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U.S. - Japan - SE Asia Workshop on Monsoon Asia Tropical Forest Carbon Dynamics and
Sustainability
SummaryAlfredo R. Huete, Univ Arizona
Xiangming Xiao, Univ. Oklahoma
Scott R. Saleska, Univ. Arizona
Dennis Dye, JAMSTEC, Japan
Nobuko Saigusa, NIES, Japan
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WORKSHOP OBJECTIVES“Basic” Objectives
• Facilitate/enhance international communication among researchers/students concerning Monsoon Asia tropical forest carbon dynamics and sustainability
• Survey of recent/ongoing/planned research activities and results in tropical Monsoon Asia, reports from other regions (Amazon, etc.)
• Identify key science questions and research priorities (including societal benefits), particularly those that require integrated approaches (field observations, process modeling, remote sensing)
Workshop on Monsoon Asia Tropical Forest Carbon Dynamics and SustainabiityJanuary 8-11, 2009, Khon Kaen, Thailand
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Potential Objectives
• Plan/proposal for new international research collaborations
• A framework for addressing the science questions and research priorities, for example:
• simple: individual, ad hoc projects
• ambitious:
• substantial bilateral/multilateral project(s)
• broad, “umbrella” mission (similar to STORMA, GAME, LBA?)
• basis for seeking research support from respective funding agencies
Workshop on Monsoon Asia Tropical Forest Carbon Dynamics and SustainabiityJanuary 8-11, 2009, Khon Kaen, Thailand
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Potential Objectives, cont.
• Outline or “scope” specific project(s) that:
• can be conducted effectively within our proposed framework
• targets the key science questions and research priorities
Workshop on Monsoon Asia Tropical Forest Carbon Dynamics and SustainabiityJanuary 8-11, 2009, Khon Kaen, Thailand
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Broader Impacts: Tropical forest regions have social, cultural and economic significance, as home to large and growing human populations and as sources of important renewable and non-renewable resources.
This workshop will address a number of challenging, cross-discipline research topics integrating in-situ observations, remote sensing, land use, and modeling approaches to advance our understanding of tropical forests and their sustainability in the face of increasing human and environmental pressures.
These issues are among the research and educational priorities identified by the 11th Japan-U.S. Workshop on Global Change in 2005 and this proposal is in response to recommendations for Japan-U.S. joint research that emerged from the Workshop.
Workshop on Monsoon Asia Tropical Forest Carbon Dynamics and SustainabiityJanuary 8-11, 2009, Khon Kaen, Thailand
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Workshop encompassed a few key themes, structured around a set of
motivating science questions;
(1) What can we learn about Monsoon Asia tropical forest functioning by integrating ground-based carbon flux datasets spanning a range of vegetation conditions and climate?
(2) How can we use local site carbon fluxes to scale to and calibrate spatially extensive satellite data to enable regional modeling and prediction of carbon fluxes across Monsoon Asia?
(3) What is the role, extent, and effects of human interactions (land use activities, resource use, forest disturbance and conversion, etc.) on landscape functioning and sustainability?
(4) What is the seasonality of carbon and water fluxes in Monsoon Asia forests, how do they compare with seasonal patterns in the neotropics, and why is this seasonality so difficult to model?
(5) What role do environmental controls on seasonality have in explaining vegetation dynamics in response to inter-annual climate variability.
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field trip
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Asian Institute of Technology
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• Previous answer: photosynthesis and/or transpiration decline in dry seasons:
Dickenson & Henderson-Sellars (1988)
Nobre et al. (1991)
Tian et al. (1998) [TEM]
Botta et al. (2002) [ IBIS]
Werth & Avissar (2002) [ GISS GCM ]
Lee et al. (2005) [ NCAR CLM]
Climate and/or ecosystem models
What is the seasonality of ecosystem
metabolism in Amazônia?
Saleska
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Early LBA results from Tapajos National Forest showed unexpected seasonality…
Jan Apr Jul Oct
500
1000
1
2
3
Models
Data
GP
P (
Mg
C h
a-1
mo
-1)
PA
R
(µm
ol m
-2 s
-1)
Dry Season
(GPP = Gross Primary Production)
Saleska et. al. (2003) Science; Hutyra et al. (2007) JGR
What is the seasonality of ecosystem
metabolism in Amazônia?
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• … generality of unexpected seasonality
confirmed for equatorial Amazon by
remote sensing.
• These data are powerful suited for vegetation dynamics and for deriving relationships between carbon fluxes and key driving variables.
