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256 IV - BURNED LAND MAPPING, FIRE SEVERITY DETERMINATION, AND VEGETATION RECOVERY ASSESSMENT sensor TerraSAR-X ERS ASAR dataset 16 Nov 08/19 Dec 2008 28/29 Mar 96 08 Jan/12 Feb 09 polarization HH HV HH&HV VV HH local inc. angle R 2 R 2 R 2 Std. err. R 2 Std. err. R 2 Std. err. all pseudo-plots 0.631 0.303 0.692 197.7 0.651 153.5 0.435 269.7 pseudo-plots grouped by local incidence angle 10-15 - - - - 0.655 149.9 0.864 132.0 16-20 - - - - 0.662 152.3 0.819 149.3 21-25 0.936 0.768 0.936 101.5 0.746 132.5 0.732 173.4 26-30 0.861 0.551 0.866 126.1 0.741 130.9 0.712 176.7 31-35 0.678 0.368 0.717 178.8 0.735 135.8 0.648 203.1 36-40 0.685 0.380 0.702 175.6 0.743 125.3 0.711 200.3 41-45 0.652 0.381 0.653 197.2 - - - - 46-50 0.732 0.499 0.732 181.0 - - - - 51-55 0.727 0.391 0.748 164.9 - - - - 56-60 0.854 0.594 0.854 140.0 - - - - 66-65 0.862 0.478 0.865 129.2 - - - - Table 1 - Determination coefficients explaining the agreement between burn severity and interferometric coherence. 5 - Discussion Figure 1 shows that coherence increases with burn severity at all frequencies and polarizations. However, noticeable differences in absolute values appear not only between data acquired at different SAR frequencies but also for image pairs acquired with the same system at different time interval. Coherence increased by about 0.25-0.3 units from unburned to highly burnt forests. Regression analysis showed moderate relations between dNBR values and interferometric coherence of co-polarized beams when local incidence angle was not accounted for. Determination coefficients were highest for X-band and one-day C-band data (Table 1). The use of the coand cross-polarized X-band coherence in the regression model did not improve significantly the results. Analysis of dNBR as a function of coherence after grouping by 5 0 local incidence angle intervals showed increased values of the determination coefficients for all frequencies and polarizations. Coherence was affected by topography, decreasing with the increase of the local incidence angle (Figure 2). 6 - Conclusions Interferometric data provided important advantages over the use of backscattering coefficient for burn severity evaluation: i) lower influence
Properties of x- and c- band repeat-pass interferometric sar coherence in mediterranean pine forests affected by fires 257 of topography on the coherence estimates ii) higher determination coefficients obtained for the single-polarized medium spatial resolution ERS data (Tanase et al., 2009b) and iii) no need for multi-polarized datasets. Acknowledgments The work has been financed by the Spanish Ministry of Science and Education and the European Social Fund. ASAR and TerraSAR-X data were provided by the ESA and DLR. References Liew, S.C., Kwoh, L.K., Padmanabhan, K., Lim, O.K., Lim, H., 1999. Delineating Land/Forest Fire Burnt Scars with ERS Interferometric Synthetic Aperture Radar. Geophysical Research Letters, 26: 2409-2412. Tanase, M., Pérez-Cabello, F., de la Riva, J., Santoro, M., 2009a. TerraSAR- X data for burn severity evaluation in Mediterranean forests on sloped terrain. IEEE Trans. Geosci. Remote Sensing, accepted for publication. Tanase, M., de la Riva, J., Pérez-Cabello, F., Santoro, M., 2009b. Backscatter properties of X-, C- and L- band SAR in Mediterranean pine forests affected by fires. In, Advances in RS and GIS Applications in Forest Fire Management Towards an Operational Use of Remote Sensing in Forest Fire management. Matera, Italy: EARSeL. Tanase, M., Santoro, M., de la Riva, J., Pérez-Cabello, F., 2009c. Backscatter properties of multitemporal TerraSAR-X data and the effects of influencing factors on burn severity evaluation, in a Meditteranean pine forest. In, IEEE International Geosicence and Remote Sensing Symposium, IGARSS09. Cape Town, South Africa: IEEE. Wegmüller, U., Werner, C., Strozzi, T., 1998. SAR interferometric and differential interferometric processing. In, IGARSS`98, Seattle, IEEE: 1106- 1108
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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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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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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
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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
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Page 249 and 250: MONITORING POST-FIRE VEGETATION REG
Page 251 and 252: Monitoring post-fire vegetation reg
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Page 263 and 264: Backscatter properties of x- and c-
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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
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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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Page 294 and 295: 292 FORTUNATO G. pag. 191 FRENCH N.
Page 296: Finito di stampare nel mese di agos
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