Remote Sensing of forest fires

(focus on Mediterranean ecosystems)

Aristotle University of Thessaloniki

Greece

Laboratory of Forest Management and Remote SensingSchool of Forestry & Natural Environment

http://fmrs.web.auth.gr/

Ioannis Z. Gitas - Associate Professor

Tel: +30 2310 992699, Fax: +30 2310 992677E-mail: igitas@for.auth.gr

Presentation Structure

Mediterranean ecosystems and their characteristics

Forest fires in the Mediterranean

Forest Fire Management related Remote Sensing (and GIS) applications

Mediterranean ecosystems are limited to five relatively small areas around the planet

The Mediterranean forests, woodlands, and scrubbiome can be found in the world's fiveMediterranean climate zones, on the west coastof continents in the mid-latitudes.

Mediterranean ecosystems

The climate is characterized by hot, drysummers and mild, wet winters.

Vegetation types can range from forests towoodlands, savannas, shrublands, andgrasslands.

High biodiversity (uniquely adapted animaland plant species) due to the limited extentand isolation of the Mediterranean climateregions.

Of the most highly altered ecosystems on theplanet due to high human impact (habitation,agriculture, recreation).

Mediterranean ecosystems(characteristics)

› Natural fires are an integral part ofmany terrestrial ecosystemsincluding the Mediterranean.

› However, from the 1960s untiltoday, the general trend in thenumber of fires and surfaceburnings in the EuropeanMediterranean areas has increasedexponentially.

› This increase is mainly due to: (a)changes in traditional land uses, theconsequence of which is higher fuelaccumulation, and (b) globalclimatic warming.

Forest fire statistics for Greece (period 1980-2007)

Forest Fires in the European Mediterranean

Lebanon 2007 Greece 2007 Turkey 2006

Portugal 2005 France 2003 Spain 2006

Italy 2007

Fire, both natural and human-caused, has played a major role inshaping the landscape in the Mediterranean.

Forest Fires (examples from the Mediterranean region)

Forest Fires in Greece(the Peloponnese - August 2007)

Weather patterns Human activities

Topography VegetationSource: Emilio Chuvieco

Forest Fire Factors

A complete fire managementprogramme includes thefollowing:

o pre-fire planning (e.g.creation of fire-breaks,fuel type mapping,topography)

o fire detection andmonitoring (e.g. FUEGOsystem, observatories)

o fire suppression (e.g. useof retardants), and

o post-fire evaluation (e.g.burned area mapping,regeneration mappingand monitoring).

Forest Fire Management

Remotely sensed data and GIS analysis may be used in all phases of afire management programme.

Pre-fire Operations

Post-fire Operations

During fire Operations

Remote Sensing and GIS in Forest Fire Management

Forest Fire Management related Remote Sensing (and GIS) applications

Pre-fire planning

o Vegetation dryness mapping and monitoring

o Fire tower visibility analysis etc.

o Fuel type mapping (eg. ArcFuel)

During fire (assist operations)

o Fire Suppression

Post-fire impact assessment

o Burned area mapping

o Operational Burned Area Mapping at National Level

o Burn Severity mapping

o Short and long term damage assessment

Pre-fire Planning

Vegetation monitoring at

approx. weekly basis

Change detection map

Alexandridis, T.K., Katagis, T., Gitas, I.Z., Silleos, N.G., Eskridge, K.M., Gritzas, G. Investigation of aggregation effects in vegetation condition monitoring at anational scale (2010) International Journal of Geographical Information Science, 24 (4), pp. 507-521.DOI: 10.1080/13658810902798107

Pre-fire planning

Vegetation dryness mapping (MODIS – 250 m)

produced for the period 2002 – 2013 on a weekly basis

Pre-fire planning

Vegetation dryness monitoring (interannual comparison)

Alexandridis, T.K., Gitas, I.Z., Silleos, N.G. An estimation of the optimum temporal resolution for monitoring vegetation condition on a nationwidescale using MODIS/Terra data (2008) International Journal of Remote Sensing, 29 (12), pp. 3589-3607.DOI: 10.1080/01431160701564618

Pre-fire planning

Road network

Map of existing firetowers

Land coverDEM

Visibility map

Fire tower visibility analysis

Pre-fire planning

Estimation of defensible space

Pre-fire planning

› Classification of fuel is a difficult and complexprocess that requires good knowledge ofecology and fire behaviour.