• Use to test model/remote sensing estimates of carbon exchange and seasonality.
Green-up Brown-down
EVI was well correlated with tower-flux GPP in intact rainforest and pasture sites and provides a useful tool for models in scaling this flux to the Amazon region.
Huete et al. GRL 2006
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Seasonal Cycle Shapes Amazon’s
Response To Environmental Change
… generality of unexpected
seasonality confirmed for
equatorial Amazon
by remote sensing.Huete et al. (2006)
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!EVI
Basin-wide greening in dry season October EVI (dry season) minus June EVI (wet season)
!Questions" Is this typical across the Amazon? If not, what are the differences?
" What mechanisms matter for controlling seasonality of metabolism?
" How do we get the models right for the right reasons?
Santarem PastureTapajos Forest
Huete et al. GRL 2006
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0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
EV
I
Start of Dry Season (rainfall <100 mm/month)
Cerrado
Tropical rainforest
Amazon transitional ecosystems (Ecotones)
Ratana et al.
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NOAA- Advanced Very High Resolution Radiometer (AVHRR) in the Amazon
rainforest drying?
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Month of Year
AV
HRR
- N
DV
I (2
0 y
ear)
0
50
100
150
200
250
300
350
400
Prec
ipit
atio
n, m
m (
20
yea
r)
Brasilia Araguaia-1 Araguaia-2 Tapajos
Brasilia, precip Araguaia, precip. Tapajos, precip
Precip.
Dry season
Not only models, but
also satellite vegetation
data products show
inconsistent patterns of
seasonality and
“vegetation responses”
to drought and
disturbance.
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Phenology peak
month
Huete et al.,
2008
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Huete et al.,
2008
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Satellite Enhanced Vegetation Index (EVI) relationships with eddy covariance tower measurements of gross primary productivity (GPP) are very high and linear, with consistent cross-site relationships in temperate and tropical biomes. (Huete et al., Agric. & For. Met., 2008).
- this greatly facilitates the scaling and extension of tower data of ET and Carbon fluxes to regional and global scales. Huete et al.,
2008
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Scott R. Saleska Luis Gustavo de Goncalves, Ian Baker, Marcos Costa, Ben Poulter, Brad Christoffersen, Scott Denning, Humberto da Rocha, Kamel Didan, Lindsey Gulden, Alfredo Huete, Kazuhito Ichii, Hewlley Imbuziero, Akihiko Ito, Bart Kruijt, Antonio Manzi, Celso von
Randow, Natalia Restrepo-Coupe, Enrique Rosero, Rodrigo da Silva, Julio Tota, Xubin Zeng
Seasonality of carbon and water fluxes across the Amazon basin: synthesizing results from remote
sensing, towers, and models: the LBA-MIP project
Saleska
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The LBA-Model Intercomparison Project (LBA-MIP)
Initial Results
#Focus on 3 sites:- Central Eastern Amazon Forest (Santarem K67)- Southern Amazon forest (RJA)- Non Amazon Cerrado (Savanna) (PDG)
#Focus on 4 models:
Caxiuana
São Gabriel
Cachoeira
Sinop
Equator
10 ° S
20 ° S
Amaz ô nia
(A) Atlantic Ocean
Caxiuana
São Gabriel
Cachoeira
Sinop
Equator
10 ° S
20 ° S
Amaz ô nia
(A) Atlantic Ocean
Equator
10 ° S
20 ° S
Equator
10 ° S
20 ° S
(A) Atlantic Ocean
(K67)
(RJA)
(PDG)
- 2 variants of NCAR’s Community Land Model (CLM): (CLM3, CLM3.5)
-Integrated Biosphere Simulator (IBIS) (Foley et al)-Simple Biosphere, ver 3 (SiB3)
# Focus on Evapotranspiration Saleska
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1.Finish the LBA-MIP! (model runs collated, then jointly analyzed, special issue of Ag. Forest Meteorology)
2.LBA-MIP, phase 2: Large-scale, spatially continuous driver and model output fields
3.Beyond seasonality: ability to correctly model effects of interannual variation, such as ENSO response, and ultimately, climate change
4.Generalize: apply similar integrated approach to Asian tropical forests to better understand similarities and differences?
