Dr. ana sebastian (gmv sau) “results of the arc fuel methodology achieved in southern spain”
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  • Arcfuel fuel types over the entire area of study in Spain. Table shows the area and the percentage of the different fuel classes found in the Spanish pilot area. The Table evidences the predominance of a few classes: Coniferous Evergreen Dense (21%) and above all, Shrubs (42%). The non-wildland fuels represent a 17% of the study area. <br />
  • Results are acceptable and particularely satisfactory when related to the discrimination of Evergreen forests. Conversely the discrimination of decidous trees in the classification was not always correct (33% commission error). Nonetheless as observed before the presence of Deciduos vegetation in the pilot area is minor (&lt; 3%). <br />
  • Selection of valid plots <br /> The first step consisted of eliminating the LUCAS sample plots located close to the border between two Arcfuel classes - that is: plots having two or more Arcfuel classes within a circle of 50m radius (pixel size in the classification) centered in the plot. <br /> By deleting these “non-pure” plots we aimed at minimizing the impact of incoherencies among the information sources. <br /> The LUCAS plots that after this filtering still showed some kind of basic incoherence (eg. a plot that according to LUCAS is vineyards, whereas according to the JRC map is a conifer stand, or according to CLC a built up area) where examined one by one for confirmation and then incoherencies were marked also as non valid. <br /> When LUCAS differed from the SIOSE information, priority was given to the latter on account of its higher detail. <br /> Validation <br /> This process consisted of three steps: <br /> A sub-sample of valid LUCAS plots was created, which was free of basic incoherencies with layers used at the root of the fuel mapping process. <br /> For each valid plot the information among the three sources of information (Arcfuel classification, LUCAS, SIOSE+ Vegetation Map) was compared, and correctly classified plots and errors were labeled accordingly. <br /> Basic statistics were derived per ArcFuel fuel type class <br />   <br /> To understand the validation results shown in the next Section it is important to recall that the different datasets handled do not have the same reference date: <br /> SIOSE & Vegetation map integrated product: 2005 <br /> CORINE Land cover: 2006 <br /> JRC Forest Types: <br /> LUCAS: 2009 <br /> Arcfuel classification based on Landsat imagery: 2011 <br /> This fact can particularly affect typically dynamic land covers such as Shrubs and Grasses. <br />
  • Figure 6 below shows an example of a LUCAS plot filtered out according to criteria a): The 50m radius circle drawn around the plot contains two Arcfuel classes: Mixed Forest Evergreen Scrub and Coniferous evergreen Scrub. It is important to recall here that the discrimination between Coniferous and Broadleaves comes from the Forest Types map of the JRC. Likewise the Mixed forest pixels were detected in the process of resampling the original 25m Forest Types map (JRC) to a 50m resolution dataset in order to match the Arcfuel classification resolution (50). This means the value added by Arcfuel’s classification is the discrimination between Evergreen and Deciduous. <br /> Figure 7 below show an example of a plot eliminated according to criteria b): a LUCAS plot in a Shrubland area (without tree cover) falls in a Coniferous forest according to JRC’s Forest Type map (scale effect) and misleading Arcfuel classification. This plot was filtered out from the analysis. <br />
  • Of the 1442 LUCAS plots falling with the study area (Málaga and Córdoba provinces), 1198 were identified as “non-pure” plots and thus were eliminated by using a the 50m radius criterion. Another 73 plots were eliminated on a one-by-one basis. <br /> Note that a higher radius could have been applied and more non-valid plots would have been detected at a time, but it is estimated that this, more conservative, two-steps method prevented us from eliminating an excessive number of plots. <br /> By crossing the classification values with the validation sources (LUCAS and SIOSE) in the remaining 171 valid plots we deduced that 136 of them were