalex-snapshot
III. Measuring surface soil moisture using passive microwave remote sensing
inferredcites →https://doi.org/10.1002/joc.1688openalex-snapshot
Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States
inferredcites →https://doi.org/10.1007/s40725-020-00116-5openalex-snapshot
Satellite Remote Sensing Contributions to Wildland Fire Science and Management
inferredcites →https://doi.org/10.1016/j.agrformet.2007.12.005openalex-snapshot
Estimation of live fuel moisture content from MODIS images for fire risk assessment
inferredcites →https://doi.org/10.1016/j.agrformet.2021.108503openalex-snapshot
Continental-scale prediction of live fuel moisture content using soil moisture information
inferredcites →https://doi.org/10.1016/j.agrformet.2022.108941openalex-snapshot
Drought-related leaf functional traits control spatial and temporal dynamics of live fuel moisture content
inferredcites →https://doi.org/10.1016/j.cliser.2017.04.001openalex-snapshot
Seasonal predictions of Fire Weather Index: Paving the way for their operational applicability in Mediterranean Europe
inferredcites →https://doi.org/10.1016/j.envsoft.2022.105467openalex-snapshot
Multi-modal temporal CNNs for live fuel moisture content estimation
inferredcites →https://doi.org/10.1016/j.isprsjprs.2021.07.010openalex-snapshot
Live fuel moisture content estimation from MODIS: A deep learning approach
inferredcites →https://doi.org/10.1016/j.jhydrol.2007.02.018openalex-snapshot
Spatially distributing monthly reference evapotranspiration and pan evaporation considering topographic influences
inferredcites →https://doi.org/10.1016/j.rse.2004.03.017openalex-snapshot
Estimating live fuel moisture content from remotely sensed reflectance
inferredcites →https://doi.org/10.1016/j.rse.2006.06.023openalex-snapshot
Evaluating remotely sensed live fuel moisture estimations for fire behavior predictions in Georgia, USA
inferredcites →https://doi.org/10.1016/j.rse.2013.05.029openalex-snapshot
A global review of remote sensing of live fuel moisture content for fire danger assessment: Moving towards operational products
inferredcites →https://doi.org/10.1016/j.rse.2017.06.031openalex-snapshot
Google Earth Engine: Planetary-scale geospatial analysis for everyone
inferredcites →https://doi.org/10.1016/j.rse.2018.04.053openalex-snapshot
A fuel moisture content and flammability monitoring methodology for continental Australia based on optical remote sensing
inferredcites →https://doi.org/10.1016/j.rse.2020.111797openalex-snapshot
SAR-enhanced mapping of live fuel moisture content
inferredcites →https://doi.org/10.1016/j.scitotenv.2019.04.296openalex-snapshot
Seasonal prediction of climate-driven fire risk for decision-making and operational applications in a Mediterranean region
inferredcites →https://doi.org/10.1016/j.scitotenv.2021.145410openalex-snapshot
Evaluation of microwave soil moisture data for monitoring live fuel moisture content (LFMC) over the coterminous United States
inferredcites →https://doi.org/10.1023/a:1011641601076openalex-snapshot
Flammability Assessment of Mediterranean Forest Fuels
inferredcites →https://doi.org/10.1029/2021gl092843openalex-snapshot
A Shorter, Sharper Rainy Season Amplifies California Wildfire Risk
inferredcites →https://doi.org/10.1038/s41597-019-0164-9openalex-snapshot
Globe-LFMC, a global plant water status database for vegetation ecophysiology and wildfire applications
inferredcites →https://doi.org/10.1038/sdata.2018.214openalex-snapshot
Present and future Köppen-Geiger climate classification maps at 1-km resolution
inferredcites →https://doi.org/10.1071/ar06188openalex-snapshot
Constraints and opportunities in applying seasonal climate forecasts in agriculture
inferredcites →https://doi.org/10.1071/wf07017openalex-snapshot
Evaluating predictive models of critical live fuel moisture in the Santa Monica Mountains, California
inferredcites →https://doi.org/10.1071/wf08055openalex-snapshot
Critical live fuel moisture in chaparral ecosystems: a threshold for fire activity and its relationship to antecedent precipitation
inferredcites →https://doi.org/10.1071/wf18091openalex-snapshot
Why is the effect of live fuel moisture content on fire rate of spread underestimated in field experiments in shrublands?