Future directions
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Saleska, Didan, Huete, Rocha (2007), Science
Forests green-up in during 2005 Amazon drought
[Resilience]
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Little is known regarding the resilience of tropical forest
ecosystems to increasing human pressures and climate
variability, despite the large consequences to carbon cycling,
fires, ecosystem services, and the socioeconomic welfare of
the region. Curran et al. (Science, 2004) found strong linkages of ENSO
events on tropical forest functioning in the Kalimantan rainforests of Borneo, in which intact rainforests were able to survive ENSO events, however, disturbed areas became drought susceptible, triggering widespread fires and a drastic reduction in the regenerative capacity of the rainforests.
The combination of land use pressures with climate variability
may result in forest collapse,
Disturbance & Land Use Pressures
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Mekong Region Economic Corridor Development
Figure 2. Development of economic corridors. All weather paved road infrastructure as
of 1992 (A); 2006 (B); and planned for 2015 (C).
1992 2006 2015
Little is known regarding the resilience of Monsoon Asia tropical ecosystems to increasing human pressures and climate variability, despite the large
consequences to carbon cycling, fires, ecosystem services, and the socioeconomic welfare of the region.
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!"#$"%&'(%&)%(*+,-.&/(%"0$&1,+"#,"2&3.(4-.&5%(6%-7&('&)%(*+,-.&/(%"0$&1,+"#,"&8&9(#+$(%+#6
::&*.($0&+#&;<&,(=#$%+"0>&?&7+..+(#&$%""0&7(#+$(%"@ Shirley Dong
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Smithsonian Global Forest Carbon Research Initiative
Quantifying and explaining variation in carbon pools and fluxes in tropical and temperate forests
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Objective 1: Quantify current forest carbon pools
- Tree trunks and branches (~40-50%)
- Woody necromass (~5-10%)
- Soil and fine roots (~30-40%)
- Liana (~1-3%)
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Objective 2: Quantify major forest carbon fluxes
- Annual tree growth and mortality rates
- Litter fall: leaf, fruit, flower production
- Soil respiration: below-ground production and allocation
- Input and output of coarse woody debris
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Objective 3: Investigate the mechanisms
- Meteorological monitoring: temperature, rainfall, humidity, wind speed and direction, solar insolation
- Soil characterization: structure, fertility, water-holding capacity
- Plant functional traits: wood specific gravity, mature height, leaf size, seed mass
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• Huai Kha Khaeng Wildlife Sanctuary, Thailand
• Khao Chong Wildlife Refuge, Thailand
• Pasoh Forest Reserve, Peninsular Malaysia
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U.S. Department of the InteriorU.S. Geological Survey
Cloud-induced Dynamics ofGlobal and Diffuse PARat a Moist Tropical Site:Implications for Forest Photosynthesis
Dennis G. Dye
USGS Southwest Geographic Science Center
Flagstaff, Arizona
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Building an Asian network of PAR sensors through international collaboration
Phimai, Thailand
Putussibau,
Indonesia,Pontianak,
Indonesia
Sapporo, Japan,
Haibei, China
Ulanbator, Mongolia (planned)
Lambir Hills, Malaysia(potential)
Yokohama, Japan (planned)
Tsukuba, Japan (planned)
Coincident with CO2 flux towers
on opportunity basis
Sulawesi, Indonesia(potential)
Sumatra, Indonesia(potential)
Central Kalimantan(potential)
Chiang Mai, Thailand(potential)
Balikpapan,
Indonesia
Dennis Dye
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Putussibau Observation Site" Delta-T BF3 sensor
" total (global) & diffuse PAR (!mol m-2 s-1)
" 1-min. interval
" 15 days (14-28 Mar 2007)
Dennis Dye
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Sample Images (natural color) from prototypeHDR-SISrgb for PAR at Putussibau, W. Kalimantan
Dennis Dye
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Current SE Asia flux towers and research in tropical forests and peatlands
Takashi Hirano (Hokkaido Univ., Japan)
Kohn Kaen, January 9-11, 2009
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1. Kog-Ma2. Mae Moh3. Mae Klong4. Sakaerat5. Pasoh6. Lambir7. Palangkaraya18. Palangkaraya29. Palangkaraya310.Bukit Soeharto(interruption)11.Kampong Chhnang12.Kampong Thom
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Takashi Hirano
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Environmental conditions of tropical forest in SE Asia
• Large variability in precipitation pattern (ENSO) • Land-use change (plantation, oil palm, rubber et al.)• Large-scale fires and haze (smoke) in El Niño years
Kuala Lumpur (Sep. 2005)Sep. 1997
Networking tower sites
Synthesis researches on:" Geographical distribution of CO2 flux (Fc) and
evapotranspiration (ET)" Seasonal and inter-annual variations in Fc and ET" Controlling factors of variations in Fc and ET
Kalimantan (Sep. 2002)
Haze
Takashi Hirano
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Tropical peatland in SE Asia
"In SE Asia, pealtlands are widely distributed in the area of 270,000 km2, which accounts for about 10% of total land area there.
