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

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218 IV - BURNED LAND MAPPING, FIRE SEVERITY DETERMINATION, AND VEGETATION RECOVERY ASSESSMENT face is detected in 2002 (36.07 ha) only in the crop (74%) and grass/shrub (26%) classes. In this park burned area is also detected in pastureland (data not shown in the histograms) although it is only 3% of the five-year total (1157.55 ha). This type of information can be very useful for the assessment of land cover changes driven by fires especially when they affect natural resources such as protected forests. Accuracy assessment showed that on average the overall accuracy of ASTER scene classification is better than 90% and omission and commission errors are about 50% and 15%; low commission errors highlight that classification is conservative with few false alarms. These figures quantify the average scene accuracy and not the accuracy of the annual burned area maps obtained by summing burned perimeters. Since our results can be of interest for scientific groups working on fire monitoring, we distribute burned area maps through a Web Map Server (WMS) (URL: http://geoportal.irea.cnr.it:8080/geoportal/local_it.jsp) created at CNR-IREA premises for purposes of the European Project IDE- Univers (www.ideunivers.eu). These burned areas perimeters are also available through the “Portale Cartografico Nazionale” (URL: http://www.pcn. minambiente.it/PCN/progetto_incendi.htm) of the Italian Ministry of the Environment. 4 - Conclusions In this work we built a geographic database of burned area perimeters for Italian National Parks derived from ASTER and SPOT satellite images between 2001 and 2005. Accuracy measures highlighted the conservative character of the classifications with a low rate of false alarms (average scene commission error is less than 15%). References Brivio, P.A., Petrucci, B., Boschetti, M., Carrara, P., Pepe, M., Rampini, A., Stroppiana, D., Zaffaroni, P., 2009. A multi-year geographic database of fire affected area derives from satellite images in the National Parks of Italy. Italian Journal of Remote Sensing, Vol 41, n. 2. Congalton, R.G., 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37, 35-46. Paganini, M., Arino, O., Benvenuti, M., Cristaldi, M., Bordin, M., Coretti, C., Musone, A., 2003. ITALSCAR, a regional burned forest mapping demonstration project in Italy. International Geoscience and Remote Sensing Symposium, 2003. IGARSS ‘03. Proc. 2003 IEEE Volume 2, 21-25 July 2003: 1290-1292. Piccoli D., Cattoi M., 2004. I rilievi delle aree percorse dal fuoco effettuati dal Corpo Forestale dello Stato per le attività di polizia giudiziaria.
Satellite derived multi-year burned area perimeters within the national parks of Italy 219 Presentazione del seminario “Telerilevamento e spazializzazione nel monitoraggio forestale e ambientale per la difesa degli ecosistemi” Università degli Studi del Molise, Pesche (IS), 24 January 2007. Thonicke, K., Venevsky, S., Sitch, S., Cramer, W., 2001. The role of fire disturbance for global vegetation dynamics: coupling fire into a Dynamic Global Vegetation Model. Global Ecology & Biogeography, 10, 661-677.
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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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GLOBAL MONITORING OF THE ENVIRONMEN
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Global monitoring of the environmen
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Global monitoring of the environmen
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DAILY MONITORING OF PRE-FIRE VEGETA
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Daily monitoring of pre-fire vegeta
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THE GLOBAL MODIS BURNED AREA PRODUC
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The global MODIS burned area produc
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III FIRE DETECTION AND FIRE MONITOR
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162 III - FIRE DETECTION AND FIRE M
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164 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
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Page 181: References System for early forest
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Page 189 and 190: ADVANCING THE USE OF MULTI-RESOLUTI
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Page 203: IV BURNED LAND MAPPING, FIRE SEVERI
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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: 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
Page 245 and 246: SOME NOTES ON SPECTRAL PROPERTIES O
Page 247 and 248: Some notes on spectral properties o
Page 249 and 250: MONITORING POST-FIRE VEGETATION REG
Page 251 and 252: Monitoring post-fire vegetation reg
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Page 261 and 262: Abstract: SAR data from a test site
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268 IV - BURNED LAND MAPPING, FIRE
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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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