further developing the products of the italian project pg ... · 2006 2010 daily ndvi daily ewt 16...

International conference on forest fire risk modelling and mapping“Vulnerability to forest fire at wildland-urban interfaces”

Further developing the products of the Italian project

Vulnerability to forest fire at wildland urban interfaces30th Sept. – 2nd Oct. 2013 - Aix en Provence, France

p g p p jSIGRI to meet the requirements for the management

of the forest fires at Wildland-Urban InterfacesG. Lanevea, M. Jahjaha, F. Ferruccib, B. Hirnc, F. Battazzad, L. Fusillia, R. de Bonisaa Università di Roma “La Sapienza” – DIAEE, Rome, Italy – [email protected] Università della Calabria, Department of Earth Sciences, Rends (CS), Italy

IES C lti I t lli f E i t d S it R It lc IES Consulting – Intelligence for Environment and Security, Rome, Italyd Agenzia Spaziale Italiana, Rome, Italy

University of Rome “La Sapienza”

SIGRI SIGRI -- Sistema Integrato di Gestione Rischio IncendiSistema Integrato di Gestione Rischio IncendiSIGRI SIGRI -- Sistema Integrato di Gestione Rischio IncendiSistema Integrato di Gestione Rischio Incendiwww.sigri.it ggA project A project fundedfunded byby the the ItalianItalian SpaceSpace AgencyAgency (ASI)((ASI)(contractcontract n. I/052/08/0) n. I/052/08/0)

ggA project A project fundedfunded byby the the ItalianItalian SpaceSpace AgencyAgency (ASI)((ASI)(contractcontract n. I/052/08/0) n. I/052/08/0)

g

30th Sept. - 2nd Oct. 2013 - Aix en Provence

Introduction - 1SIGRI IntroductionSIGRI, Introduction

The three years SIGRI project (ended in December 2012) is part of the program "Natural and human induced Hazards" that the National Space Plan of ASI (Italian Space Agency) identifies, in the field of E th Ob tiEarth Observation:

Floods: PROSA/OPERA,Landslide: MORFEO,Volcanoes: SRVAir quality: QUITSAT,q yOil spill: PRIMI,Earthquake: SIGRIS,Fires: SIGRI.Fires: SIGRI.

The objective of the project is the development of an integrated decision support system for the civil protection from Forest Fires based on Earth Observation (EO) satellite data protection from Forest Fires based on Earth Observation (EO) satellite data. The reference user, the Italian Civil Protection Department (DPC), has been involved in the consolidation of the system and service requirements, both in the demonstration and validation h l phases on sample areas.


Objectives

1 The SIGRI (integrated system for the management of Forest Fire risk)project concerns the implementation of a demonstration system capableproject concerns the implementation of a demonstration system capableof generating products based on earth observation data (MSG,TERRA/MODIS, HR and VHR optical multispectral data, SAR), integratedwith data from other sources (spatial data, cartographic maps andmore) for supporting the management of the forest fire phenomenon inits different stages before during and after the eventits different stages: before, during and after the event.

2 The products developed in the framework of the SIGRI project respond tod h f f l l lneeds concerning the forest fires management at local, regional or

national level. Hereinafter we intend to analyze the possibility of furtherdeveloping some of the project products to make them suitable for thedeveloping some of the project products to make them suitable for theWUI fire management needs.

.


Strategic products: The products of this level can be considered as "static products" during the entire

Introduction - 2Strategic products: The products of this level can be considered as static products during the entire forest fires risk season. In strategic mode the system can provide products to support the prediction/prevention of the phenomenon:

TIME DEPENDENT FIRE HAZARD MAPSTIME-DEPENDENT FIRE HAZARD MAPSGEOSPATIAL FIRE HAZARD MAPMAPS OF THE BURNED AREAS BASED ON SAR DATAMAPS OF THE BURNED AREAS BASED ON OPTICAL DATAMAPS OF THE BURNED AREAS BASED ON OPTICAL DATAREGENERATION OF VEGETATION MAP

Tactical products: The products of this level can be considered as "dynamic" for the entire forest fires high risk period. The system will generate products useful in the management of current events, by detecting the event, (hotspot detection based on SEVIRI/MSG), by allowing the simulation of fire propagation, by providing the dynamic map of vulnerability:p p g y p g y p y

