7th Workshop on Forest Fire Management - EARSeL, European ...

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118 II - VALIDATION OF RS PRODUCTS FOR FIRE MANAGEMENT where CR (λi) is the differential absorption in each wavelength (λi), R (λi) is the reflectance, Rc λ(i) is the reflectance of the continuous tendency. 4 - Results The three sets of spectral data, reflectance (R), FDS and BD, were analyzed using a stepwise multiple linear regression routine. The number of points of the data set (n=305) allowed choosing until six independent variables. Results are summarized in the Table 1. Statistically significant relationships are observed between the vegetation remains product and the three spectral datasets (adjusted r 2 > 0.8). The results of the charcoal product show more differences between spectral datasets although the values are quite good in all of them: adjusted r 2 near 0.6 in the R and BD datasets and higher than 0.7 in the FDS. Differences between datasets are also observed in the ash product although with this product the analysis with the BD dataset does not achieve good results (adjusted r 2 = 0.46), relationships with R and FDS shown values of 0.67 and 0.74, respectively. Table 1 - Summary of the regression results. 5 - Conclusions This research has shown the validity of the combined used of high spatial resolution photography and field spectrometry to better the understanding of fire severity variable. According to the results we can state some conclusions related to the usefulness of the different spectral dataset. The calculation of transformed hyperspectral data is justified only for ash products and especially for the charcoal because vegetation showed the same adjust-
Relationships between combustion products and their spectral properties in fire-affected shrublands 119 ed values with the three dataset (R, FDS and BD). Considering the results attained in the FDS dataset we can state that vegetation, charcoal and ash can be adequately estimate from spectral data. As these products are representative of different fire severity levels, we can conclude that from FDS we are able to improve the evaluation of this variable. References Dawson, T.P., Curran, P.J., 1998. Technical note: A new technique for interpolating the reflectance red edge position. International Journal of Remote Sensing, 19: 2133-2139. Miller, J.D., Yool, S.R., 2002. Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM+ data. Remote Sensing of Environment, 82: 481-496. Mutanga, O., Skidmore, A.K., 2004. Hyperspectral band depth analysis for better estimation of grass biomass (Cenchrus ciliaris) measured under controlled laboratory conditions. International Journal of Applied Earth Observations and Geoinformation, 5: 87-96. Pérez, B., Moreno, J.M., 1998. Methods for quantifying fire severity in shrubland-fires, Plant Ecology, 139: 91-101. Smith, A.M.S., Wooster, M.J., Drake, N.A., Dipotso, F.M., Falkowski, M.J. and Hudak, H.T., 2005. Testing the potential of multispectral remote sensing for retrospectively estimating fire severity in African Savannahs, Remote Sensing of Environment, 97: 92-115.
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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
Page 69: Fuel moisture content estimation: a
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Page 77 and 78: FUEL MODEL MAPPING USING IKONOS IMA
Page 79 and 80: Fuel model mapping using ikonos ima
Page 81 and 82: FIRST STEPS TOWARDS A LONG TERM FOR
Page 83 and 84: First steps towards a long term for
Page 85: 3 - Conclusion and further research
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
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Page 117 and 118: RELATIONSHIPS BETWEEN COMBUSTION PR
Page 119: 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
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Page 169 and 170: REAL-TIME MONITORING OF THE TRANSMI
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Real-time monitoring of the transmi
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NOAA’S OPERATIONAL FIRE AND SMOKE
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Noaa’s operational fire and smoke
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SYSTEM FOR EARLY FOREST FIRE DETECT
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3 - Result in Germany System for ea
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References System for early forest
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182 III - FIRE DETECTION AND FIRE M
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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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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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