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

ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”18 December 2013, Aristotle University Research Dissemination Center, Thessaloniki, Greece

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 LópezGMV - Isaac Newton, 11; P.T.M. Tres Cantos, E-28760 Madrid

Tel.: +34 91 807 21 00, Email: [email protected]

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ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”

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ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”18 December 2013, Aristotle University Research Dissemination Center, Thessaloniki, Greece

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Results of the ArcFUEL methodology achieved in Southern Spain

Study areaData inputsMethodsValidation Discussion

ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 8

STUDY AREA

SIERRA DE LAS NIEVES

Biosphere Reserve & Natural Park

Western area of Málaga, Andalusia

Highest elevation peak at 1919 m

AOI covering 20.163 ha

Biosphere Reserve & Natural Park

Western area of Málaga, Andalusia

Highest elevation peak at 1919 m

AOI covering 20.163 ha


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.


DATA INPUTS

10

ASTER GDEM Landsat TM5 Corine Land Cover JRC Forest Types and Cover Types Local Land cover & Vegetation data


METHODS

A-FUEL TYPE CLASSIFICATION1. IMAGE PRE-PROCESSING

DEM processing Atmospheric correction

2. VEGETATION INDICES COMPUTATION3. CLASSIFICATION

B-FUEL PARAMETERS MATCHING


Main classes

Broadleaved

Coniferous

Grasses & Shrubs

(Surface fuels)

Ground fuels Corine Land Cover Peat bogs

Salt marshes

Salines

Interdidal f lats

Inland marshes

Water courses

Discontinuous urban fabric

Green urban areas

Non-irrigated arable land

Permanently irrigated land

Vineyards

Fruit trees and berry plantations

Olive grovesAnnual crops associated w ith

permanent cropsComplex cultivation patterns

Sport and leisure facilities

No fuels Corine Land Cover No fuels

Agroforestry Corine Land Cover Agroforestry

The remaining area after the other main classes are mapped

Azonic fuels Corine Land Cover

Non w ildland fuels Corine Land Cover

Dataset source

JRC Forest type 2006


Main classes

Salt marshes

Salines

Interdidal f lats

Inland marshes

Water courses


Green urban areas



Vineyards


Olive groves

Annual crops associated w ith permanent crops

Complex cultivation patterns





Dataset sourceMain classes



Dataset sourceMain classes

Broadleaved

Coniferous

Dataset source



Main classes

Broadleaved

Coniferous

Grasses & Shrubs

(Surface fuels)


Salt marshes

Salines

Interdidal f lats

Inland marshes

Water courses


Green urban areas



Vineyards


Olive groves

Annual crops associated w ith permanent crops

Complex cultivation patterns




The remaining area after the other main classes are mapped



Dataset source



EOEO

EOEO

A-FUEL TYPE CLASSIFICATION


METHODSA-FUEL TYPE –ORIENTED VEGETATION CLASSIFICATION

1-Image pre-processing1. Mosaic 1ºx1º ASTER GDEM files

New Raster tool of Arcgis 9.3

2. Re-project to UTM WGS84 zone 30 North3. Merge Landsat TM scenes into a single stack

ENVI “Layer Stacking tool”

4. Generate DEM-derived products Slope and Aspect (ENVI) Skyview and Shadow raster (ATCOR)

5. Perform ATMOSPHERIC CORRECTION6. Perform Landsat mosaic and clip AOI


ASTER MosaickingAtmospheric correction

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METHODSA-FUEL TYPE –ORIENTED VEGETATION CLASSIFICATION

2- Vegetation indices computation1. NDVI is calculated for each Landsat-5 TM scene

2nd Feb. & 5th May 2011

2. Image subtraction: [NDVI summer-NDVIwinter ]

3.Image masking: using the land cover classes “Broadleaved”, “Coniferous” and “Mixed Forest”

4.Image masking: using the land cover classes “Shrubs and grasslands”.


A - FUEL TYPE CLASSIFICATION

3- Image classificationISODATA Unsupervised classification over the difference imageMasking:

“Broadleaved”, “Coniferous” & “Mixed Forest”

“Shrubs and grasslands”.

