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136 II - VALIDATION OF RS PRODUCTS FOR FIRE MANAGEMENT 5 - Conclusions We have shown that it is feasible to assess dead fuel moisture content by means of remote sensing data. Air temperature and relative humidity have been estimated with MSG-SEVIRI data in a meteorological station in Spain. The main source of error is due to unexplained variance in the retrieval of the vapour pressure. Future research will be focused on improving the estimation of water vapour with precipitable water content. A more robust relationship will be addressed by increasing the number of meteorological data trying to cover the whole Spanish territory. N MAE RMSE a b R U bias U slope U error e a (kPa) 59 0.17 0.22 0.32 0.76 0.61 0.25 0.04 0.71 T (ºC) 364 2.51 3.37 1.84 0.85 0.89 0.20 0.08 0.72 RH (%) 364 9.09 12.59 12.22 0.75 0.68 0.12 0.08 0.80 10h (%) 364 2.12 3.28 3.85 0.64 0.62 0.08 0.15 0.77 Table 1. Error measurements of retrieved parameters. N, number of elements; MAE, mean absolute error; RMSE, root mean square error; a and b, intercept and slope of the regression between observed versus predicted; r, Pearson correlation between observed and predicted; U bias , proportion of RMSE associated with mean differences between observed and predicted values; U slope , proportion of RMSE associated with deviations from the 1:1 line; U error , proportion of RMSE associated with unexplained variance. References Aguado, I., Chuvieco, E., Borén, R., Nieto, H., 2007. Estimation of dead fuel moisture content from meteorological data in Mediterranean areas. Applications in fire danger assessment. International Journal of Wildland Fire, 16, 390-397. Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop evapotranspiration: Guidelines for computing crop water requirements (p. 300). Rome, Italy: FAO. Bolsenga, S.J., 1965. The Relationship Between Total Atmospheric Water Vapor and Surface Dew Point on a Mean Daily and Hourly Basis. Journal of Applied Meteorology, 4, 430-432. Bradshaw, B.S., Deeming, J.E., 1983. The 1978 National Fire Danger Rating System. Technical documentation (p. 41). Ogden, Utah: USDA. Dimitrakopoulos, A., Papaioannou, K.K., 2001. Flammability assessment of Mediterranean forest fuels. Fire Technology, 37, 143-152. Goward, S.N., Waring, R.H., Dye, D.G., Yang, J.L., 1994. Ecological Remote- Sensing at OTTER: Satellite Macroscale Observations. Ecological Applications, 4, 322-343. Rothermel, R.C., 1972. A Mathematical Model for Predicting Fire Spread in Wildland Fuels. Ogden, Utah: USDA, Forest Service. Schwarz, F.K., 1968. Comments on “Note on the Relationship between Total
Estimation of national fire danger rating system 10 hour timelag fuel moisture content with MSG-SEVIRI data 137 Precipitable Water and Surface Dew Point”. Journal of Applied Meteorology, 7, 509-510. Simard, A.J., 1968. The moisture content of forest fuels - A review of the basic concepts (p. 47). Ottawa, Ontario: Forest Fire Research Institute. Smith, W.L., 1966. Note on the Relationship Between Total Precipitable Water and Surface Dew Point. Journal of Applied Meteorology, 5, 726- 727. Sobrino, J.A., Romaguera, M., 2004. Land surface temperature retrieval from MSG1-SEVIRI data. Remote Sensing of Environment, 92, 247-254. Sobrino, J.A., Romaguera, M., 2008. Water-vapour retrieval from Meteosat 8/SEVIRI observations. International Journal of Remote Sensing, 29, 741-754. Viney, N.R., 1991. A Review of Fine Fuel Moisture Modelling (pp. 215-234). Viney, N.R., Catchpole, E.A., 1991. Estimating Fuel Moisture Response Times From Field Observations. International Journal of Wildland Fire, 1, 211- 214.