correctly classified (80%) and 35 were classification errors (20%). <br /> Table 7 below shows a summary of the classification performance for the Arcfuel classes present in the study area. In accordance with what was observed before about the distribution of the classes in the area, most of the LUCAS plots fall within Arcfuel Shrubs pixels. <br />   <br /> The overall 80% of correctly classified plot is a satisfactory result. The analysis per fuel type class shows particularly good results for the Shrubs (90%) and Coniferous Evergreen Dense class (96%). The plots in the Broadleaves Evergreen Dense class were all correctly classified, but their number is not significant to extract any conclusion. Something similar happens with the plots in Grasses: 12 plots of which 8 (67%) were correctly classified. <br /> Likewise, the plots falling in deciduous classes (incorrectly classified) were not enough in number to draw any conclusion. <br />

Dr. ana sebastian (gmv sau) “results of the arc fuel methodology achieved in southern spain” Presentation Transcript

  • 1. Results of the ArcFUEL methodology achieved in Southern Spain ArcFUEL Final Workshop, 18/12/2013, Thessaloniki “Forest Fires: Fuel mapping in the Mediterranean countries” Ana Sebastián López GMV - Isaac Newton, 11; P.T.M. Tres Cantos, E-28760 Madrid Tel.: +34 91 807 21 00, Email: asebastian@gmv.com ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 18 December 2013, Aristotle University Research Dissemination Center, Thessaloniki, Greece 1
  • 2. GLOBAL SOLUTIONS FOR THE SPACE MARKET GMV INNOVATING SOLUTIONS
  • 3. GENERAL ABOUT GMV  Multinational conglomerate founded in 1984  Private capital  Offices in Spain, Portugal, Poland, USA, Germany, Romania, France, Malaysia, and India  Over 1,000 employees all over the world  Roots tied to the Space and Defense industries  Currently operating in Aeronautics, Space, Defense, Security, Transportation, Healthcare and ICT industries. ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
  • 4. GMV IN THE WORLD Conglomerate of 11 operating subsidiaries and a holding company.  Customers in 5 continents  Permanent staff in 10 countries   SPAIN MADRID – HEADQ. VALLADOLID SEVILLE BARCELONA VALENCIA CANARY ISLANDS LEON ZARAGOZA  PORTUGAL  USA  GERMANY  FRANCE  POLAND  ROMANIA  MALAYSIA  INDIA ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
  • 5. INDUSTRIES         Aeronautics Space Defense Security Healthcare Transportation Telecommunications Public Sector and Corporate ICT ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
  • 6. GMV IN THE SPACE SECTOR SATELLITE GROUND SEGMENT SYSTEMS #1 Worldwide as independent Satellite Control Centre provider to commercial telecom operators  +230 Satellite missions worldwide have used GMV technology  Main European supplier of critical GNSS ground components  #3 as Galileo system developer  CUSTOMERS: Space Agencies  Satellite Operators  Main manufacturers  QUALITY:  CMMI Level 5 ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
  • 7. Results of the ArcFUEL methodology achieved in Southern Spain Study area Data inputs Methods Validation Discussion ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 18 December 2013, Aristotle University Research Dissemination Center, Thessaloniki, Greece 7
  • 8. STUDY AREA SIERRA DE LAS NIEVES  Biosphere Reserve & Natural Biosphere Reserve & Natural Park Park  Western area of Málaga, Western area of Málaga, Andalusia Andalusia  Highest elevation peak at Highest elevation peak at 1919 m 1919 m  AOI covering 20.163 ha AOI covering 20.163 ha ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 8
  • 9. STUDY AREA SIERRA DE LAS NIEVES  Limestone mountains with rugged relief  Spanish fir forests in cool, moist shady areas (botanical relic of the glacial period on the Iberian Peninsula)  Holm oak and cork trees in lower areas, along with some areas of carob and chestnut trees. ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
  • 10. DATA INPUTS      ASTER GDEM Landsat TM5 Corine Land Cover JRC Forest Types and Cover Types Local Land cover & Vegetation data ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 10
  • 11. METHODS A-FUEL TYPE CLASSIFICATION 1. IMAGE PRE-PROCESSING  DEM processing  Atmospheric correction 1. VEGETATION INDICES COMPUTATION 2. CLASSIFICATION B-FUEL PARAMETERS MATCHING ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 11