METHODS

[NDVI summer-NDVIwinter ]


A - FUEL TYPE CLASSIFICATION3- Refinement Density cover (JRC cover types map) Merge of all the produced map layers in a single

layer:

METHODS


Fuel Class ha %

Broadleaved Evergreen Scrub 17,63 1,08

Broadleaved Evergreen Open 0,16 0,01

Broadleaved Evergreen Dense 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 55,58 3,42

Coniferous Evergreen Open 5,57 0,34

Coniferous Evergreen Dense 340,51 20,95

Coniferous Deciduous Scrub 7,31 0,45

Coniferous Deciduous Open 0,49 0,03

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

Agroforestry 2,12 0,13

TOTAL 1625,65 100,00


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).


VALIDATION

1ST iteration Deciduous VS Evergreen.

3rd National Forest Inventory Training area Plots every

1kmx1km Total of 163

IFN3 plots


VALIDATION

1ST iteration Deciduous VS Evergreen spp. 3rd National Forest Inventory

Training area Plots every 1kmx1km Total of 163 IFN3 plots


VALIDATION

1ST iteration Shrubs VS Grasslands

3rd National Forest Inventory Training area Plots every

1kmx1km Total of 163

IFN3 plots


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


VALIDATION

2nd iteration The Integrated product (1:10.000) “SIOSE” plus “Vegetation map of Andalucía” (2005)


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) Validation1. 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


LC1 LUCAS LEGEND (LC1)

ARCF ID ARCFUEL FUEL TYPES LUCAS CLASSES

A11 Buildings with 1 to 3 floors

1 Broadleaved Evergreen Scrub OK OK- OK

A13 Greenhouses

C10 D10 E10 A21 Non built up area features

2 Broadleaved Evergreen Open

OK OK- OK A22 Non built up linear features

C10 D10 E10

B11 Common wheat

3 Broadleaved Evergreen Dense OK

B12 Durum wheat

C10 B13 Barley

4 Broadleaved Deciduous Scrub

OK OK OK B14 Rye

C10 D10 B74

B15 Oats

5 Broadleaved Deciduous Open OK OK- OK

B16 Maize

C10 E10 B74 B23 Other root crops

6 Broadleaved Deciduous Dense

OK OK B31 Sunflower

C10 B74

B34 Cotton

7 Coniferous Evergreen Scrub OK OK

B37 Other non permanent industrial crops

C20 D10 B41 Dry pulses

8 Coniferous Evergreen Open

OK OK- OK B42 Tomatoes

C20 D10 E10

B43 Other fresh vegetables

9 Coniferous Evergreen Dense OK

B74 Nuts trees

C20 B75 Other fruit trees and berries

10 Coniferous Deciduous Scrub

B76 Oranges

B77 Other citrus fruit

11 Coniferous Deciduous Open B81 Olive groves

B82 Vineyards

12 Coniferous Deciduous Dense

C10 Broadleaved forest

C20 Coniferous forest

13 Mixed Evergreen Scrub

OK OK C30 Mixed forest

C30 D10

D10 Shurbland with sparse tree cover

14 Mixed Evergreen Open OK OK- OK

D20 Shurbland without tree cover

C30 D10 E10 E10 Grassland with sparse tree/shrub cover

15 Mixed Evergreen Dense

OK E20 Grassland without tree/shrub cover

C30

E30 Spontaneously vegetated surfaces

16 Mixed Deciduous Scrub OK OK

F00 Bare land

C30 D10

LUCAS ArcFUEL


VALIDATION

2nd iteration steps1. Selection of valid plots


VALIDATION2nd 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

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 one-by-one basis.

Correct

classifi

Classific

errors

%

corre

ct

Broadleaves

Deciduous Scrub0 1 0%

Broadleaves

Evergreen

Dense

4 0 100

%

Coniferous

Deciduous

Dense

0 2 0%

Coniferous

Evergreen

Dense

25 1 96%

Grasses 8 4 67%Shrubs 98 11 90%

Remaining 171 valid plots: 136 of them were correctly

classified (80%) 35 were errors (20%).


