FOREST FIRE GROUP Current Status & Planning
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1 JPTM Manila FOREST FIRE GROUP Current Status & Planning JST-JICA Project Wild Fire and Carbon Management in Peat-Forest in Indonesia Hokkaido University, The University of Tokyo, JAXA University of Palangka Raya, LAPAN
2 Structure of FF Group FF-1 : Wild/Peat Fire Control System Kazuya Kaku Atsushi Ono Orbita Roswintiarti Aswin Usup FF-1-1 Fire Detection Koji Nakau Masami Tokuno Keiji Kushida Suwarsono, Parwati FF: Fire Detection and Fire Prediction System Toshihisa Honma Agus Hidayat Ratih D. Dimyati FF-1-2Wildfire Local Validation Toshihisa Honma Koji Nakau Aswin Usup General Coordination Hendrik Segah Atsushi Ono Orbita Roswintiarti Aswin Usup FF-1-3 Met. Modeling and Fire Simulation FF-1-4 Peat Moisture Estimation Keiji Kimura Orbita Roswintiarti Wataru Takeuchi Nanin Anggraeni FF-1-5 Fire Information via SMS Hendrik Segah FF-2 : Mapping and Modeling the Land Cover Hendrik Segah Agus Kristiyono FF2-1 Land Coverage Map Keiji Kimura Agus Kristiyono Kustiyo, Bambang Trisakti FF2-2 Spectrum Library (plant/soil) FF2-3 Carbon Budget Estimation Hiroshi Tani Hendrik Segah Keiji Kimura Teguh Prayogo
3 Purposes in Plan of Operation Improve fire hotspot algorithm Estimate carbon emission by biomass burning among different ecotypes 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 11 Project Outputs The fire hotspot algorithms that suitable with Indonesia with levels of accuracy The biomass burning emission estimates from different soil (peat and mineral soil) and land cover types The in-situ fire information (locations and coverage) through the ground-checking validation Trainings programs for the related stakeholder Development of Fire Prediction Model Model of water regime (Soil Moisture) Land cover /land use biophysical/physiological maps Detection of land cover / land use change (quantitative area Spatial estimation) and temporal carbon budget maps FF1-1 FF1-2 FF1-5 To develop the fire hotspot algorithms derived from Terra/Aqua MODIS satellite data To evaluate the fire hotspot algorithms through local validation To provide Indonesian fire suppression teams and other stakeholder agencies with the accurate fire hotspot information To derive the levels of accuracy of the FF1-3 resulted fire hotspot algorithms FF1-4 FF2-1 Project Activities To develop the peat moisture content threshold for fire to burn Mapping of land cover / land use attributes in at the landscape scale by means of operationally available satellite data Modeling carbon budget by recovered and FF2-3 growing existing vegetation 7 Establish spectral library ( plant / soil ) in investigation area Correlation between remote sensing derived land surface spectral parameters with field measurement parameters Establishing of a spectral library (plant / soil) for the investigation area FF2-2 Estimating land use/cover parameters and forest properties at the intermediate and stand scale by means of new high resolution satellite data
4 FF Group Activities in 2010 Activities/ Timeline Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Group Meetings 15- Sapporo FF Meeting 17- Tokyo FF Meeting 26-Tokyo FF Meeting 16- Tokyo FF Meeting 27-Jakarta FF Meeting 5- Sapporo FF Meeting JST/JICA Project FF-1 Field Jakarta Bali & P.Raya Jakarta, P. Raya, Pare-Pare Workshop Jakarta, P. Raya travels FF-2 Jakarta Jakarta, P. Raya Project Objectives (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%
5 Operation Schedule in 2009 (1 st 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.
6 Operation Schedule in 2010 (2 nd 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
7 Step1: Making prototype in JAPAN Indonesia Japan JAXA Web Semi- Real time Firefighters in Palangka Raya (automatic) 手動配信 Analysis (Validation) Visualization(GIS) Japan Indonesia Terra & Aqua (MODIS) ALOS (PALSAR/PRISM/ AVNIR2) (on demand) Data storage Hokkaido Univ. Analysis: Fire detection & fire expansion simulation From 2009 to 2010
8 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
9 (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 In order to send data and information from Hokkaido University to LAPAN on real-time, the high-speed internet is needed certainly.