inferredcites →https://doi.org/10.1071/wf9910101openalex-snapshot
Modelling Moisture Damping for Fire Spread in a Mixture of Live and Dead Fuels
inferredcites →https://doi.org/10.1098/rsif.2013.1162openalex-snapshot
On the reliability of seasonal climate forecasts
inferredcites →https://doi.org/10.1111/nph.15808openalex-snapshot
Macro to micro: microwave remote sensing of plant water content for physiology and ecology
inferredcites →https://doi.org/10.1127/0941-2948/2006/0130openalex-snapshot
World Map of the Köppen-Geiger climate classification updated
inferredcites →https://doi.org/10.1127/0941-2948/2011/105openalex-snapshot
The thermal zones of the Earth according to the duration of hot, moderate and cold periods and to the impact of heat on the organic world
inferredcites →https://doi.org/10.1139/x04-101openalex-snapshot
Conversion of fuel moisture content values to ignition potential for integrated fire danger assessment
inferredcites →https://doi.org/10.1146/annurev.earth.33.092203.122541openalex-snapshot
OROGRAPHIC PRECIPITATION
inferredcites →https://doi.org/10.1175/bams-84-5-595openalex-snapshot
Climate and Wildfire in the Western United States
inferredcites →https://doi.org/10.1175/jcli-d-17-0410.1openalex-snapshot
An Assessment of High-Resolution Gridded Temperature Datasets over California
inferredcites →https://doi.org/10.1175/jhm-d-19-0232.1openalex-snapshot
A Comparison of the U.S. Climate Reference Network Precipitation Data to the Parameter-Elevation Regressions on Independent Slopes Model (PRISM)
inferredcites →https://doi.org/10.1371/journal.pone.0141140openalex-snapshot
Mapping Atmospheric Moisture Climatologies across the Conterminous United States
inferredcites →https://doi.org/10.1371/journal.pone.0204889openalex-snapshot
Determining fuel moisture thresholds to assess wildfire hazard: A contribution to an operational early warning system
inferredcites →https://doi.org/10.2307/2845287openalex-snapshot
Gradient Analysis of Latitudinal Variation in Southern Rocky Mountain Forests
inferredcites →https://doi.org/10.3390/fire4030045openalex-snapshot
Boots on the Ground and Eyes in the Sky: A Perspective on Estimating Fire Danger from Soil Moisture Content
inferredcites →https://doi.org/10.3390/fire5040110openalex-snapshot
Forecasting Live Fuel Moisture of Adenostema fasciculatum and Its Relationship to Regional Wildfire Dynamics across Southern California Shrublands
inferredcites →https://doi.org/10.3390/rs11131575openalex-snapshot
Estimating Live Fuel Moisture Using SMAP L-Band Radiometer Soil Moisture for Southern California, USA
inferredcites →https://doi.org/10.3390/rs12142251openalex-snapshot
Investigating Live Fuel Moisture Content Estimation in Fire-Prone Shrubland from Remote Sensing Using Empirical Modelling and RTM Simulations
inferredcites →https://doi.org/10.4996/fireecology.0801077openalex-snapshot
Modelling Fire Ignition Probability from Satellite Estimates of Live Fuel Moisture Content
inferredcites →https://doi.org/10.5194/bg-6-1389-2009openalex-snapshot
Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France
inferredcites →https://doi.org/10.5194/hess-11-1633-2007openalex-snapshot
Updated world map of the Köppen-Geiger climate classification
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4851320openalex-extracted
Real-Time Assessment of Live Forest Fuel Moisture Content and Flammability by Using Space-Time Universal Kriging
inferred← citeshttps://doi.org/10.1002/ajb2.70040openalex-snapshot
From plant traits to fire behavior: Scaling issues in flammability studies
inferred← citeshttps://doi.org/10.1002/rse2.416openalex-snapshot
Leveraging the next generation of spaceborne Earth observations for fuel monitoring and wildland fire management
inferred← citeshttps://doi.org/10.1007/s11069-026-08022-yopenalex-snapshot
A study on machine learning-based prediction model for surface litter moisture content in coniferous forests
