prof. ioannis gitas (au th) “forest fuel classification and mapping at large scale in mediterran

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

1

Forest fuel classification and mapping at large

scale in Mediterranean Areas

ArcFUEL Final Workshop, 18/12/2013, Thessaloniki“Forest Fires: Fuel mapping in the Mediterranean countries”

Dr. Pericles Toukiloglou, Dr. George Eftitsidis & Prof. Ioannis GitasAristotle University | Faculty of Forestry and Natural Environment |

55143, [email protected]

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

Methodology considerations

Low costApplicable across EuropeEmphasis on Mediterranean ecosystemsMedium spatial resolution (~50m)Results compatible with existing applications & projects (e.g. FUELMAP)

2


Pilot study sitesGreek (Taksiarhis)Italian (Cosenza)Portuguese (Lousã Mountains)Spanish (Sierra de Las Nieves Natural Park)

3


Greek study siteArea: 10400 haAltitude range: 320-1195mClimate: MediterraneanMain vegetation: Trees, Shrubs & Grasses

4


Datasets usedEEA, Corine landcover mapJRC, Forest type mapEFFIS, Forest damage assessment mapsMODIS Vegetation Continuous Fields (collection 5)Ecoregion type mapLandsat TM & ETM+ imagesASTER, GDEM v2

5


Classification schemeCompliance with FUELMAPHierarchical Main classes Seasonal behavior Vegetation density Ecoregion type Full detail

6

ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries” 7

Main class Temporal detail level Vegetation density detail level Ecoregion type detail level Full detail level

Broadleaved forest

Deciduous

Scrub Alpine North

Boreal

Nemoral

Atlantic

North

Alpine South

Continental

Atlantic Central

Pannonic – Pontic

Lusitanian

Anatolian

Mediterranean

Mountain

Mediterranean

North

Mediterranean South

Mediterranean East

Black

Sea

Ecoregion + Scrub Deciduous Broadleaved Forest

Open Ecoregion + Open Deciduous Broadleaved Forest

Dense Ecoregion + Dense Deciduous Broadleaved Forest

Evergreen

Scrub Ecoregion + Scrub Evergreen Broadleaved Forest

Open Ecoregion + Open Evergreen Broadleaved Forest

Dense Ecoregion + Dense Evergreen Broadleaved Forest

Coniferous forest

Deciduous

Scrub Ecoregion + Scrub Deciduous Coniferous Forest

Open Ecoregion + Open Deciduous Coniferous Forest

Dense Ecoregion + Dense Deciduous Coniferous Forest

Evergreen

Scrub Ecoregion + Scrub Evergreen Coniferous Forest

Open Ecoregion + Open Evergreen Coniferous Forest

Dense Ecoregion + Dense Evergreen Coniferous Forest

Mixed forest

Deciduous

Scrub Ecoregion + Scrub Deciduous Mixed Forest

Open Ecoregion + Open Deciduous Mixed Forest

Dense Ecoregion + Dense Deciduous Mixed Forest

Evergreen

Scrub Ecoregion + Scrub Evergreen Mixed Forest

Open Ecoregion + Open Evergreen Mixed Forest

Dense Ecoregion + Dense Evergreen Mixed Forest

Surface fuels Grasses Ecoregion + GrassesShrubs Ecoregion + Shrubs

Ground fuels Ecoregion + Ground fuels

Non Wildland fuels

Ecoregion + Non Wildland fuels

Azonic fuels Ecoregion + Azonic fuels

Agroforestry Ecoregion + AgroforestryBurned areas Ecoregion + Burned areas

No fuels No fuels


Detailed FUELMAP class Basic FUELMAP class Associated ArcFuel classPeat bogs

Ground fuels Ground fuelsWooded peat bogsPastures

Surface fuels Surface fuels

Sparse grasslandsMediterranean grasslands and steppesTemperate, Alpine and Northern grasslandsMediterranean moors and heathlandsTemperate, Alpine and Northern moors and heathlands

Mediterranean open shrublands (sclerophylous)Mediterranean shrublands (sclerophylous)Deciduous broadleaved shrublands (thermophilous)