10 (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 3 rd 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.
11 (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.
12 (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.
13 Project Goals FF1 :Construct wild/peat fire control system FF2: Mapping and modeling the land cover
14 Objects of FF-1 Subgroup FF1-1 To develop the fire hotspot detection algorithms derived from Terra/Aqua MODIS data FF1-2 To evaluate the fire hotspot detection algorithms through local validation FF1-3 To derive the levels of accuracy of the resulted fire simulation FF1-4 To apply the water regime to the fire prediction and the water level control of canals FF1-5 To provide Indonesian fire suppression teams and other stakeholder agencies with the accurate fire hotspot information satellite
15 Structure of FF1 Subgroup FF1-4 Water Regeme FF1-3 Expansion Simulation FF1-1 Detection We need to set up 5 servers for FF-1 - Stable network - Stable electoricity - Safe space FF1-5 Fire Alart to Fire FIghter FF1-2 Ground Observation JAXA EORC, Koji Nakau 15
16 FF1-1 Fire Detection New Generation Fire Detection MOD14 Proposed ASTER false color R:2.24µm G:1.65µm B:0.66µm Y: MOD14 R:Proposed 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
17 FF1-2 Validation LANDSAT7/5 and Ground observation We do not know the apperent temperatures of crown fire and peat fire. Active Forest Fire Active Peat Fire Large Active Peat Fire --- GPS track of observer on Aug RGB LANDSAT7 short wave infrared image
18 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.
19 JAXA EORC, Koji Nakau FF1-4 Water Regeme
20 Example of Thermography Image of flight observation RGB IR UAV (Unmanned aerial vehicle) flight observation and Wireless Sensor Network are indispensable as well as ground observations.
21 Objects of FF-2 Subgroup FF2-1 Mapping of land cover / land use attributes in at the landscape scale by means of operationally available satellite data FF2-2 Estimating land use/cover parameters and forest properties at the intermediate and stand scale by means of new high resolution satellite data FF1-3 Modeling carbon budget by recovered and growing existing vegetation
22 Polygon Data Layers on GIS in FF2 Line Data Point Data Raster Data On the same projection It consists of gathering various kinds of distribution data around Palangka Raya, carbon flux data in some points observed by other group, and so on. With GIS analysis, the 3. carbon Building inventory database will be provided for other groups.
23 One example: Land cover classification by ALOS/PALSAR imagery around Palangka Raya We classified the vegetation into eight categories from the HH and HV polarization of ALOS/PALSAR with the ISODATA method which is a kind of the non-training classification. 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.
24 Changing land covers in the study area during recent 10 years May, 1997 July, 2000 Oct., Results Page et al.(1997) LANDSAT ETM+(NDVI) From PALSER data (our study)
25 Results of land cover analysis We can analyze the land cover every 46-days with ALOS-PALSAR imagery. Water Dense forest Thin forest Thin bush Burnt forest Burnt bush Bare ground Town July 9, 2007 August 24, 2007 October 9, 2007
26 A study on vegetation classification in tropical area using satellite data LANDSAT 9 June 2001 LANDSAT 19 May 2002 LANDSAT 5 August 2007 LANDSAT 19 May 2008 Legend: LANDSAT DATA: 09 June May May June August August August May 2008
27 A Study on vegetation classification in tropical area using satellite data LANDSAT 9 June 2001 LANDSAT 5 August Legend:
28 Another Example: Estimation of CO 2 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 2,100,000ha by the soil respiration around 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)
29 CO2 emission data are compared with GOSAT data
30 Spectrum library (peat & soil) Preliminary results Dry peat 2008 Wet peat Imperata cylicdrica 2008
31 Green
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