JST-JICA Project” Wild Fire and Carbon Management in Peat-Forest in Indonesia”

Hokkaido University, The University of Tokyo, JAXAUniversity of Palangka Raya, LAPAN

FOREST FIRE GROUP Current Status & Planning

2010.07.07JPTM Manila

FF-1-3 Met. Modeling and Fire Simulation

FF-1-4 Peat Moisture Estimation

FF-1-1 Fire Detection

Koji NakauMasami TokunoKeiji KushidaSuwarsono, Parwati

Keiji KimuraOrbita Roswintiarti

Wataru TakeuchiNanin Anggraeni

FF-1-5 Fire Information via SMS

Hiroshi TaniHendrik Segah

General Coordination

Hendrik SegahAtsushi OnoOrbita RoswintiartiAswin Usup

FF-1 : Wild/Peat Fire Control System

FF-1-2Wildfire Local ValidationToshihisa HonmaKoji NakauAswin Usup

Kazuya KakuAtsushi OnoOrbita RoswintiartiAswin Usup

FF-2 : Mapping and Modeling the Land CoverHendrik SegahAgus Kristiyono

FF: Fire Detection and Fire Prediction SystemToshihisa HonmaAgus HidayatRatih D. Dimyati

FF2-2 Spectrum Library (plant/soil)

Keiji KimuraAgus KristiyonoKustiyo, Bambang Trisakti

FF2-1 Land Coverage Map

Keiji KimuraTeguh Prayogo

FF2-3 Carbon Budget Estimation

Hendrik Segah

Structure of FF Group

7 Purposes in “Plan of Operation”

Improve fire hotspot algorithm

Estimate carbon emission by biomass burning among different ecotypes

1

2

3

4

5

6

7

Transfer in-situ fire information to each region

Construct prediction model of wildfire occurrence

Construct model of water regime

Make map of land cover /land use change

Establish spectral library ( plant / soil ) in investigation area

The fire hotspot algorithms that suitable with Indonesiawith levels of accuracy

Development of Fire Prediction Model

The biomass burning emissionestimates from different soil (peat and mineral soil) and land cover types

The in-situ fire information(locations and coverage)through the ground-checkingvalidation

Model of water regime(Soil Moisture)

Trainings programsfor the related stakeholder

Land cover /land use biophysical/physiological maps

Detection of land cover / land

use change (quantitative area

estimation)

Establishing of a spectral library(plant / soil) for the investigationarea

Correlation between remote sensing derived land surface spectral parameters with field measurement parameters

Spatial and temporalcarbon budget maps

11 Project OutputsTo develop the fire hotspot algorithmsderived from Terra/Aqua MODIS satellite data

To evaluate the fire hotspot algorithmsthrough local validation

To derive the levels of accuracy of theresulted fire hotspot algorithms

To develop the peat moisture contentthreshold for fire to burn

Mapping of land cover / land useattributes in at the landscape scale bymeans of operationally available satellitedata

To provide Indonesian fire suppressionteams and other stakeholder agencieswith the accurate fire hotspot information

Estimating land use/cover parametersand forest properties at theintermediate and stand scale by meansof new high resolution satellite data

Modeling carbon budget by recovered and growing existing vegetation

FF1-1

FF1-2

FF1-3

FF1-4

FF1-5

FF2-1

FF2-2

FF2-3

Project Activities

FF Group Activities in 2010Activities/Timeline

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Group Meetings15-

SapporoFF Meeting

17-Tokyo

FF Meeting

26-TokyoFF

Meeting

1６-Tokyo

FF Meeting

27-Jakarta

FF Meeting

5-Sapporo

FF Meeting

JST/JICA Project 28-29Workshop

FF-1 Field

travels

JakartaBali & P.Raya

Jakarta, P. Raya, Pare-Pare

Jakarta, P. Raya

FF-2 Jakarta Jakarta, P. Raya

Project Objectives 2009 – 2014 (Mar) Rate of Achievement

1. Improve fire hotspot algorithm ~ 25%

2. Estimate carbon emission by biomass burning among different ecotypes ~ 15%

3. Transfer in-situ fire information to each region ~25%

4. Construct prediction model of wildfire occurrence ~20%

5. Construct model of water regime ~25%

6. Make map of land cover /land use change ~25%

7. Establish spectral library (plant / soil) in investigation area ~25%

Operation Schedule in 2009 (1st year)

• Examination of the system

• Comparison of fire detection methods

• Analysis of parameters in the fire expansion simulation

• Examination of the system transfer from Hokkaido University to LAPAN

• Ground truth

.

