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

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238 IV - BURNED LAND MAPPING, FIRE SEVERITY DETERMINATION, AND VEGETATION RECOVERY ASSESSMENT (Keeley, 1986), thus affecting the structure of plant communities and causing a decline of long-term ecosystem productivity. The effective manifestation of post-fire succession is determined by a combination of local physical conditions, climatic factors and pre-fire vegetation (e.g. Lloret and Vilà, 2003; Whelan, 1995). In the above-mentioned context, a considerable number of fire recovery studies, based on remote sensing information, have been conducted in regions characterized by Mediterranean climates. In particular, spectral vegetation indices (Röder et al., 2008), namely NDVI, have proven to be especiallty useful to monitor plant regeneration after fire (Díaz-Delgado et al., 2003). 2 - Results The response of vegetation was assessed based on fields of Normalised Difference Vegetation Index (NDVI) as derived from images acquired by the VEGETATION instrument on-board SPOT 4 and SPOT 5. Covering the period 1999-2006, data consist of the S10 products of the VITO database (http://free.vgt.vito.be) at the 1km x 1km spatial scale. Large burnt scars in Portugal during the 2003 and 2005 fire seasons were identified using k-means clustering applied to 12 monthly NDVI anomalies, from September of the year to August of the year after the fire season. As shown in Figure 1, cluster analysis allows identifying two (four) clusters in 2003 (2005). In both years, the centroid associated to systematic negative values of monthly anomalies throughout the year (black circles) is worth being pointed out since the corresponding spatial distributions (Figure 2) correspond to burnt scars (black pixels). Figures 3 and 4 present observed NDVI values over areas corresponding to four selected burnt scars, two of them respecting to the 2003 fire season and the other two to 2005. The locations of the scars are indicated by the red boxes in Figure 2. During the late spring preceding the occurrence of the fire episodes, namely in May 2003 and 2005, all regions present high levels of vegetation activity (left panels of Figures 3 and 4), with values of NDVI around 0.7. Nine months after the fire episodes, in May 2004 and 2006 (middle panels), values of NDVI drop to around 0.35 on average. It may be noted, however, that the spatial distributions of NDVI before the fire season of 2003 present higher values than the ones before the fire season of 2005, in particular over the burnt scar located in the south of Portugal (Figure 3, bottom panel), a feature that relates with the severe drought that hit the country during 2004/2005. A similar behaviour may be observed with the NDVI values after the fire events, which provide an indication of fire sevirity. Again, NDVI after the fire season of 2003 tends to be larger than NDVI after the fire season of 2005. Finally, relative differences between NDVI of May before and after the fire events (left panels of Figures 3 and 4) present higher values in the case of the burnt scars locat-
Assessment of post fire vegetation recovering in Portugal 239 ed in the center of Portugal both fire seasons. The different behavior may be related with several factors, namely fire severity, fire recurrence and land cover types. For instance, according to Corine Land Cover 2000, the two burn scars in 2003 correspond to forested areas (broadleaved in the south and coniferous in the center) whereas, in 2005, the selected areas are mainly degraded lands. References Bond, W.J., Midgley, J.J., 2001. Ecology of sprouting in woody plants: the persistence niche. Trends Ecol. Evol. 16: 45-51. Christensen, N.L., 1994. Fire and soil in Mediterranean shrublands. In J. M. Moreno & W. C. Oechel (Eds.), The role of fire in Mediterranean-type ecosystems (pp. 79-95). New York: Springer. Díaz-Delgado, R., Lloret, F., Pons, X., 2003. Influence of fire severity on plant regeneration by means of remote sensing imagery, Int. J. Rem. Sensing 24 (8): 1751-1763. Gill, A.M., Groves, R.H., Noble, I.R., 1981. Fire and the Australian biota. Australian Academy of Science, Canberra, AU. Keeley, J.E., 1986. Resilience of Mediterranean shrub communities to fire. In Dell, B., Hopkins, A.J.M., Lamont B.B., (Eds.), Resilience in Mediterranean type ecosystems. Kluwer Academic Publishers, 95-112. Lloret, F. 1998. Fire, canopy cover and seedling dynamics in Mediterranean shrubland of northeastern Spain. J. Veg Sci. 9: 417-430. Lloret, F., Vilà, M., 2003. Diversity patterns of plant functional types in relation to fire regime and previous land use in Mediterranean woodlands. J. Veg. Sci. 14: 387-398. Röder, A., Hill, J., Duguy, B., Alloza, J.A., Vallejo, R., 2008. Using long time series of Landsat data to monitor fire events and post-fire dynamics and identify driving factors. A case study in the Ayora region. Rem. Sens. of Environment, 112 (1): 259-273. Trigo R.M., Pereira, J.M.C., Pereira, M.G., Mota B., Calado, M.T., Da Camara C.C., Santo, F.E., 2006. Atmospheric conditions associated with the exceptional fire season of 2003 in Portugal. Int. J. of Climatology 26 (13): 1741-1757. Whelan, R.J., 1995. The ecology of fire. Cambridge University Press, Cambridge, UK.
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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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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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Page 189 and 190: ADVANCING THE USE OF MULTI-RESOLUTI
Page 191 and 192: Advancing the use of multi-resoluti
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Page 196 and 197: 194 III - FIRE DETECTION AND FIRE M
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
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
Page 253: Monitoring post-fire vegetation reg
Page 261 and 262: Abstract: SAR data from a test site
Page 263 and 264: Backscatter properties of x- and c-
Page 265: 6 - Conclusions Backscatter propert
Page 273 and 274: CORRECTION OF TOPOGRAPHIC EFFECTS I
Page 275 and 276: Correction of topographic effects i
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Page 279 and 280: BURNED AREAS MAPPING BY MULTISPECTR
Page 281 and 282: Burned areas mapping by multispectr
Page 283 and 284: Burned areas mapping by multispectr
Page 285 and 286: 4 - Conclusions Burned areas mappin
Page 287 and 288: Abstract: In this paper NDVI VEGETA
Page 289 and 290: 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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