› Fuel type classification is traditionally basedon the use of the, so called, fuel models suchas the:

o Northern Forest Fire Laboratory (NFFL) Fuel Model

o Prometheus fuel model (Mediterranean Basin specific)

o Other (Greek fuel model - Dimitrakopoulos 2001)

› Recent fuel type mapping methods rely on thecombined use of exisitng datasets (e.g. LPIS,CORINE) and remote sensing derivedinformation.

Fuel type classification

Fuel type mapping

PROMETHEUS model - IKONOS imagery

Giakoumakis M., I.Z. Gitas, J. San-Miguel (2002) Object-oriented classification modelling for fuel type mapping in the Mediterranean, using LANDSAT TM and IKONOS imagery- preliminary results, in Viegas, D.X. (ed.), IV International Conference on Forest Fire Research: Forest Fire Research & Wildland Fire Safety, Millpress, Rotterdam, ISBN 90-77017-72-0, p. 66

Resolution 60 cm

Output ready to be used in firebehaviour models such as FARSITE

Mallinis, G., Mitsopoulos, I.D., Dimitrakopoulos, A.P., Gitas, I.Z., Karteris, M. Local-scale fuel-type mapping and fire behavior prediction byemploying high-resolution satellite imagery (2008). IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1(4), pp. 230-239. DOI: 10.1109/JSTARS.2008.2011298

Fuel type mapping

Using Quickbird imagery –Taxiarchis University Forest

A comparative analysis of Hyperion, Quickbird and Landsat TM and imagery for fuel type mapping of a

typical Mediterranean landscape

G. Mallinis, G. Galidaki, I. Gitas, A Comparative Analysis of EO-1 Hyperion, Quickbird and Landsat TM Imagery for Fuel Type Mapping of a Typical Mediterranean Landscape, Remote Sensing 6(2), 1684-1704, 2014.

Fuel type mapping

Fuel type mapping

• ArcFuel is an example of a multi-resolution multi-source mappingapproach.

• The method was recently developed within the frame of the ArcFUELLIFE project (http://www.arcfuel.eu/index.php/en/).

The ArcFuel model

Fuel type mapping

DMC su

mmer

DMC winter

LUCAS points

LPIS-ILOTS

• The NOFFi fuel map is developed on the experience gained fromthe ArcFUEL project.

• The map is produced on behalf of the Greek Forest Service who isfunding the project.

The National Observatory of Forest Fires (NOFFi) fuel map

Fuel type mapping

• Three pilot areas (Chalkidiki, Attiki, Xanthi) are currently used forthe development of the methodology.

• Once the method is checked for its accuracy then will beimplemented in the whole country.

The NOFFi fuel map (current status)

During fire

Fire Suppression

Satellite image-map for fire-fighting resources allocation

Fire Suppression

1. Estimation of vegetation density using image analysis

2. GIS analysis for locating the ‘line of defence’

Planning the ‘line of defence’

Post-fire mapping and monitoring

Burned area mapping

Traditional ways of mapping forest fires

(Greek Forest Service)

Burned area mapping

The starting point for remote sensing research in the field of burned areamapping is the study of the spectral properties of the burned areas, andtheir comparison to other major classes of land cover existing on theimage.

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Burned Area Mapping with Remote Sensing

Burned area mapping

Gitas et al. (2007) Wildfires & Remote Sensing - Fast Mapping Results Provide Deeper Insights, GEOInformatics, October/November 2007,Vol 10, 16-19.

Burned Area mapping using VHR imagery (Parnitha 2007 - IKONOS)

Burned area mapping

Gitas, I. Z., Polychronaki, A., Katagis, T. and Mallinis, G. (2008) Contribution of remote sensing to disaster management activities: A casestudy of the large fires in the Peloponnese, Greece, International Journal of Remote Sensing, 29:6, 1847 – 1853

Burned area mapping and rapid damage assessment

An FMRS - DMC ii - WWF Hellas partnership

Burned area mapping

Mitri, G.H., Gitas, I.Z. A semi-automated object-oriented model for burned area mapping in the Mediterranean region using Landsat-TM imagery (2004) International Journal of Wildland Fire, 13 (3), pp. 367-376. Cited 26 times. DOI: 10.1071/WF03079

Geographic Object-based Image Analysis (GEOBIA)

Operational Burned area mapping

In house developed stand-alone application for the implementation of advanced classification algorithms

Advanced classification techniques in BA (NOFFi)

Dragozi E, Gitas IZ, Stavrakoudis DG, Theocharis JB. Burned Area Mapping Using Support Vector Machines and the FuzCoC FeatureSelection Method on VHR IKONOS Imagery. Remote Sensing. 2014; 6(12):12005-12036.