Operation Schedule in 2010 (2nd year)

• Making prototype system in Hokkaido University

• Test of mobile terminal (mobile phone or short message service:SMS) for firefighters

• Incorporating fire detection methods into the system

• Incorporating the fire expansion simulation into the system

• Preparation to transfer the system from Hokkaido University to LAPAN

• Ground truth

Terra & Aqua （MODIS）

Analysis

Data storage

Web

Firefightersin Palangka Raya

ALOS（PALSAR/PRISM/

AVNIR2)

Semi-Real time

手動配信

Visualization（GIS）

（Validation）

↓Japan

↑Indonesia

JAXA

Hokkaido Univ.

Step1: Making prototype in JAPAN

↓Indonesia

↑Japan

(automatic)

（on demand）

From 2009 to 2010

Analysis: Fire detection & fire expansion simulation

Matters to consider our systems

1. Transportation of data and information

2. Management and maintenance of the system in Indonesia

3. The corporation with firefighters in Palangka Raya.

4. The mobile terminal for firefighters

5. The relationships with other projects

(1) Transportation of data and information

• LAPAN has the some receivers of MODIS at ParePare in Sulawesi Island and Rumpin in Bogor.

• I heard the high-speed network will be connected to LAPAN at August 2009.

• In order to send data and information from Hokkaido University to LAPAN on real-time, the high-speed internet is needed certainly.

(2) Management and maintenance of the system in Indonesia

• The system will be managed and maintained by LAPAN sustainably after the final year of our project (in 2013).

• We must operate the system in LAPAN from the 3rd year (in 2011). We need buy the hardware and setup it in Indonesia under the rule of JICA-fund.

• Our system is based on the LINUX operating system to operate the data analysis automatically.

• Our system includes the regional meteorological simulation like MM5/WRF. The maintenance is needed.

(3) The corporation with firefighters in Palangka Raya

• Study area is near Palangka Raya.

• We shall often contact the members in Palangka Raya University and the firefighters in the area.

(4) The mobile terminal for firefighters

• Information about the fire prediction is communicated by mobile phone/SMS through internet from LAPAN to the firefighters in Palangka Raya after address matching.

(5) The relationships with other projects

We should think about the relationships with other projects.

Partnership or Competition

• “The Project for Support on Forest Resources Management through Leveraging Satellite Image Information” with JICA and BAPLAN (Forest Planning Agency, Ministry of Forestry)

• Australian Project

• German Project

We will gather above the information.

Project Goals

• FF1 :Construct wild/peat fire controlsystem

• FF2: Mapping and modeling the landcover

Objects of FF-1 Subgroup• FF1-1 To develop the fire hotspot detection

algorithms derived from Terra/Aqua MODIS satellitedata

• FF1-2 To evaluate the fire hotspot detectionalgorithms through local validation

• FF1-3 To derive the levels of accuracy of the resultedfire simulation

• FF1-4 To apply the water regime to the fire predictionand the water level control of canals

• FF1-5 To provide Indonesian fire suppression teamsand other stakeholder agencies with theaccurate fire hotspot information

Structure of

FF1 Subgroup

FF1-1Detection

FF1-3ExpansionSimulation

FF1-4WaterRegeme

FF1-5Fire Alartto FireFIghter

FF1-2GroundObservation

15JAXA EORC, Koji Nakau

We need to set up 5 servers for FF-1- Stable network- Stable electoricity- Safe space