inferred← citeshttps://doi.org/10.1007/s12145-024-01690-zopenalex-snapshot
Machine learning methods for wildfire risk assessment
inferred← citeshttps://doi.org/10.1016/j.agrformet.2026.111093openalex-snapshot
Drought indices predict changes in live fuel moisture content (LFMC) across French Mediterranean shrublands: a multisource and machine learning approach
inferred← citeshttps://doi.org/10.1016/j.ecoinf.2026.103639openalex-snapshot
A continental-scale approach to ecosystem condition monitoring using satellite imagery and deep learning
inferred← citeshttps://doi.org/10.1016/j.envsoft.2024.106111openalex-snapshot
A physics-based model of thermodynamically varying fuel moisture content for fire behavior prediction
inferred← citeshttps://doi.org/10.1016/j.envsoft.2026.106942openalex-snapshot
Untethered from earthly constraints: A spatial seven-day ahead machine-learning forest fuel moisture forecasting system, independent of real-time sensor networks
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2025.06.002openalex-snapshot
Deep learning for wildfire risk prediction: Integrating remote sensing and environmental data
inferred← citeshttps://doi.org/10.1016/j.pyro.2026.100010openalex-snapshot
Seasonal prediction of live fuel moisture content
inferred← citeshttps://doi.org/10.1038/s41597-024-03159-6openalex-snapshot
Globe-LFMC 2.0, an enhanced and updated dataset for live fuel moisture content research
inferred← citeshttps://doi.org/10.1080/01431161.2026.2633780openalex-snapshot
Estimation of Live fuel moisture content via spectral–meteorological time-series fusion: a TCN–BiGRU deep learning framework
inferred← citeshttps://doi.org/10.1109/mgrs.2024.3393010openalex-snapshot
Deep Learning for Satellite Image Time-Series Analysis: A review
inferred← citeshttps://doi.org/10.21203/rs.3.rs-5093197/v1openalex-snapshot
Comparative Analysis of Linear Regression and Machine Learning Models for Dead Fuel Moisture Content Prediction in Golestan Province Forests, NE Iran
inferred← citeshttps://doi.org/10.2139/ssrn.5366420openalex-snapshot
A Continental-Scale Approach to Ecosystem Condition Monitoring Using Satellite Imagery and Deep Learning
inferred← citeshttps://doi.org/10.3390/f15050736openalex-snapshot
Comparative Analysis of Machine Learning-Based Predictive Models for Fine Dead Fuel Moisture of Subtropical Forest in China
inferred← citeshttps://doi.org/10.3390/f16091423openalex-snapshot
A Novel Approach for Inverting Forest Fuel Moisture Content Utilizing Multi-Source Remote Sensing and Deep Learning
inferred← citeshttps://doi.org/10.3390/f17070817openalex-snapshot
From Ecological Monitoring to Prevention Decision Support: A Critical Review of Artificial Intelligence for Forest Fire Prevention
inferred← citeshttps://doi.org/10.3390/f17101158openalex-snapshot
Post-Rainfall Dynamics and Hourly Prediction of Surface Fine Dead Fuel Moisture Across Contrasting Land-Cover Conditions in Northeast China
inferred← citeshttps://doi.org/10.3390/fire9010026openalex-snapshot
A Recurrent Neural Network for Forecasting Dead Fuel Moisture Content with Inputs from Numerical Weather Models
inferred← citeshttps://doi.org/10.3390/jimaging12020088openalex-snapshot
Analysis of Biological Images and Quantitative Monitoring Using Deep Learning and Computer Vision
inferred← citeshttps://doi.org/10.3390/rs16132480openalex-snapshot
Operational Forest-Fire Spread Forecasting Using the WRF-SFIRE Model
inferred← citeshttps://doi.org/10.3390/rs17213580openalex-snapshot
Monitoring Wildfire Risk with a Near-Real-Time Live Fuel Moisture Content System: A Review and Roadmap for Operational Application in New Zealand
inferred← citeshttps://doi.org/10.5194/nhess-25-1521-2025openalex-snapshot
Evaluation of machine learning approaches for large-scale agricultural drought forecasts to improve monitoring and preparedness in Brazil
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