HOT SPOT DETECTIONFIRE SPREAD SIMULATIONDYNAMICDYNAMIC HAZARDHAZARD MAPMAP (MFPI(MFPI))DYNAMICDYNAMIC HAZARDHAZARD MAPMAP (MFPI(MFPI))

Legislative products:HIGHHIGH RESOLUTIONRESOLUTION MAPSMAPS OFOF BURNEDBURNED AREASAREASHIGHHIGH RESOLUTIONRESOLUTION MAPSMAPS OFOF BURNEDBURNED AREASAREAS


Following SIGRI: PREFER, a GMS FP7 Emergency Project

• PREFER - Space-based Information Support for Prevention and REcovery of Forest Fires Emergency in the MediteRranean Area.

• Project Duration: 3 years• Project Duration: 3 years• Consortium: 8 partners• Total Cost: 2.8 MEuro• EC Contribution: 1 9 MEuro

Information support to recovery /restoration phase

Products• EC Contribution: 1.9 MEuro• Starting date: 1st December 2012.http://www.prefer-copernicus.eu

Post‐fire Vegetation Recovery Map

Burn Scar Map HR, VHR Optical and SAR

Biomass Burning Aerosol Map

3D Fire Damage Assessment Map

Products

Seasonal fuel map

Seasonal fire hazard vulnerability andSeverity Damage Map

Information support to preparadness/prevention phase

Seasonal fire hazard, vulnerability and risk map

Daily fire hazard map

b d f


phase Prescribed fire map

MethodologyMAP OF BURNED AREAS (APF) FROM OPTICAL DATA

9/10

11/1219/20

16/16 17/1920/18

15/15

AlgorithmIt is based on the analysis of the pixels of a Change

MAP OF BURNED AREAS (APF) FROM OPTICAL DATA

6/12

5/8

18/11

13/6

8/5

7/7

14/14

11/13

Detection Map characterized by a decrease in the amount of biomass and /or the vegetation cover.

1/3

4/410/9

8/5

2/2

The pixels of the change detection image, which show reflectance values less than the average values of the reflectances of the pixels

3/1

values of the reflectances of the pixels corresponding to pseudo-invariant or Permanent Reflector (PR) are considered as areas affected by fire fire.

Products description, example: map of change detection with optical data

The product is generated: 3 times/year on the test area Liguria (April June September) twice year for the test area

Map characteristics: Input: Landsat/SPOT/IRS images, Spatial res.: 5 - 30 m, Values: 0 = value for the areas out ofthe ROI, 1 = no-change, 2 = change, 4 = clouds or shadow pixels . Output: geotiff images for the three test regions.

The product is generated: 3 times/year on the test area Liguria (April, June, September), twice year for the test area Sardinia and Calabria (June, September).

, g , g , p p g g g



First image: L5 009/06/2009 Change DetectionChange Detection + APFFinal Image + APF


Final image: L5 28/08/2009


Map of APF from optical and SAR data Product validationMap of APF from optical and SAR data Product validationCalabria, fires having burned an area > 3 ha. APF (in red) compared with in-situ measurement (yellow).

Sardinia, WorldView,image of the 20110819 (MS 2m, PAN 50 cm) .

GPS measurements (white) from Forest


(white) from Forest Corps of the 20110701fire, APF (yellow) .

RGBRGB imageimage RR:: 2011060420110604,,GG:: 2011070620110706,, BB:: 2011080720110807

ChangeChange--DetectionDetection basedbased onon CSKCSK ImageImage2011080620110806 VSVS 2011082220110822..

Map of APF from optical dataMap of APF from optical data Product validationSardinia, fires. APF (in green) compared with in-situ measurement (yellow).

Superimpositionof the GPS based

GPS measurement APF based on Kompsat- 2measurements and the APF based on Kompsat-2Kompsat-2 images (MS 4 m, PAN 1m)


Map of APF from optical dataExample of WUI burned area estimate based on L8 images, August 2013

Map of APF from optical data

Calabria, fires having burned an area > 3 ha.

APF (in red) compared with in-situ measurement (in yellow).

