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

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82 I - PRE-FIRE PLANNING AND MANAGEMENT According to the Pan-European Forest/Non-Forest Map 2000, only 10.7% of the ignition points fall into the Forest category. It must be considered that the Forest class excludes woodlands with trees smaller than 5 m height, burnt areas, forest roads and forest nurseries and regeneration (with less than 30% canopy closure). Data limitations derived from the incorrect insertion of coordinates in the original file and the posterior transformation of projection systems must be taken into account. Nevertheless, these results provide an important insight about the fire domain concerning ignitions; land covers such as artificial surfaces that represent the urban/rural interface and the agricultural areas, shouldn’t be excluded from the analysis, since fires often start in these areas and propagate to wildlands. These findings are in accordance with previous studies, which show that around 95% of forest fires in Mediterranean Europe are human-caused (e.g., Ne’eman et al., 2004). To confirm the influence of human variables in the occurrence of fires, an additional preliminary analysis was carried out, based on the distribution of ignition points in relation to the roads network. Data of Portuguese roads were obtained from TeleAtlas (2006-2009 TeleAtlas) and analysed according to the type of roads (national roads and local roads). Buffers of 50, 100, 200 and 500 meters were created around the roads and the total number of ignition points falling into each buffer was calculated. It was found that the density of ignition points (IP/km2 /10) increases in the classes up to 100 m distance from the roads, being more evident in the local roads dataset (Fig. 2). Figure 2 - Density of ignition points according to distance from the roads.
3 - Conclusion and further research First steps towards a long term forest fire risk of Europe 83 These preliminary results point out to the potential influence of land use and road network in the distribution of fire ignition points in Portugal. Further analysis of these and other variables is under development, as part of the methodology to assess long-term forest fire risk in Europe. References Amatulli, G., Perez-Cabello, F., de la Riva, J., 2007. Mapping lightning/ human-caused wildfires occurrence under ignition point location uncertainty. Ecological Modelling 200: 321-333 Catry, F.X., Damasceno, P., Silva, J.S., Galante, M., Moreira, F., 2007. Spatial Distribution Patterns of Wildfire Ignitions in Portugal. International Conference Wildfire 2007, Sevilla, Spain de la Riva, J., Perez-Cabello, F., Lana-Renault, N., Koutsias, N., 2004. Mapping wildfire occurrence at regional scale. Remote sensing of Environment 92: 288-294 Martinez, J., Vega-Garcia, C., Chuvieco, E., 2009. Human-caused wildfire risk rating for prevention planning in Spain. Journal of Environmental Management 90: 1241-1252 Ne’eman, G., Goubitz, S., Nathan, R., 2004. Reproductive traits of Pinus halepensis in the light of fire - a critical review. Plant Ecology 171, pp. 69-79 Pekkarinen, A., Reithmaier, L., Strobl, P., 2009. Pan-European Forest/Non- Forest mapping with Landsat ETM+ and CORINE Land Cover 2000 data. ISPRS Journal of Photogrammetry and Remote Sensing, 64 (2), 171-183
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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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18 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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Fire and climate change in Boreal F
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Page 35 and 36: PROJECTING FUTURE BURNT AREA IN THE
Page 37 and 38: Projecting future burnt area in the
Page 39 and 40: Projecting future burnt area in the
Page 41 and 42: MULTISCALE CHARACTERIZATION OF SPAT
Page 43 and 44: Multiscale characterization of spat
Page 45: Multiscale characterization of spat
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Page 59 and 60: CLASSIFICATION OF SITE AND STAND CH
Page 61 and 62: Classification of site and stand ch
Page 63 and 64: Classification of site and stand ch
Page 65 and 66: FUEL MOISTURE CONTENT ESTIMATION: A
Page 67 and 68: Fuel moisture content estimation: a
Page 69: Fuel moisture content estimation: a
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: First steps towards a long term for
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 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
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134 II - VALIDATION OF RS PRODUCTS
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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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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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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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