ARCFUEL FUEL TYPE SCHEME Vegetation description ECOREGIONS JRC FUEL TYPE SCHEME Group

FT No

0 Ground fuels Ground fuels ALL Peat bogs

Ground 1

Wooded peatbogs 2

1 Mediterranean grasslands and steppes Grasses 10,11,12,13,14,15

Mediterranean grasslands and steppes/Pastures/Sparse grasslands

Grasses

3,4,5

2 Northern, Alpine and Temperate grasslands

Grasses 1,2,3,4,5,6,7,8,9

Temperate, Alpine and Northern grasslands//Pastures/Sparse grasslands 6

3 Deciduous broadleaved shrubs Shrubs Deciduous ALL Deciduous broadleaved shrublands (thermophilous)

Shrubs

11

4 Evergreen Mediterranean shrublands Shrubs Evergreen Medium & Dense

10,11,12,13,14,15

Mediterranean moors and heathlands 7 Mediterranean shrublands (sclerophylous) 10

5 Northern, Alpine and Temperate low shrubs

Shrubs Evergreen Medium & Dense

1,2,3,4,5,6,7,8,9

Temperate, Alpine and Northern moors and heathlands 8

6 Open Mediterranean shrublands Shrubs Evergreen Open (Scrub) 10,11,12,13,14,15

Mediterranean open shrublands (sclerophylous) 9

7 Alpine and Northern conifer scrublands Shrubs Evergreen Open (Scrub) 1,2,3,4,5.6,7,8,9

Shrublands in Alpine and Northern conifer forests

Transitional

19

8 Thermophilous broadleaved scrublands Broadleaved Deciduous Scrub 10,11,12,13,14,15

Shrublands in thermophilous broadleaved forests 16

9 Northern broadleaved forests scrublands Broadleaved Deciduous Scrub 1,2,3

Northern open shrublands in broadleaved forests 18

10 Deciduous Broadleaved scrublands Broadleaved Deciduous Scrub 6,7,8,9 Shrublands in beech and mesophytic broadleaved forests 17

11 Mediterranean sclerophylous forests scrubland Broadleaved Evergreen Scrub ALL

Shrublands in Mediterranean sclerophylous forests 14

12 Mediterranean montane conifer scrublands

Coniferous Evergreen Scrub 11,12,15 Shrublands in Mediterranean montane conifer forests 15

13 Mediterranean conifers scrublands Coniferous Evergreen Scrub 10,13,14 Shrublands in Mediterranean conifer forests 13

14 Northern, Alpine and Temperate shrublands

Coniferous Evergreen Scrub 2,3,6,7,8,9 Shrublands in Alpine and Northern conifer forests 19

15 Alpine conifer scrublands Coniferous Evergreen Scrub 1,4,5 Alpine open shrublands (conifers) 12

16 Evergreen Broadleaved forest Broadleaved Evergreen forest ALL

Thermophilous broadleaved forest

Broadleaved

30 Mediterranean evergreen broadleaved forest 29

17 Deciduous Broadleaved forest Broadleaved Deciduous forest 1,4,5,6,7,8,9,10,11,12,13,14,15

Beech forest 32

Mesophytic broadleaved forest 31

Montane beech forest 33 18 Boreal Deciduous Broadleaved forest Broadleaved Deciduous forest 2,3 White birch boreal forest 34

19 Mediterranean Evergreen Conifers Conifers Evergreen forest 13,14,15

Mediterranean long needled conifer forest (mediterranean pines)

Conifers 20

Mediterranean scale-needled open woodlands (juniperus, cupressus) 21

20 Mediterranean and montane evergreen Conifers Evergreen forest 8,9,10,11,12 Mediterranean montane long 22


DISCUSSIONThis 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.


DISCUSSIONInconsistencies 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).


Thank you!!Ana Sebastián

Senior Project Manager

Remote Sensing Applications and Services Division

[email protected]

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

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

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