Burned area mapping

Dragozi E, Gitas IZ, Stavrakoudis DG, Theocharis JB. Burned Area Mapping Using Support Vector Machines and the FuzCoC FeatureSelection Method on VHR IKONOS Imagery. Remote Sensing. 2014; 6(12):12005-12036.

Results from the implementation of the advanced algorithms

Burned area mapping

Gitas et al. (2010) BAS2, An In-House Developed Stand Alone GIS Application For The Estimation Of Burned Area Statistics. 3rdWSEAS International Conference on VISUALIZATION, IMAGING and SIMULATION (VIS '10), 3-5 November 2010, University of Algarve,Faro, Portugal.

Open-source GIS software for damage assessment – Burned Area Statistics (BAS2)

Fire Type mapping

Mitri G.H. and Gitas I.Z. (2006) Fire type mapping using object-based classification of Ikonos imagery. International Journal ofWildland Fire 15, 457-462.

Canopy burn

Surface burn

Forest canopy:

heavily burned?

Living trees in the plot:

scorched?

Vegetationno

no yes

yes

Mapping the type of fire using IKONOS imagery

Burn severity

Burn severity is a descriptive term that integrates the physical, chemicaland biological changes on a site as a result of fire disturbance.

(Jain,2004) FIRE IMPACT ON SOIL AND VEGETATION

Burn severity-Definition

Burn severity

LANDSAT TM images used

before and after the fire.

Estimation of NBR

(Normalized Burned ratio)

index and production of burn

severity map

Veraverbeke et al. (2010) Evaluating Landsat Thematic Mapper spectral indices for estimating burn severity of the 2007 Peloponnesewildfires in Greece. International Journal of Wildland Fire 19, 558–569

Estimation using LANDSAT imagery

Burn severity

LegendVery High

High

Moderate

Low

Estimation using WorldView-2 imagery, GEOBIA and Composite Burn Index (CBI)

(on-going research)

Burn severity field data were collected annually from 100 selected 60X60m plots (November of 2011, August of 2012, November of 2014).

Long-term monitoring

1995 2006

1989 Fire

1985 Fire 1985 Fire

1989 Fire

Legend

Coniferous Forest

Bare Land

Broadleaved Forest

Low Vegetation

Mixed Forest

Shrubs

Polychronaki, A.; Gitas, I.Z.; Veraverbeke, S.; Debien, A. Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using

Object-Based Classification. Remote Sens. 2013, 5, 5680-5701.

Monitoring of burned areas –Synergy of SPOT and RADAR ERS satellite data

Generation of fractional vegetation

cover maps with the use of Spectral

Mixture Analysis (SMA) method.

Veraverbeke et al. (2011) Spectral mixture analysis to assess post-fire vegetation regeneration using Landsat Thematic Mapper imagery:

Accounting for soil brightness variation, International Journal of Applied Earth Observation and Geoinformation, Volume 14, Issue 1, 1-11.

Long-term monitoring

Post-fire vegetation monitoring using LANDSAT data and SMA

Long-term monitoring

Breaks For Additive Season and Trend (BFAST)

Katagis Thomas, Gitas Ioannis Z., Toukiloglou Pericles, Veraverbeke Sander, Goossens Rudi (2014) Trend analysis of medium- andcoarse-resolution time series image data for burned area mapping in a Mediterranean ecosystem. International Journal of Wildland Fire23, 668–677.

Post-fire vegetation monitoring using trend analysis of satellite time series

Long-term monitoring

Mitri G.H. and Gitas I.Z. (2009) Mapping Postfire Vegetation Recovery Using EO-1 Hyperion Imagery, IEEE Transactions on Geoscience andRemote Sensing

Regeneration monitoring- Thasos island

The forest ecosystem succession

assessment is based on the comparison

of the pre-fire and the post-fire land

cover maps within a GIS environment.

Long-term monitoring

Vegetation succession monitoring –Thasos island

The range of RS applications related to forest fires is increasing as a result of the following:

A

• an increase in the number of sensors with different characteristics suitable for studying aspects of fire

B

• an increase in the number of sensors with different characteristics suitable for studying aspects of fire

C

• the development of new advanced digital image analysis techniques

D

• improved access to and availability of satellite data and derived products

Thank you very much for your attention