Post-Fire assessment usingSentinel-2 images in French

Mediterranean area

Office National des Forêts

Yvon Duché, Jean-Luc Kicin, Benoît Reymond, Rémi Savazzi

ONF presentation

ONF (National Forestry Board) is a State Public Body, under the joint supervision of the Ministries of Forestry and the Environment.

ONF is responsible for forest management for both the state and local government, and has a public service remit to help the State and local authorities in protecting forests against fires.

ONF has a specialized agency in the Midi-Mediterranean area to deal with wildfire issues that performs the following tasks:

• Operational - monitoring, detection, first response, support to control activities

• Development and maintenance work - roads, water points, areas cleared of undergrowth

• Expertise support - hazard and fire mapping, fire risk management plans, equipment mapping …

• Project management

Calculation method usingSentinel-2 data

Within these missions, ONF establishes wildfire maps. Sentinel-2 images have been used from 2016 using differenced Normalized burnt Ratio (dNBR) calculation method. This method is based on the different spectral responses of Near InfraRed(NIR) and Shortwave Infrared bands (SWIR) for unburnt/burnt areas.

So

urc

e :

US

DA

Fo

rest

Se

rvic

e

Calculation method usingSentinel-2 data

Example : Rognac fire, 10th of August 2016, 2 655 ha

Post-fire image of 13th of AugustSentinel 2A © ESA 2016 © CNES 2016

Pre-fire image 3rd of AugustSentinel 2A © ESA 2016 © CNES 2016

NBR = ������

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NBR post fireNBR pre fire

dNBR = NBR(pre-fire) - NBR(post-fire)

Fire outline mapping

Result of the dNBR calculation

(raster format) Value > 0.1

Vector conversion

No pixels

shape

generalizing

The dNBR calculation allows a quick fire outline mapping.

Fire outline mapping

• Flat terrain

• Maximum outline difference < 20 m (i.e. pixel size)

• 0.4 % surface difference between GPS record and dNBR map

Aix-en-Provence, 14th of June 2016 Châteauneuf-les-Martigues, 14th of July 2016

• Steep terrain

• 6 % surface difference between GPS/manual cartography (unattainable areas) and dNBR map

Accuracy of fire outline mapping has been validated on different kinds of situations.

Fire outline mapping

Red = false spot / Green = true spot

• dNBR mapping seems accurate for “big” (size/intensity) fires / in most summer conditions in French Mediterranean conditions equivalent to GPS survey

• For big fires it allows a quick mapping of the fire outline

• In steep terrain, dNBR is more accurate than traditional mapping

• dNBR can also contribute to check and map small fire spots (20x20) more rapidly and more efficiently

These tests have shown that :

Fire outline mapping

Detected Undetected

But depending on burn severity and vegetation type, some burnt areas can be missed by the dNBR calculation.

This kind of situations often occur during the winter period when burn severity is lower than during summer time.

Moustiers-Ste-Marie, 22nd of October 2017

Moustiers-Ste-Marie, 22nd of October 2017

Roquefort des Corbières, 6th of September 2017

Fire outline mapping

Therefore, fire outline mapping during winter period must complete dNBR calculation with GPS survey for instance.

Detected

Undetected

Moustiers-Ste-Marie, 22nd of October 2017

In 2017, availability of Sentinel 2B images has reduced the fire mappingdelay.

In Mediterranean area, all fires of 50 ha and over have been mapped. The first one occurred on 24th of March, the last one on 30th of November.

44 fires from 50 to 2263 ha have been mapped using Sentinel images (16280 ha overall i.e. 83% of all burnt areas).

Fire outline mapping

Assessing Post-fire vegetationdamages using severity index

The vegetation burn severity is defined as being the loss of aerial and subterranean organic material due to burning, by combustion or mortality.

The classes of the severity index are defined from US fires, but can be used as first approximation to interpret the dNBR in Mediterranean conditions.