  • 12. Main classes Main classes A-FUEL TYPE CLASSIFICATION Datasetsource Dataset source Broadleaved Broadleaved JRC Forest type 2006 JRC Forest type 2006 Coniferous Coniferous JRC Forest type 2006 JRC Forest type 2006 Grasses&& Shrubs Grasses Shrubs (Surface fuels) (Surface fuels) EO EO The remaining area after the other main classes areare mapped The remaining area after the other main classes mapped Ground fuels Ground fuels Corine Land Cover Cover Corine Land PeatPeat bogs bogs marshes Salt Salt marshes Salines Salines Azonic fuels Azonic fuels Corine Land Cover Cover Corine Land Interdidal flats flats Interdidal Inland marshes Inland marshes Water courses Water courses Discontinuous urban Discontinuous urban fabricfabric Green urban Green urban areasareas Non-irrigated arable land land Non-irrigated arable EO EO Permanently irrigated Permanently irrigated land land Non w ildland fuels Non w ildland fuels Corine Land Cover Cover Corine Land Vineyards Vineyards Fruit trees and and berry plantations Fruit trees berry plantations Olive groves Olive groves Annual crops associated w ith Annual crops associated w ith permanent crops permanent crops Complex cultivation patterns Complex cultivation patterns Sport leisure facilities Sport and and leisure facilities No fuels No fuels Corine Land Cover Cover Corine Land Agroforestry Corine Land Cover Cover Corine Land Agroforestry No No fuelsfuels Agroforestry Agroforestry ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 12
  • 13. METHODS A-FUEL TYPE –ORIENTED VEGETATION CLASSIFICATION 1-Image pre-processing 1. Mosaic 1ºx1º ASTER GDEM files  New Raster tool of Arcgis 9.3 1. Re-project to UTM WGS84 zone 30 North 2. Merge Landsat TM scenes into a single stack  ENVI “Layer Stacking tool” 1. Generate DEM-derived products  Slope and Aspect (ENVI)  Skyview and Shadow raster (ATCOR) 1. Perform ATMOSPHERIC CORRECTION 2. Perform Landsat mosaic and clip AOI ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 13
  • 14. ASTER Mosaicking Atmospheric correction 14 ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
  • 15. METHODS A-FUEL TYPE –ORIENTED VEGETATION CLASSIFICATION 2- Vegetation indices computation 1. NDVI is calculated for each Landsat-5 TM scene  2nd Feb. & 5th May 2011 1. Image subtraction: [NDVI -NDVIwinter ] summer 3.Image masking: using the land cover classes “Broadleaved”, “Coniferous” and “Mixed Forest” 4.Image masking: using the land cover classes “Shrubs and grasslands”. ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 15
  • 16. METHODS A - FUEL TYPE CLASSIFICATION 3- Image classification ISODATA Unsupervised classification over the difference image Masking:  “Broadleaved”, “Coniferous” & “Mixed Forest”  “Shrubs and grasslands”. [NDVI summer-NDVIwinter ] ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 16
  • 17. METHODS A - FUEL TYPE CLASSIFICATION 3- Refinement  Density cover (JRC cover types map)  Merge of all the produced map layers in a single layer: ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 17
  • 18. Fuel Class ha % Broadleaved Evergreen Scrub 17,63 1,08 Broadleaved Evergreen Open 0,16 0,01 31,90 1,96 Broadleaved Deciduous Scrub 9,98 0,61 Broadleaved Deciduous Open 0,03 0,00 Broadleaved Deciduous Dense 22,52 1,39 Coniferous Evergreen Scrub Coniferous Evergreen Open 55,58 5,57 3,42 0,34 Coniferous Evergreen Dense 340,51 20,95 Coniferous Deciduous Scrub Coniferous Deciduous Open 7,31 0,49 0,45 0,03 Broadleaved Evergreen Dense Coniferous Deciduous Dense 13,64 0,84 Mixed Evergreen Scrub 1,68 0,10 Mixed Evergreen Open 0,01 0,00 Mixed Evergreen Dense 2,11 0,13 Mixed Deciduous Scrub 0,27 0,02 Mixed Deciduous Open 0,00 0,00 Mixed Deciduous Dense 0,41 0,02 Shrubs 682,43 41,98 Grassess 94,64 5,82 Ground Fuels 0,00 0,00 Azonic Fuels 0,18 0,01 Non Wildland Fuels 279,29 17,18 Non Fuel 57,25 3,52 ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 18
  • 19. VALIDATION VALIDATION APPROACH  GIS layers -based validation VALIDATION PLAN: 1ST iteration  validating the discrimination between deciduous and evergreen species. This was done using the field plots from the National Forest Inventory. 2nd iteration  validating the discrimination of vegetation assemblages. This was done using the information on vegetation assemblages contained in SIOSE (1:10.000) and the Vegetation Map of Andalusia (1:10.000). ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 19