Alpine open shrub lands (conifers)Shrublands in Mediterranean conifer forests

Transitional forest

Scrub Broadleaved forestShrublands in Mediterranean sclerophylous forests

Shrublands in Mediterranean montane conifer forests

Scrub Coniferous forestShrublands in thermophilous broadleaved forestsShrublands in beech and mesophytic broadleaved forests

Northern open shrublands in broadleaved forestsScrub Mixed forest

Shrublands in Alpine and Northern conifer forestsMediterranean long needled conifer forest (mediterranean pines)

Coniferous forest

Open Coniferous forestMediterranean scale-needled open woodlands (juniperus, cupressus)

Mediterranean montane long needled conifer forest (black and scots pines)

Mediterranean montane short needled conifer forest (firs, cedar)

Dense Coniferous forestAlpine long needled conifer forest (pines)Alpine short needled conifer forest (fir, alp. spruce)

Northern long needled conifer forest (scots pine)Northern short needled conifer forest (spruce)Mediterranean evergreen broadleaved forest

Broadleaved forest

Open Broadleaved forestThermophilous broadleaved forestMesophytic broadleaved forestBeech forest

Dense Broadleaved forestMontane beech forestWhite birch boreal forestMixed Mediterranean evergreen broadleaved with conifers forest

Mixed forest

Open Mixed forestMixed thermophilous broadleaved with conifers forest

Mixed mesophytic broadleaved with conifers forestDense Mixed forest

Mixed beech with conifers forestRiparian vegetation

Other fuels

Non Wildland fuelsCoastal and inland halophytic vegetation and dunes Azonic fuelsAquatic Marshes Burned areasAgroforestry areas AgroforestryNo fuel No fuel No fuel


Data updateUse latest available dataset releaseAssume fire as the primary cause of broad land cover change between official land cover map releasesUpdate land cover datasets for burned areas using the yearly EFFIS forest damage assessment maps

9


Data updateCollect all the EFFIS forest damage assessment maps produced since the release year of the landcover map

10


Data updateAppend the burned areas

11


Data updateConvert the land cover dataset to vector format


Data updateUpdate the vector dataset for burned areasCORINE, update the “Burnt area” classJRC, update the “Non Forest” class


Data updateConvert the updated dataset back to raster format using a majority filterCORINE->50mJRC ->25m


Main fuel classes originating from the JRC forest type map

Broadleaved, Coniferous and Mixed Forest classesAggregate groups of four neighboring 25m pixels to 50m onesThe mixed class is created through the aggregation of both broadleaved and coniferous pixels


Updated forest type map

C C C C

C C B

C B B

C B B B

C B B

C C

M B

M

Forest main classes

Number of 25m resolution pixels Assigned classBroadleaved Coniferous Non

Forest4 0 0 Broadleaved Forest3 0 1 Broadleaved Forest3 1 0 Broadleaved Forest2 0 2 Broadleaved Forest2 1 1 Broadleaved Forest2 2 0 Mixed Forest1 0 3 Non Forest1 1 2 Mixed Forest1 2 1 Coniferous Forest1 3 0 Coniferous Forest0 0 4 Non Forest0 1 3 Non Forest0 2 2 Coniferous Forest0 3 1 Coniferous Forest0 4 0 Coniferous Forest

Aggregation to 50 m

Aggregation rules


JRC Forest type Aggregation


Main fuel classes originating from the CORINE map

ArcFuel main class CORINE class

Ground fuels Peat bogsNon Wildland fuels Discontinuous urban fabric Fruit trees and berry plantations

Green urban areas Olive grovesSport and leisure facilities Annual crops associated with permanent cropsNon-irrigated arable land Complex cultivation patternsVineyards Permanently irrigated land

Azonic fuels Inland marshes SalinesSalt marshes Intertidal flats

Agroforestry Agro-forestry areas Land principally occupied by agriculture, with significant areas of natural vegetation

Burned areas Burnt areasNo fuels Estuaries Dump sites Beaches, dunes, sands Water bodies

Industrial or commercial units

Water courses Road and rail networks and associated land

Continuous urban fabric

Port areas Bare rocks Glaciers and perpetual snow Construction sitesAirports Rice fields Mineral extraction sites Sea and oceanCoastal lagoons