Burned areas smaller than 1 ha are routinely detected.


Methodology Tactical Products description example: Fire hazard index (MFPI)

FPI Burgan 1998MFPI characteristics:Input: NDVI, EWT, E0, Hum, Temp.

Tactical Products description, example: Fire hazard index (MFPI)

FPI Burgan 2000Spatial resolution: 250 m,

Temp. Resolution: 3 hours,

JRC

Temp. Resolution: 3 hours,

Values: 0 - 100, value for the areas out of the ROI -2, cloudy pixels -4.

Output: geotiff images.

Validation: fire occurrences, other indices.

Vegetation water contentTo improve the performance

EvapotranspirationTo take into account the effect of solar illumination indetermining the existing humidity in the died vegetation


MethodologyDaily NDVI EvapotranspirationDaily EWT

NDVI Min (7/8)

MinMin

2006 2010

Daily NDVI EvapotranspirationDaily EWT

16 days

( )

Max (3/4)

MaxMax

RGLR

(3/4) Max

Green veg. fraction

Dead veg. fractionLL

Corine

Fuel

LLFM

DLFMFPI

Fire prob. index

Ext. Mois. fractiong

MXDL

LLueType, Min H MXD

FPI

Temp/humid EMC FM TNFTen hour lag fuel moisture Fraction of ten hour lag fuel moisture


MethodologyHour: 00 Hour: 06 Hour: 12 Hour: 18Hour: 00 Hour: 06 Hour: 12 Hour: 18

Example of FPI Hour: 00 Hour: 12pcomputed every 3 hours on Sardinia and Corsica, day 28 Aug 2013day 28 Aug. 2013


Methodology A Fire hazard index (MFPI) devoted to WUI

Is a MFPI based on High Resolution satellite images(L8, Sentinel-2, etc.) feasible ?

A Fire hazard index (MFPI) devoted to WUI

Spatial resolution

MethodologySummer variability of the NDVI according to MODISSummer variability of the NDVI, according to MODIS

VI maquis

ND

VV

IN

DV

forest

VI

sparsely vegetated pixelsN

DV


Days after 15/06/2010

Th d t lid ti f ll d t h

Results and ValidationThe products validation followed two approaches:statistical (5 years fire data) and deterministic (selection of specific dayscharacterized by many fires)characterized by many fires).

For the validation we usedFPI index (corrispondent index ‘FWI’) of JRC EFFIS projectFPI index (corrispondent index FWI ) of JRC EFFIS projectAIB/AIBFN reportsCOAU Action LoggMODIS and MSG Hot-Spot detection

Statistical: pixels recognized as high-risk follows the general behaviour ofStatistical: pixels recognized as high risk follows the general behaviour offire occurrence. OR a greater number of pixels with high FPI correspondsto a greater number of events;gDeterministic: taking into account individual days; the areas affected bythe fires are mainly those in which the index has assumed higher values.


A fi i i l l i i d b

Validation

80

100

120

140

25000

30000

35000

40000

Serie2

A first statistical analysis was carried out byconsidering a single month of FPI maps (Calabria,July 2007) and the corresponding list of MODIS

0

20

40

60

0

5000

10000

15000

20000 Serie2Serie1FPIHS hot spots. In this figure we can see, as a function

of the days of the July month, the number of hotspots and the number of pixels marked with high

01 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

0p p g

risk of fire (class 5, FPI between 60 and 100).

It’s clear the high correlation between the twoi i h l li i il fiquantities that, at least preliminarily, seems to confirm

the ability of the calculated FPI index in accordancewith written documents (research and algorithmspecification) to capture the variability of the availablevegetation to burn, taking in consideration thevegetation state (dry biomass) and meteorologicalg ( y ) gconditions.

Validation: statistical approachValidation: statistical approachFig. 1 A, gives the daily distribution of fires occurred in Sardinia on August 2011. Fig. 1 B gives the percentage of pixels analyzed with respect the total number corresponding to the whole region. Fig. 1 C reports the total number of pixels FPI > 70 and finally the Fig. 1 D gives the percentage of pixels with FPI > 70 vs the number of analyzed pixels The images show as the number of pixels daily analyzed gives the percentage of pixels with FPI > 70 vs the number of analyzed pixels. The images show as the number of pixels, daily analyzed can vary as consequence of the presence of clouds or invalid pixels in the MODIS image.