  • 20. VALIDATION 1ST iteration  Deciduous VS Evergreen.  3rd National Forest Inventory  Training area  Plots every 1kmx1km  Total of 163 IFN3 plots ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 20
  • 21. VALIDATION 1ST iteration  Deciduous VS Evergreen spp.  3rd National Forest Inventory  Training area  Plots every 1kmx1km  Total of 163 IFN3 plots ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 21
  • 22. VALIDATION 1ST iteration  Shrubs VS Grasslands  3rd National Forest Inventory  Training area  Plots every 1kmx1km  Total of 163 IFN3 plots ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 22
  • 23. VALIDATION 2nd iteration  SOURCES: i) The LUCAS (Land Use / Cover Area Frame Statistical Survey) dataset (2009 campaign)  Multipurpose field survey that estimates the area occupied by different LULC types on the basis of observations taken at more than 250.000 sample points throughout the EU. ii) The Integrated product (1:10.000, 2005)  “SIOSE” (LULC map of Spain) +  “Vegetation map of Andalucía” iii) Aerial orthophotos 2008 ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 23
  • 24. VALIDATION 2nd iteration  The Integrated product (1:10.000) “SIOSE” plus “Vegetation map of Andalucía” (2005) ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 24
  • 25. VALIDATION 2nd iteration A) Selection of valid plots The following LUCAS plots were eliminated   Plots close to 2 or more Arcfuel classes border Plots showing incoherence  examined individually When LUCAS differed from the SIOSE, priority was given to the latter (higher detail). B) Validation 1. Over the sub-sample of valid LUCAS plots 2. For each valid plot the information among the different sources was compared, and correctly classified plots and errors were labeled accordingly. 3. Basic statistics were derived per ArcFuel fuel type class ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 25
  • 26. LUCAS  ArcFUEL LC1 A11 A13 A21 A22 B11 B12 B13 B14 B15 B16 B23 B31 B34 B37 B41 B42 B43 B74 B75 B76 B77 B81 B82 C10 C20 C30 D10 D20 E10 E20 E30 F00 LUCAS LEGEND (LC1) Buildings with 1 to 3 floors Greenhouses Non built up area features Non built up linear features Common wheat Durum wheat Barley Rye Oats Maize Other root crops Sunflower Cotton Other non permanent industrial crops Dry pulses Tomatoes Other fresh vegetables Nuts trees Other fruit trees and berries Oranges Other citrus fruit Olive groves Vineyards Broadleaved forest Coniferous forest Mixed forest Shurbland with sparse tree cover Shurbland without tree cover Grassland with sparse tree/shrub cover Grassland without tree/shrub cover Spontaneously vegetated surfaces Bare land ARCF ID 1 2 ARCFUEL FUEL TYPES Broadleaved Evergreen Scrub Broadleaved Evergreen Open 3 Broadleaved Evergreen Dense 4 Broadleaved Deciduous Scrub 5 Broadleaved Deciduous Open 6 Broadleaved Deciduous Dense 7 8 Coniferous Evergreen Scrub Coniferous Evergreen Open 9 Coniferous Evergreen Dense 10 Mixed Evergreen Scrub OK C10 D10 E10 OK OK- OK C10 D10 E10 OK OK OK C10 D10 B74 OK OK- OK C10 E10 B74 OK OK C10 B74 OK OK C20 D10 OK OK- OK C20 D10 E10 OK C10 OK Coniferous Deciduous Dense 13 OK- Coniferous Deciduous Open 12 OK Coniferous Deciduous Scrub 11 LUCAS CLASSES 14 Mixed Evergreen Open 15 Mixed Evergreen Dense 16 Mixed Deciduous Scrub C20 OK OK C30 D10 OK OK- OK C30 D10 E10 OK C30 OK OK C30 D10 ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 26
  • 27. VALIDATION 2nd iteration steps 1. Selection of valid plots ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 27
  • 28. VALIDATION 2nd iteration   Entire AOI (Córdoba and Málaga)  SIOSE & Vegetation map integrated product: 2005  CORINE Land cover: 2006  JRC Forest Types: 2006  LUCAS: 2009  Arcfuel classification based on Landsat TM scenes: 2011 Correct Classific % classifi errors corre ct Broadleaves 0 1 0% Deciduous Scrub Broadleaves 4 0 100 Evergreen Dense Coniferous % 0 2 0% 25 1 96% 8 98 4 11 67% 90% Deciduous Dense Coniferous Evergreen  Of the 1442 LUCAS plots  1198 were identified as “non-pure” plots and thus were eliminated by using a the 50m radius criterion.  73 plots were eliminated on a oneby-one basis. Dense Grasses Shrubs  Remaining 171 valid plots:  136 of them were correctly classified (80%)  35 were errors (20%). ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 28