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Proceedings of the VII Internationa
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SCIENTIFIC COMMITTEE Olivier Arino
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Analysis of human-caused wildfire o
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Monitoring post-fire vegetation reg
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10 Agency, Italian National Forestr
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I PRE-FIRE PLANNING AND MANAGEMENT
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16 I - PRE-FIRE PLANNING AND MANAGE
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USING SPATIAL ANALYSIS TO CHARACTER
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Using spatial analysis to character
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Abstract: Fire is the major stand-r
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Fire and climate change in Boreal F
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PROJECTING FUTURE BURNT AREA IN THE
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Projecting future burnt area in the
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Projecting future burnt area in the
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MULTISCALE CHARACTERIZATION OF SPAT
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Multiscale characterization of spat
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Multiscale characterization of spat
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CLASSIFICATION OF SITE AND STAND CH
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Classification of site and stand ch
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Classification of site and stand ch
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FUEL MOISTURE CONTENT ESTIMATION: A
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Fuel moisture content estimation: a
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Fuel moisture content estimation: a
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FUEL MODEL MAPPING USING IKONOS IMA
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Fuel model mapping using ikonos ima
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FIRST STEPS TOWARDS A LONG TERM FOR
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First steps towards a long term for
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3 - Conclusion and further research
Page 88 and 89: 86 I - PRE-FIRE PLANNING AND MANAGE
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Page 93 and 94: FUEL MOISTURE CONTENT ESTIMATION BA
Page 95 and 96: 3 - Results Fuel moisture content e
Page 97 and 98: CYBERPARK PROJECT: MULTITEMPORAL SA
Page 99 and 100: Cyberpark project: Multitemporal sa
Page 101 and 102: REMOTE SENSING-BASED MAPPING OF FUE
Page 103 and 104: Remote Sensing-based Mapping of fue
Page 105 and 106: ASSESSING CRITICAL FUEL PARAMETERS
Page 107 and 108: Assessing critical fuel parameters
Page 109: II VALIDATION OF RS PRODUCTS FOR FI
Page 112 and 113: 110 II - VALIDATION OF RS PRODUCTS
Page 117 and 118: RELATIONSHIPS BETWEEN COMBUSTION PR
Page 119 and 120: Relationships between combustion pr
Page 121: Relationships between combustion pr
Page 129 and 130: OPERATIONAL USE OF REMOTE SENSING I
Page 131 and 132: Operational use of remote sensing i
Page 133: Operational use of remote sensing i
Page 141 and 142: GLOBAL MONITORING OF THE ENVIRONMEN
Page 143 and 144: Global monitoring of the environmen
Page 145: Global monitoring of the environmen
Page 153 and 154: DAILY MONITORING OF PRE-FIRE VEGETA
Page 155 and 156: Daily monitoring of pre-fire vegeta
Page 157 and 158: THE GLOBAL MODIS BURNED AREA PRODUC
Page 159 and 160: The global MODIS burned area produc
Page 161: III FIRE DETECTION AND FIRE MONITOR
Page 164 and 165: 162 III - FIRE DETECTION AND FIRE M
Page 169 and 170: REAL-TIME MONITORING OF THE TRANSMI
Page 171 and 172: Real-time monitoring of the transmi
Page 173 and 174: NOAA’S OPERATIONAL FIRE AND SMOKE
Page 175 and 176: Noaa’s operational fire and smoke
Page 177 and 178: SYSTEM FOR EARLY FOREST FIRE DETECT
Page 179 and 180: 3 - Result in Germany System for ea
Page 181: References System for early forest
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ADVANCING THE USE OF MULTI-RESOLUTI
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Advancing the use of multi-resoluti
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Advancing the use of multi-resoluti
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194 III - FIRE DETECTION AND FIRE M
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IV BURNED LAND MAPPING, FIRE SEVERI
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204 IV - BURNED LAND MAPPING, FIRE
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Abstract: The aim of this paper is
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Burnt area index using MODIA and AS
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4 - Conclusions Burnt area index us
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SATELLITE DERIVED MULTI-YEAR BURNED
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Satellite derived multi-year burned
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Satellite derived multi-year burned
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MODIS REFLECTIVE AND ACTIVE FIRE DA
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3 - Methodology and results MODIS r
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MODIS reflective and active fire da
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SOME NOTES ON SPECTRAL PROPERTIES O
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Some notes on spectral properties o
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MONITORING POST-FIRE VEGETATION REG
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Abstract: SAR data from a test site
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Backscatter properties of x- and c-
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6 - Conclusions Backscatter propert
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CORRECTION OF TOPOGRAPHIC EFFECTS I
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Correction of topographic effects i
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Correction of topographic effects i
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BURNED AREAS MAPPING BY MULTISPECTR
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Burned areas mapping by multispectr
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Burned areas mapping by multispectr
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4 - Conclusions Burned areas mappin
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Abstract: In this paper NDVI VEGETA
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Post Fire vegetation recovery estim
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Post Fire vegetation recovery estim
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292 FORTUNATO G. pag. 191 FRENCH N.
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Finito di stampare nel mese di agos
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