A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models
Live Fuel Moisture Content (LFMC) contributes to fire danger and behavior, as it affects fire ignition and propagation. This paper presents a two layered Landsat LFMC product based on topographically corrected relative Spectral Indices (SI) over a 2000–2011 time series, which can be integrated into...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/11/1714 |
| _version_ | 1827716196346101760 |
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| author | Mariano García David Riaño Marta Yebra Javier Salas Adrián Cardil Santiago Monedero Joaquín Ramirez M. Pilar Martín Lara Vilar John Gajardo Susan Ustin |
| author_facet | Mariano García David Riaño Marta Yebra Javier Salas Adrián Cardil Santiago Monedero Joaquín Ramirez M. Pilar Martín Lara Vilar John Gajardo Susan Ustin |
| author_sort | Mariano García |
| collection | DOAJ |
| description | Live Fuel Moisture Content (LFMC) contributes to fire danger and behavior, as it affects fire ignition and propagation. This paper presents a two layered Landsat LFMC product based on topographically corrected relative Spectral Indices (SI) over a 2000–2011 time series, which can be integrated into fire behavior simulation models. Nine chaparral sampling sites across three Landsat-5 Thematic Mapper (TM) scenes were used to validate the product over the Western USA. The relations between field-measured LFMC and Landsat-derived SIs were strong for each individual site but worsened when pooled together. The Enhanced Vegetation Index (EVI) presented the strongest correlations (r) and the least Root Mean Square Error (RMSE), followed by the Normalized Difference Infrared Index (NDII), Normalized Difference Vegetation Index (NDVI) and Visible Atmospherically Resistant Index (VARI). The relations between LFMC and the SIs for all sites improved after using their relative values and relative LFMC, increasing r from 0.44 up to 0.69 for relative EVI (relEVI), the best predictive variable. This relEVI served to estimate the herbaceous and woody LFMC based on minimum and maximum seasonal LFMC values. The understory herbaceous LFMC on the woody pixels was extrapolated from the surrounding pixels where the herbaceous vegetation is the top layer. Running simulations on the Wildfire Analyst (WFA) fire behavior model demonstrated that this LFMC product alone impacts significantly the fire spatial distribution in terms of burned probability, with average burned area differences over 21% after 8 h burning since ignition, compared to commonly carried out simulations based on constant values for each fuel model. The method could be applied to Landsat-7 and -8 and Sentinel-2A and -2B after proper sensor inter-calibration and topographic correction. |
| first_indexed | 2024-03-10T19:34:10Z |
| format | Article |
| id | doaj.art-dd76e7e895244700902118969aca8094 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T19:34:10Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-dd76e7e895244700902118969aca80942023-11-20T01:52:31ZengMDPI AGRemote Sensing2072-42922020-05-011211171410.3390/rs12111714A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior ModelsMariano García0David Riaño1Marta Yebra2Javier Salas3Adrián Cardil4Santiago Monedero5Joaquín Ramirez6M. Pilar Martín7Lara Vilar8John Gajardo9Susan Ustin10Environmental Remote Sensing Research Group, Department of Geology, Geography and the Environment, Universidad de Alcalá. Calle Colegios 2, 28801 Alcalá de Henares, SpainEnvironmental Remote Sensing and Spectroscopy Laboratory (SpecLab), Spanish National Research Council (CSIC), 28037 Madrid, SpainFenner School of Environment & Society, Colleges of Science, The Australian National University, Acton, ACT 2601, AustraliaEnvironmental Remote Sensing Research Group, Department of Geology, Geography and the Environment, Universidad de Alcalá. Calle Colegios 2, 28801 Alcalá de Henares, SpainTechnosylva, 24009 León, SpainTechnosylva, 24009 León, SpainTechnosylva, La Jolla, CA 92037-7231, USAEnvironmental Remote Sensing and Spectroscopy Laboratory (SpecLab), Spanish National Research Council (CSIC), 28037 Madrid, SpainEnvironmental Remote Sensing and Spectroscopy Laboratory (SpecLab), Spanish National Research Council (CSIC), 28037 Madrid, SpainInstituto de Bosques y Sociedad, Facultad de Ciencias Forestales Y Recursos Naturales, Universidad Austral de Chile, Campus Isla Teja, Valdivia 5090000, ChileCenter for Spatial Technologies and Remote Sensing (CSTARS), John Muir Institute of the Environment, University of California Davis, One Shields Drive, Davis, CA 95616, USALive Fuel Moisture Content (LFMC) contributes to fire danger and behavior, as it affects fire ignition and propagation. This paper presents a two layered Landsat LFMC product based on topographically corrected relative Spectral Indices (SI) over a 2000–2011 time series, which can be integrated into fire behavior simulation models. Nine chaparral sampling sites across three Landsat-5 Thematic Mapper (TM) scenes were used to validate the product over the Western USA. The relations between field-measured LFMC and Landsat-derived SIs were strong for each individual site but worsened when pooled together. The Enhanced Vegetation Index (EVI) presented the strongest correlations (r) and the least Root Mean Square Error (RMSE), followed by the Normalized Difference Infrared Index (NDII), Normalized Difference Vegetation Index (NDVI) and Visible Atmospherically Resistant Index (VARI). The relations between LFMC and the SIs for all sites improved after using their relative values and relative LFMC, increasing r from 0.44 up to 0.69 for relative EVI (relEVI), the best predictive variable. This relEVI served to estimate the herbaceous and woody LFMC based on minimum and maximum seasonal LFMC values. The understory herbaceous LFMC on the woody pixels was extrapolated from the surrounding pixels where the herbaceous vegetation is the top layer. Running simulations on the Wildfire Analyst (WFA) fire behavior model demonstrated that this LFMC product alone impacts significantly the fire spatial distribution in terms of burned probability, with average burned area differences over 21% after 8 h burning since ignition, compared to commonly carried out simulations based on constant values for each fuel model. The method could be applied to Landsat-7 and -8 and Sentinel-2A and -2B after proper sensor inter-calibration and topographic correction.https://www.mdpi.com/2072-4292/12/11/1714live fuel moisture contentLandsat-5 TMfire behavior simulatorfire dangerfire propagationdata normalization |
| spellingShingle | Mariano García David Riaño Marta Yebra Javier Salas Adrián Cardil Santiago Monedero Joaquín Ramirez M. Pilar Martín Lara Vilar John Gajardo Susan Ustin A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models Remote Sensing live fuel moisture content Landsat-5 TM fire behavior simulator fire danger fire propagation data normalization |
| title | A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models |
| title_full | A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models |
| title_fullStr | A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models |
| title_full_unstemmed | A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models |
| title_short | A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models |
| title_sort | live fuel moisture content product from landsat tm satellite time series for implementation in fire behavior models |
| topic | live fuel moisture content Landsat-5 TM fire behavior simulator fire danger fire propagation data normalization |
| url | https://www.mdpi.com/2072-4292/12/11/1714 |
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