  • 29. ARCFUEL FUEL TYPE SCHEME Vegetation description ECOREGIONS 0 Ground fuels Ground fuels ALL 1 Mediterranean grasslands and steppes Grasses 10,11,12,13,14 ,15 2 Northern, Alpine and Temperate grasslands Grasses 1,2,3,4,5,6,7,8, 9 3 Deciduous broadleaved shrubs Shrubs Deciduous ALL 4 Evergreen Mediterranean shrublands Shrubs Evergreen Medium & Dense 10,11,12,13,14 ,15 5 Northern, Alpine and Temperate low shrubs Shrubs Evergreen Medium & Dense 6 Open Mediterranean shrublands Shrubs Evergreen Open (Scrub) 7 Alpine and Northern conifer scrublands Shrubs Evergreen Open (Scrub) 8 Thermophilous broadleaved scrublands Broadleaved Deciduous Scrub 1,2,3,4,5,6,7,8, 9 10,11,12,13,14 ,15 1,2,3,4,5.6,7,8, 9 10,11,12,13,14 ,15 9 Northern broadleaved forests scrublands Broadleaved Deciduous Scrub 10 Deciduous Broadleaved scrublands Broadleaved Deciduous Scrub 6,7,8,9 Broadleaved Evergreen Scrub ALL Coniferous Evergreen Scrub 11,12,15 Coniferous Evergreen Scrub 10,13,14 11 12 Mediterranean sclerophylous forests scrubland Mediterranean montane conifer scrublands 1,2,3 13 Mediterranean conifers scrublands 14 Northern, Alpine and Temperate Final Workshop “Forest Fires: Fuel mapping in ArcFUEL Coniferous Evergreen Scrub 2,3,6,7,8,9 shrublands JRC FUEL TYPE SCHEME Peat bogs Group Ground FT No 1 Wooded peatbogs 2 Mediterranean grasslands and steppes/Pastures/Sparse 3,4,5 grasslands Grasses Temperate, Alpine and Northern grasslands//Pastures/Sparse grasslands 6 Deciduous broadleaved shrublands (thermophilous) 11 Mediterranean moors and heathlands 7 Mediterranean shrublands Shrubs (sclerophylous) 10 Temperate, Alpine and Northern moors and heathlands 8 Mediterranean open shrublands (sclerophylous) 9 Shrublands in Alpine and Northern conifer forests 19 Shrublands in thermophilous broadleaved forests 16 Northern open shrublands in broadleaved forests 18 Shrublands in beech and mesophytic broadleaved forests 17 Shrublands in Mediterranean Transitional sclerophylous forests 14 Shrublands in Mediterranean montane conifer forests 15 Shrublands in Mediterranean conifer forests 13 29 Shrublands in Alpine and the Mediterranean countries” Northern conifer forests 19
  • 30. DISCUSSION This work assessed the performance of the ArcFuel methodology, up to level 4, in the Spanish study area Within the pilot area (Sierra de las Nieves) a first assessment was performed, consisting of comparing Arcfuel classification with the NFI dominant (tree, shrubs and grasses) species.  The 96% of overall accuracy obtained for Deciduous/ Evergreen classification and the 87% of overall accuracy obtained for the Shrubs/ Grassess classification are deemed as very good results. A second assessment was performed within the entire study area at the points marked by the existence of a LUCAS plots.  Approached considered (local sources) containing information on the specific vegetation assemblages, much closer to the concept of forest fuel types. ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 30
  • 31. DISCUSSION Inconsistencies were observed between LUCAS / SIOSE+Vegetation / EU layers defining the first levels of Arcfuel classification  It was decided to proceed with the validation only in those points where consistency existed. Results yielded an overall 80% of correctly classified plot which is a satisfactory performance.  The analysis per fuel type class showed particularly good results for the Shrubs (90%) and Coniferous Evergreen Dense class (96%).  The plots in the Broadleaves Evergreen Dense, and specifically those in deciduous classes (incorrectly classified) were not enough in number to draw any conclusion. Validation was considered very positive, but incomplete without the ffield work (later performed by Meteogrid). ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 31
  • 32. Thank you!! Ana Sebastián Senior Project Manager Remote Sensing Applications and Services Division asebastian@gmv.com GMV Isaac Newton, 11 P.T.M. Tres Cantos E-28760 Madrid Tel. +34 91 807 21 00 Fax +34 91 807 21 99 www.gmv.com ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 32