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Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
3rd International Conference on Modelling, Monitoring and Management of Forest Fires22 – 24 May, 2012, New Forest, UK
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 GómezGMV | Isaac Newton 11 | 28760 Tres Cantos (Madrid), ES
T: +34-918-072-100 | avinue@gmv.com mggimenez@gmv.com
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com2
IndexFCD ModelInput DataData HarmonizationNoise Reduction ProcessIndices Computation. Synthesis ModelIntegration ModelDiscussionReferences
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com3
FCD ModelDeveloped 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 densityFCD 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)
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com4
FCD Model
(A. Rikimaru et al., 2002)
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com5
Input DataLandsat 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
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com6
LT52010352011257MPS00
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com7
Input DataMUCVA10 (Andalusian Vegetation Cover and Use Map, 2010)Hierarchical coding of land uses from 4 main types:
Infrastructures and built surfacesWetlands and water surfacesAgricultural landsNatural and forest areas
112 cartographical classes
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com8
Data HarmonizationLANDSAT5 TM imagery converted from WGS84 UTM30 to ETRS89 LAEAMUCVA10 converted from ED50 UTM30 (official reference system in Spain until 2007). Conversion parameters as follows (IGN, 2005):
ΔX (m) = -131.032ΔY (m) = -100.251ΔZ (m) = -163.354μ (ppm) = 9.39Ωx (arc seconds) = 1.2438Ωy (arc seconds) = 0.0195Ωx (arc seconds) = 1.1436
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com9
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com10
Noise Reduction ProcessNoise 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 BodiesCloudsCloud 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)
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com11
Input Landsat5 TM image
Building masks
Landsat masked image
Pilot Area location
Sierra de las Nieves Natural
Park
MUCVA10
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com12
Range NormalizationLinear stretching is applied from [min, max] to [0, 255]
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
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
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Avanced Vegetation Index
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
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]
14
Bare Soil Index
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
Synthesis Model. Vegetation density %
15
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
Variability components explained by every component are:611.1514 / (611.1514 + 88.6811) = 0.8733 ~ 87.3%88.6811 / (611.1514 + 88.6811) = 0.1267 ~ 12.7%
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PCA1
Synthesis Model. Vegetation density %
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com17
Vegetation Density (%)
Synthesis Model. Vegetation Density %Vegetation Density is extracted after rescaling PCA1 as indicated in the figure below. Method used is a linear conversion
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com
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
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Scaled Shadow Index
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com19
Forest Canopy Density
Integration Model (FCD Map)Integration of VD and SSI means transformation for forest canopy density value
FCD = (VD x SSI + 1)1/2 – 1 (Rikimaru et al. 2002)
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com20
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com21
Dense Forestry Areas
FCD Map Google Earth
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com22
Dense Shrublands with trees
FCD Map Google Earth
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com23
Sparse Shrublands with trees
FCD Map Google Earth
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com24
Grassland with trees
FCD Map Google Earth
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com25
Dense shrubland without trees
FCD Map Google Earth
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com26
Sparse Shrubland without trees
FCD Map Google Earth
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com27
Grasslands
FCD Map Google Earth
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com28
Open areas bare or barely vegetated
FCD Map Google Earth
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com29
DiscussionQualitative assessment producing good resultsQuantitative assessment to be done. JRC Tree Cover map use to be investigatedNon-fuel masks (urban areas) to be applied to avoid miss-detectionsCorrelations 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
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com30
DiscussionShrublands vs Forest based on SSI to be investigatedDigital Elevation Models to be included in the process to mask shadowsDEM to produce altitudinal profiles in order to characterize shrublands vs forestry
Arturo Vinué, Marta Gómez; GMV; T:+34 918 072 100; avinue@gmv.com mggimenez@gmv.com31
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/Landsat_DN_to_Kelvin.pdf) /Rikimaru, A., Roy, P.S., Miyatake, S.,2002. Tropical forest cover density mapping. Tropical Ecology 43(1): 39-47Rikimaru, A. and Tateishi, R., 2003. Development of Forest Cover Density Mapping Methodology. Proceedings CEReS International Symposium Remote Sensing, 41-49
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