Main fuel classes originating from the CORINE map


Surface fuelsThe area not covered by any of the other classesAssumed to be covered by Grasses and Shrubs


Surface fuels


Conflict resolutionIn case of conflicting main classes over the same area, the class originating from the most recent dataset is retainedIf the conflicting classes originate from equally current datasets, then the class originating from the highest resolution dataset is retained


Temporal refinementCertain main fuel classes contain sub-classes with distinctly different seasonal behavior. The physical properties of these sub-classes differ over different seasons and thus so do their properties as a fuel. The main fuel classes that can be further sub-classified based on their seasonal behavior are: the Broadleaved, Coniferous and Mixed forest fuels, which can

be sub-classified to Deciduous and Evergreen and the Surface fuels, which can be sub-classified to Grasses

and Shrubs


Temporal refinement


Temporal refinementAssumption: Distinctly different seasonal NDVI value differences imply vegetation types with distinctly different seasonal behaviorAssumption: Seasonal NDVI value differences are not affected considerably by factors other than the physical properties of the vegetation


Temporal refinementLandsat images selection rules: Captured recently and during:

Summer Winter

Low cloud cover


Temporal refinementLandsat image pre-processing Calibration Atmospheric correction Cloud and shadow masking Topographic correction NDVI calculation Seasonal NDVI value difference calculation

(summer-winter)


Temporal refinement


Temporal refinementOver areas covered solely by trees, the highest seasonal NDVI value differences should be recorded over Deciduous, and the lowest over Evergreen treesOver areas covered solely by surface fuels, the highest seasonal NDVI value differences should be recorded over Grasses, and the lowest over Shrubs


Temporal refinementHow can the seasonal NDVI value differences, which are neither too high and neither too low, be classified?No optimum set of seasonal NDVI value criteria for distinguishing the classes across Europe Wide in-class variability Wide range of possible image reception dates

Empirical criteria would be costly


Temporal refinementAlternative: use an automated clustering algorithm such as ISODATA to perform an unsupervised classification Two classes Performed over an area covered solely by two vegetation

types with distinctly different seasonal behavior Classified area should be large enough to include both

vegetation types


Temporal refinement


Vegetation DensityVegetation density is an important fuel propertyAt the time, the available data (MOD44B) is restricted to tree forest fuelsThree sub-classes based on vegetation coverage percentage: Scrub (0-10%) Open (10-40%) Dense (40-100%)


Vegetation Density


Ecoregion typeEcoregion type effects fire behaviorImproves the compliance with FUELMAP15 ecoregion types identified over Europe


Ecoregion typeEuropean Ecoregion types

Alpine North

Boreal

Nemoral

Atlantic North

Alpine South

Continental

Atlantic Central

Pannonic – Pontic

Lusitanian

Anatolian

Mediterranean Mountain

Mediterranean North

Mediterranean South

Mediterranean East

Black Sea


Full detailCombine all the available fuel property layers


Full detailVegetation fuel class name Area coverage percentage

Dense Broadleaved Deciduous 15.975%

Dense Broadleaved Evergreen 20.564%

Dense Coniferous Deciduous 0.026%

Dense Coniferous Evergreen 5.585%

Dense Mixed Evergreen 0.128%

Grasses 24.170%

Non Fuels 17.635%

Non Wildland Fuels 0.662%

Scrub Broadleaved Deciduous 5.146%

Scrub Broadleaved Evergreen 4.007%

Scrub Coniferous Deciduous 0.004%

Scrub Coniferous Evergreen 1.078%

Scrub Mixed Evergreen 0.252%

Shrubs 4.770%


Methodology overview

39


DiscussionOptimum Landsat images may be harder to find than originally anticipatedTopographic correction is importantCompositing Landsat images may improve the results


ConclusionsThe proposed methodology can be used to regularly map forest fuel maps suitable for policy making over Europe, at low costThe methodology could be further improved in the future


Thank you

prof. ioannis gitas (au th) “forest fuel classification and mapping at large scale in mediterran

Technology