Assessing Post-fire vegetationdamages using severity index

Fields measures on the Rognac fire indicate that :

• For a same severity index, impacts can vary with the type of vegetation in place before fire :• Wooded type (forest) vegetation height > 3m

• Brush type (moor) vegetation height < 3m

• Grass type

• For a same severity index impacts on the vegetation vary with the vegetal cover density

• Test of a composite index mixing both the type of vegetation and of severity index Densité /

couvert de

la

végétation

Sévérité du feu sur la végétation (dNBR)

Faible Moyen Fort

Forêt

Houppier vert ou

légèrement roussi sur la

partie inférieure

(Sous étage et litière

brulée)

Houppier totalement roussi

(présence de quelques

sujets encore vert possible)

Etage arborée

totalement ou

partiellement brulé

(feu de cime)

Arbustif

Faible Végétation totalement brulé

Moyenne Strate arbustive roussie Végétation totalement brulée

Dense Strate arbustive verte et

roussie (en mélange)

Strate arbustive brulée et

roussi (en mélange)

Végétation

totalement brulé

Herbacée Végétation rase

totalement brulée

Végétation haute

totalement brulée

Assessing Post-fire vegetationdamages using severity index

Sentinel-2 images can also be used to qualify the type of damaged vegetation, analyzing pre-fire situation.

Pre-fire image

1 : Incombustible (Minéral, Eau)

2 : Herbacee

3 : Arbustif Dense

4 : Résineux

5 : Feuillus

Image classification

External GIS

databases

1 : Non combustible (mineral eau)

2 : Herbacée

3 : Arbustif dense

4 : Résineux hors IFN

5 : Feuillus hors IFN

6 : Vigne

7 : Verger

8 : Haie

41 : Résineux indifférenciés

42 : Pin Alep

43 : Pin Maritime

44 : Pin Laricio ou Noir

45 : Pin Pignon

51 : Feuillus indifférenciés

52 : Chêne liège

53 : Chêne vert

Pre-fire land cover

Assessing Post-fire vegetationdamages using severity index

Finally, the use of Sentinel-2 images allows a vegetation post-fire damages assessment. They represent a quick and accurate tool to evaluate the risk of potential secondary effects of wildfires.

Pre-fire land cover

Densité /

couvert de

la

végétation

Sévérité du feu sur la végétation (dNBR)

Faible Moyen Fort

Forêt

Houppier vert ou

légèrement roussi sur la

partie inférieure

(Sous étage et litière

brulée)

Houppier totalement roussi

(présence de quelques

sujets encore vert possible)

Etage arborée

totalement ou

partiellement brulé

(feu de cime)

Arbustif

Faible Végétation totalement brulé

Moyenne Strate arbustive roussie Végétation totalement brulée

Dense Strate arbustive verte et

roussie (en mélange)

Strate arbustive brulée et

roussi (en mélange)

Végétation

totalement brulé

Herbacée Végétation rase

totalement brulée

Végétation haute

totalement brulée

Non Combustible

Vignes parcourue

Verger parcourue

Haie brulée

herbacée brulée

Arbustif dense vert en mélange avec roussi

Arbustif dense roussi

Arbustif dense totalement brulé

Chêne liège parcouru encore verts

Chêne liège roussis

Chêne liège totalement brulés

Post-fire

damages

assessment

Arbustif dense vert en mélange avec roussi

Feuillus Indifférenciés parcouru encore verts

Feuillus Indifférenciés roussis

Feuillus Indifférenciés totalement brulés

Feuillus hors IFN parcouru encore verts

Feuillus hors IFN roussis

Feuillus hors IFN totalement brulés

Pin Alep parcouru encore vert

Pin Alep roussis

Pin Alep totalement brulés

Pin Maritime parcouru encore vert

Pin Maritime roussis

Pin Maritime totalement brulés

Pin Pigon parcouru encore vert

Pin Pignon roussis

Pin Pignon totalement brulés

Résineux Indifférenciés parcouru encore vert

Résineux Indifférenciés roussis

Résineux Indifférenciés totalement brulés

Résineux hors ifn parcouru encore vert

Résineux horsIFN roussis

Résineux hors IFN totalement brulés

Burn severity

Conclusion

Sentinel-2 has brought a great change in extended wildfire mapping thanks to good :

• revisit delay

• resolution

• available bands

It doesn’t replace draft operational cartography but allows to draw the final map accurately with limited field checking.

Some post-fire damages can also be come up to.

This assessment would need complementary data bases (soil) to evaluate the erosion and floods risk.

Further work on images has to be made from now on to evaluate vegetation regrowth within 2017 burnt areas.