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

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190 III - FIRE DETECTION AND FIRE MONITORING Among the fire characterization parameters provided by WF-ABBA and TA, the FRP estimates showed better sensitivity to varying fire conditions. The interplay among sub-pixel fires, background characterization, and the sensor characteristics (in particular the point spread function), had an important effect on the accuracy of the estimates produced. Pixel based estimates derived from different products remain poorly correlated and subjected to random errors. Using the results above, we designed a set of judicious criteria to integrate the active fire data from MODIS Terra and Aqua and the GOES imager (see Schroeder, 2008a) (Figure 2). The resulting product incorporates corrections aimed to minimize errors of commission and omission to maximize the complementarity between products. 4 - Conclusions In this study we discuss briefly how multiple data sets of rather different characteristics are used to advance our understanding of sub-pixel processes governing vegetation fire activity routinely mapped by two major hemispheric-to-global fire products. The results derived from the group of analyses described above are being used to further develop the fire algorithms in use, to reduce errors and to improve their performance over a broad range of conditions. References Csiszar, I., Morisette, J.T. and Giglio, L., 2006. Validation of active fire detection from moderate-resolution satellite sensors: the MODIS example in Northern Eurasia. IEEE Trans. Geo. Rem. Sens., 44(7), 1757-1764. Csizar, I., Schroeder, W., 2008. Short-term observations of the temporal development of active fires from consecutive same-day ETM+ and ASTER imagery in the Amazon: Implications for active fire product validation. IEEE J. Sel. Topics in App. Earth Obs. and Rem. Sens., 10.1109/JSTARS. 2008.2011377. Giglio, L., Csiszar, I., Restas, A., Morisette, J.T., Schroeder, W., Morton, D., Justice, C.O., 2008. Active fire detection and characterization with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Rem. Sens. Environ., 2008, doi:10.1016/j.rse.2008.03.003. Morisette, J.T., Giglio, L., Csiszar, I., Justice, C.O., 2005. Validation of the MODIS active fire product over Southern Africa with ASTER data. Int. J. Rem. Sens., 26(19), 4239-4264. Schroeder, W., 2008a. Towards an integrated system for vegetation fire monitoring. Univ. of Maryland, URL: http://hdl.handle.net/1903/8168. Schroeder, W., Csiszar, I. and Morisette, J., 2008b. Quantifying the impact of cloud obscuration on remote sensing of active fires in the Brazilian
Advancing the use of multi-resolution remote sensing data to detect and characterize biomass burning 191 Amazon. Rem. Sens. Env., doi:10.1016/j.rse.2007.05.004. Schroeder, W., Prins, E., Giglio, L., Csiszar, I., Schmidt, C., Morisette, J., Morton, D., 2008c. Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data. Rem. Sens. Env., doi:10.1016/j.rse.2008.01.005.
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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
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FUEL MOISTURE CONTENT ESTIMATION BA
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3 - Results Fuel moisture content e
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CYBERPARK PROJECT: MULTITEMPORAL SA
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Cyberpark project: Multitemporal sa
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REMOTE SENSING-BASED MAPPING OF FUE
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Remote Sensing-based Mapping of fue
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ASSESSING CRITICAL FUEL PARAMETERS
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Assessing critical fuel parameters
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II VALIDATION OF RS PRODUCTS FOR FI
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110 II - VALIDATION OF RS PRODUCTS
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RELATIONSHIPS BETWEEN COMBUSTION PR
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Relationships between combustion pr
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Relationships between combustion pr
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OPERATIONAL USE OF REMOTE SENSING I
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Operational use of remote sensing i
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Operational use of remote sensing i
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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 148 and 149: 146 II - VALIDATION OF RS PRODUCTS
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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
Page 189 and 190: ADVANCING THE USE OF MULTI-RESOLUTI
Page 191: Advancing the use of multi-resoluti
Page 203: IV BURNED LAND MAPPING, FIRE SEVERI
Page 206 and 207: 204 IV - BURNED LAND MAPPING, FIRE
Page 211 and 212: Abstract: The aim of this paper is
Page 213 and 214: Burnt area index using MODIA and AS
Page 215 and 216: 4 - Conclusions Burnt area index us
Page 217 and 218: SATELLITE DERIVED MULTI-YEAR BURNED
Page 219 and 220: Satellite derived multi-year burned
Page 221: Satellite derived multi-year burned
Page 229 and 230: MODIS REFLECTIVE AND ACTIVE FIRE DA
Page 231 and 232: 3 - Methodology and results MODIS r
Page 233: MODIS reflective and active fire da
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240 IV - BURNED LAND MAPPING, FIRE
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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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