FF1-1 Fire DetectionNew Generation Fire Detection

• Doubled S/N ratio (comparing to MOD14– 80% more HS and & 10% less False Alarm– Smoldering, small fire or slush and burn– Geographical distribution is completely different– Suitable to decide firefighting strategy and confirm extinction

MOD14 Proposed

ASTER false color R:2.24µm G:1.65µm B:0.66µm Y: MOD14 R:Proposed

FF1-2 ValidationLANDSAT7/5 and Ground observation

--- GPS track of observer on Aug 26 2009RGB LANDSAT7 short wave infrared image

Large Active Peat Fire

Active Peat Fire

Active Forest FireWe do not know the apperent temperatures of crown fire and peat fire.

FF1-3 Fire Expan. Simulation

• Simulation Result at 16:00, June25 (after 24 hours run).• The expansion for the very slow expansion mainly to southward is

overestimated. • The rapid expansion toward eastward is underestimated because of the limit

of time step.

FF1-4 Water Regeme

JAXA EORC, Koji Nakau

Example of Thermography Imageof flight observation

RGB IR

UAV (Unmanned aerial vehicle) flight observation andWireless Sensor Network are indispensable as well asground observations.

Objects of FF-2 Subgroup

• FF2-1 Mapping of land cover / land use attributes in atthe landscape scale by means of operationally

available satellite data

• FF2-2 Estimating land use/cover parameters andforest properties at the intermediate andstand scale by means of new high resolutionsatellite data

• FF1-3 Modeling carbon budget by recovered andgrowing existing vegetation

Layers on GIS in FF2

3． Building database

PolygonData

LineData

RasterData

PointData

On the same projectionIt consists of gathering various kinds of distribution data around Palangka Raya, carbonflux data in some points observed by other group, and so on. With GIS analysis, thecarbon inventory will be provided for other groups.

One example: Land cover classification by ALOS/PALSAR imagery around Palangka Raya

• We classified the vegetation into eight categories from theHH and HV polarization of ALOS/PALSAR with theISODATA method which is a kind of the non-trainingclassification.

• We made the land cover maps of three periods: July 9,August 24 and October 9, 2007 around Palangka Raya.

• The POSTEL vegetation is used for the sampling data.• The results are compared with the vegetation map by

SarVision and both classifications are very similar.• This means that the latest vegetation map can be renewed

every 46-day of the ALOS’s repeat cycle.

Changing land covers in the study areaduring recent 10 years

4． Results

May, 1997 July, 2000 Oct., 2007

Page et al.(1997) From PALSER data (our study)LANDSAT ETM+(NDVI)

Results of land cover analysis

We can analyze the land cover every 46-days

with ALOS-PALSAR imagery.

WaterDense forestThin forestThin bushBurnt forestBurnt bushBare groundTown

July 9, 2007 August 24, 2007 October 9, 2007

A study on vegetation classification in tropical area using satellite data

LANDSAT9 June 2001

LANDSAT19 May 2002

LANDSAT5 August 2007

LANDSAT19 May 2008

Legend:

LANDSAT DATA:• 09 June 2001• 19 May 2002• 22 May 2003• 25 June 2004• 31 August 2005• 18 August 2006• 05 August 2007• 19 May 2008

LANDSAT9 June 2001

Legend:

LANDSAT5 August 2007

A Study on vegetation classification in tropical area using satellite data

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22

1

2

Another Example: Estimation of CO2 emission

from Mega-Hectare area

Non-forest (8tC/ha/year emission)413,000ha 1.65MtC

Thin Forest (15-40%)(6tC/ha/year emission)1,670,000ha 10.02MtC

Thick Forest (40%-)(4tC/ha/year emission)19,000ha 0.076MtC

Total: 11.7MtC from 2,100,000haby the soil respirationaround the Mega-Hectare area

Japanese annual emission of Carbon is about 341MtC(2005). This area emits the 3.4% of CO2 from Japan. Original data by POSTEL(2008)

CO2 emission data are

compared with GOSAT

data

Spectrum library(peat & soil)

Dry peat

Wet peat

Imperata cylicdrica

2008

2008

Preliminary results

Green