This could prevent the id tifi ti f l ti identification of a correlation between the number of pixels with high FPI values and the number of fire events. In fact, ,the number of pixels on which the FPI index has been computed ranges from the 10% t th 70% f th t t l

0.06Percentage of pixels with FPI > 70 vs the computed ones10% to the 70% of the total

number of pixels corresponding to the area of interest.

0.04

0.05

els

FPI >

70

g p p

0.01

0.02

0.03

Perc

enta

ge o

f pix

e

30th Sept. - 2nd Oct. 2013 - Aix en Provence5 10 15 20 25 30

0

0.01

Day of the month

Validation: deterministic approach30

30

Validation: deterministic approach

2011 2010

15

20

25

nth

(Aug

ust 2

011)

MFPI > 60

Clouds

MFPI < 60

20

25

th (A

ugus

t 201

0)

2011

5

10

15

Day

of t

he m

on

Null

5

10

15

Day

of t

he m

ont

MFPI > 60

Clouds

MFPI < 60

5 10 15 20 25 30N. of fire events

5 10 15 20 25 30 35

N. of event

Null

For each event (report of Italian DPC), in a reasonable spatial range, of about ±1 km, we look for pixel having MFPI > 60.Sardinia 08/2010: if in the area of interest is present a pixel with high MFPI (MFPI > 60 box green) or a cloud (box gray) or all pixelsSardinia 08/2010: if in the area of interest is present a pixel with high MFPI (MFPI > 60, box green) or a cloud (box gray) or all pixelshave MFPI < 60 (box red). In 2010 a high percentage of fires occurred in areas having an high hazard index (80% of the events);

In 2011 this percentage results equal to the 45%.

The variability is in agreement with the meaning of MFPI index and with the circumstance that in Italy more than the 90% of the fireevents occur as consequence of the human intervention without which, even in adverse environmental conditions caused by hightemperatures low humidity dry vegetation most likely there would be no phenomenontemperatures, low humidity, dry vegetation, most likely there would be no phenomenon.


V l d d hTable 1 - Shift between the fire occurrence time and the more favorable meteo conditions.

Validation: deterministic approach

Period- year 2011 Same day Day before First forecast day Second forecast day13 - 31 July 36 % 37 % 53 % 53 %1 - 31 August 45 % 43 % 49 % 57 %1 - 15 September 42 % 45 % 49 % 41 %

Region LiguriaPeriod – year 2010 Same day Day before Total num. of events1 - 31 July 35 % 20 % 311 31 July 35 % 20 % 311 - 31 August 50 % 55 % 141 - 15 September 38 % 43 % 11

Region SardiniaPeriod – year 2010 Same day Day before Total num. of events

Table 2 – Relation between the areas interested by fires y y y

15 - 30 June 84 % 86 % 1521 - 31 July 80 % 80 % 3761 - 31 August 81 % 81 % 4921 - 15 September 74 % 80 % 274

the areas interested by fires and the values of the MFPI index.

Regione CalabriaPeriod – year 2010 Same day Day before Total num. of events15 - 30 June 40 % 33 % 61 - 31 July 59 % 54 % 391 - 31 August 44 % 41 % 651 - 15 September -- -- --


Validation

ConclusionsThe SIGRI project funded by ASI ended on December 2012 It was devoted to develop The SIGRI project funded by ASI ended on December 2012. It was devoted to develop satellite based products aiming at supporting the management of the forest fires.

Th l f h f h SIGRI d b bl l d This paper aims to clarify that some of the SIGRI products can be suitably applied to the problem of the management of WUI fires. In fact, the spatial resolution of some of the product is strictly related to the spatial resolution of the used satellite images the product is strictly related to the spatial resolution of the used satellite images and these can be selected in accordance with the requirements without loss of validity of the products itself.

In particular this is true for the products:- burned area estimate;

y p

burned area estimate;- fire hazard index.


further developing the products of the italian project pg ... · 2006 2010 daily ndvi daily ewt 16...

Documents