ArcFUEL Density Map based                                               on the FCD Model.                                 ...
Index       FCD Model       Input Data       Data Harmonization       Noise Reduction Process       Indices Computation. S...
FCD Model Developed during ITTO Project PD 32/93 Rev. 2 (F), “Rehabilitation of Logged-over Forests in Asia-Pacific Region...
FCD Model                                                         (A. Rikimaru et al., 2002)                              ...
Input Data Landsat TM (Thematic Mapper) Data:              LT52010352011257MPS00                PRODUCT_TYPE              ...
LT52010352011257MPS00                                                                                      6Arturo Vinué, ...
Input Data MUCVA10 (Andalusian Vegetation Cover and Use Map, 2010) Hierarchical coding of land uses from 4 main types:    ...
Data Harmonization LANDSAT5 TM imagery converted from WGS84 UTM30 to ETRS89 LAEA MUCVA10 converted from ED50 UTM30 (offici...
9Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
Noise Reduction Process Noise defined as an image component which interferes with the proper visual interpretation, such a...
Input Landsat5                                                                                  TM image                  ...
Range Normalization Linear stretching is applied from [min, max] to [0, 255]                                              ...
Advanced Vegetation Index   The Advanced Vegetation   Index is calculated with the   following formula   (Rikimaru et al. ...
Bare Soil Index  The Bare Soil Index is  calculated with the  following formula  (Rikimaru et al. 2002):BI= [(B5+B3)-(B4+B...
Synthesis Model. Vegetation density %                                                                                     ...
Synthesis Model. Vegetation density %Variability components explained byevery component are:611.1514 / (611.1514 + 88.6811...
Synthesis Model. Vegetation Density % Vegetation Density is extracted after rescaling PCA1 as indicated in the figure belo...
Shadow Index (Scaled Shadow Index)   The Shadow Index is   calculated with the following   formula (Rikimaru et al.   2002...
Integration Model (FCD Map)   Integration of VD and SSI   means transformation for   forest canopy density valueFCD = (VD ...
20Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
Dense Forestry Areas                 FCD Map                                   Google Earth                               ...
Dense Shrublands with trees                 FCD Map                                   Google Earth                        ...
Sparse Shrublands with trees                 FCD Map                                   Google Earth                       ...
Grassland with trees                 FCD Map                                   Google Earth                               ...
Dense shrubland without trees                 FCD Map                                   Google Earth                      ...
Sparse Shrubland without trees                 FCD Map                                   Google Earth                     ...
Grasslands                 FCD Map                                   Google Earth                                         ...
Open areas bare or barelyvegetated                 FCD Map                                   Google Earth                 ...
Discussion       Qualitative assessment producing good results       Quantitative assessment to be done. JRC Tree       Co...
Discussion       Shrublands vs Forest based on SSI to be       investigated       Digital Elevation Models to be included ...
References        Center for Earth Observation , University of Yale,        2012. Converting Landsat TM and ETM+ thermal  ...
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03.forest fires 2012_gmv_170523_v2

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03.forest fires 2012_gmv_170523_v2

  1. 1. ArcFUEL Density Map based on the FCD Model. Case study: Sierra de las Nieves (Spain) Forest Fires 2012 ConferenceSession ArcFUEL: Advancing Forest Fuel Mapping techniques in Europe Arturo Vinué, Marta Gómez GMV | Isaac Newton 11 | 28760 Tres Cantos (Madrid), ES T: +34-918-072-100 | avinue@gmv.com mggimenez@gmv.com 3rd International Conference on Modelling, Monitoring and Management of Forest Fires 1 22 – 24 May, 2012, New Forest, UK Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  2. 2. Index FCD Model Input Data Data Harmonization Noise Reduction Process Indices Computation. Synthesis Model Integration Model Discussion References 2 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  3. 3. FCD Model Developed during ITTO Project PD 32/93 Rev. 2 (F), “Rehabilitation of Logged-over Forests in Asia-Pacific Region, Sub-project III” (JOFCA 1991, 1993) Forest status assessed on the basis of canopy density FCD analysis utilizing data derived from four indices: Advanced Vegetation Index (AVI) Bare Soil Index (BI) Shadow Index or Scaled Shadow Index (SI, SSI) Thermal Index (TI) (A. Rikimaru et al., 2002) 3 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  4. 4. FCD Model (A. Rikimaru et al., 2002) 4 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  5. 5. Input Data Landsat TM (Thematic Mapper) Data: LT52010352011257MPS00 PRODUCT_TYPE "L1T" SPACECRAFT_ID "Landsat5" SENSOR_ID "TM" ACQUISITION_DATE 2011-09-14 WRS_PATH 201 STARTING_ROW 35 ENDING_ROW 35 5 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  6. 6. LT52010352011257MPS00 6Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  7. 7. Input Data MUCVA10 (Andalusian Vegetation Cover and Use Map, 2010) Hierarchical coding of land uses from 4 main types: Infrastructures and built surfaces Wetlands and water surfaces Agricultural lands Natural and forest areas 112 cartographical classes 7 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  8. 8. Data Harmonization LANDSAT5 TM imagery converted from WGS84 UTM30 to ETRS89 LAEA MUCVA10 converted from ED50 UTM30 (official reference system in Spain until 2007). Conversion parameters as follows (IGN, 2005): ΔX (m) = -131.032 ΔY (m) = -100.251 ΔZ (m) = -163.354 μ (ppm) = 9.39 Ωx (arc seconds) = 1.2438 Ωy (arc seconds) = 0.0195 Ωx (arc seconds) = 1.1436 8 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  9. 9. 9Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  10. 10. Noise Reduction Process Noise defined as an image component which interferes with the proper visual interpretation, such as, clouds, shadows, water bodies, etc. Three different masks carried out to accomplish further analysis out of the area of interest Water Bodies Clouds Cloud Shadows Water bodies masked out using an ENVI spectral module (LOC – Water) Clouds and Shadows masked out using training areas (parallelepiped and maximum likelihood supervised classifications) 10 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  11. 11. Input Landsat5 TM image Building masks Landsat masked image Pilot Area location Sierra de las Nieves Natural Park MUCVA10 11Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  12. 12. Range Normalization Linear stretching is applied from [min, max] to [0, 255] 12 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  13. 13. Advanced Vegetation Index The Advanced Vegetation Index is calculated with the following formula (Rikimaru et al. 2002):B43 = B4 – B3Case-a: B43 < 0 AVI= 0Case-b: B43 > 0AVI = ((B4 +1) x (256-B3) x B43)1/3 Avanced Vegetation Index 13 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  14. 14. Bare Soil Index The Bare Soil Index is calculated with the following formula (Rikimaru et al. 2002):BI= [(B5+B3)-(B4+B1)] / [(B5+B3) + (B4+B1)] x 100 +100[0 < BI <200] Bare Soil Index 14 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  15. 15. Synthesis Model. Vegetation density % 15 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  16. 16. Synthesis Model. Vegetation density %Variability components explained byevery component are:611.1514 / (611.1514 + 88.6811) =0.8733 ~ 87.3%88.6811 / (611.1514 + 88.6811) =0.1267 ~ 12.7% PCA1 16 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  17. 17. Synthesis Model. Vegetation Density % Vegetation Density is extracted after rescaling PCA1 as indicated in the figure below. Method used is a linear conversion Vegetation Density (%) 17 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  18. 18. Shadow Index (Scaled Shadow Index) The Shadow Index is calculated with the following formula (Rikimaru et al. 2002):SI= ((256-B1) x (256-B2) x (256-B3)) SSI is obtained by linear transformation of SI Scaled Shadow Index 18 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  19. 19. Integration Model (FCD Map) Integration of VD and SSI means transformation for forest canopy density valueFCD = (VD x SSI + 1)1/2 – 1 (Rikimaru et al. 2002) Forest Canopy Density 19 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  20. 20. 20Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  21. 21. Dense Forestry Areas FCD Map Google Earth 21 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  22. 22. Dense Shrublands with trees FCD Map Google Earth 22 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  23. 23. Sparse Shrublands with trees FCD Map Google Earth 23 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  24. 24. Grassland with trees FCD Map Google Earth 24 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  25. 25. Dense shrubland without trees FCD Map Google Earth 25 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  26. 26. Sparse Shrubland without trees FCD Map Google Earth 26 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  27. 27. Grasslands FCD Map Google Earth 27 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  28. 28. Open areas bare or barelyvegetated FCD Map Google Earth 28 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  29. 29. Discussion Qualitative assessment producing good results Quantitative assessment to be done. JRC Tree Cover map use to be investigated Non-fuel masks (urban areas) to be applied to avoid miss-detections Correlations between TI and SSI to be analyzed in order to include temperature information in the process (Black Soil Detection step) More detailed vegetation information to be used for validation 29 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  30. 30. Discussion Shrublands vs Forest based on SSI to be investigated Digital Elevation Models to be included in the process to mask shadows DEM to produce altitudinal profiles in order to characterize shrublands vs forestry 30 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
  31. 31. References Center for Earth Observation , University of Yale, 2012. Converting Landsat TM and ETM+ thermal bands to temperature. Available on: (http://www.yale.edu/ceo/Documentation/Lands at_DN_to_Kelvin.pdf) / Rikimaru, A., Roy, P.S., Miyatake, S.,2002. Tropical forest cover density mapping. Tropical Ecology 43(1): 39-47 Rikimaru, A. and Tateishi, R., 2003. Development of Forest Cover Density Mapping Methodology. Proceedings CEReS International Symposium Remote Sensing, 41-49 31 Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com

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