"The carbon stored in tropical peatland soil of Indonesia is estimated at 55±10 Pg (Jaenicke et al., 2008).
"Although tropical petalands naturally coexists with swamp forest, the peatlands have been deforested at 1.5% every year. The area of 120,000 km2 has been already deforested and drained (Hooijer et al., 2006).
Distribution of tropical peatlands in SE Asia (Page et al., 2004)Takashi Hirano
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Tower in DF
Large canal for drainage
Tower in UDF
Takashi Hirano
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BC site• Drained and deforested in the mid-1990’s.• Regrowing vegetation and surface peat soil were
burnt twice in 1997 and 2002 (El Niño years).
Vegetation recovery
April 2004 December 2004
March 2008Takashi Hirano
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Forest Carbon Monitoring Program
Yoshiki Yamagata [email protected]
Hozuma Sekine : [email protected]
Workshop onMonsoon Asia Tropical Forest Carbon Dynamics and SustainabilityJANUARY 8 to 11, 2009, KHON KAEN, THAILAND
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Yoshiki Yamagata [email protected]
Hozuma Sekine : [email protected]
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Subtropics Limit (+/- 35 deg)
Country Eligibility of REDD
GLC2000 Yoshiki Yamagata [email protected]
Hozuma Sekine : [email protected]
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Subtopic 2 [Shimada JAXA]Analysis of SAR Images
Subtopic 4 [Oguma NIES]Estimating Forest Structure
Parameters using Microwave
Subtopic 5 [Takeuchi UoT]Using Remote Sensing to Understand
Vegetation Disturbance
Subtopic 3 [Sekine MRI]Analysis of Forest Inventories
Su
bto
pic
1[Y
am
ag
ata
NIE
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De
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lop
ing
Ca
rbo
n A
cc
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g M
eth
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sTop-down approach(Region & Country Level )
Bottom-up approach(Plot & Site Level)
Subtopic 6 [Ito NIES]Evaluating Carbon Balance
with Ecosystem Models
Development of SARMosaic Dataset
Forest Carbon Monitoring Approach
Yoshiki Yamagata [email protected]
Hozuma Sekine : [email protected]
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South-East Asia Mosaic Dataset 1 (PALSAR;50m)
FBD 34.3 HH / HV, R=HH, G=HV, B=HH-HV
http://www.eorc.jaxa.jp/ALOS/kc_mosaic/kc_mosaic.htm
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Task main activities (in brackets potential contributors)a. Consolidation of observational requirements and associated products (NIES, JRC,
WHRC)
b. Coordinated assessment of tools and methodologies (GOFC-GOLD, JRC, WHRC)
c. Coordination of observations, including securing their continuity (JAXA, Norway,
CSIRO-Australia, CEOS?)
d. Coordination of the production of reference datasets (FAO, GTOS, JRC)
e. Demonstration or pilot initiatives to show capabilities (Australia, Norway, FAO, ESA,
Brazil, Niger)
f. Improvement of access to observations, datasets, tools and expertise and associated
Capacity Building activities. (Australia, Norway, Rep. of Korea, FAO .)
Yoshiki Yamagata [email protected]
Hozuma Sekine : [email protected]
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Rubber plantation at Chachengsao(RFC)
Hill evergreen forests at Kog-Ma (KMW)
Dry evergreen forests at Sakaerat (SKR)
Mixed deciduous forests at Mae Klong (MKL)
Teak plantation at Mae Moh (MMP)
observation sites(ThaiFlux network)
Registered
ThaiFlux
Dr. Kasemsap
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Rubber plantation at Chachengsao(RFC)
Hill evergreen forests at Kog-Ma (KMW)
Dry evergreen forests at Sakaerat (SKR)
Rice (rain-fed)at Sukothai
Teak plantation at Mae Moh (MMP)
Casava Plantationat Nakorn Ratchasima
Dry dipterocarp forest(2008)
Sugarcane plantation at Bureerum (2007)
Observation sites (ThaiFlux network)
Mixed deciduous forests at Mae Klong (MKL)
Land use monitoringat Tak
Dr. Kasemsap
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Background The Sakaerat Environmental Research Station (SERS) was established by the Thai government on
September 19, 1967.(!.". 2510; #$%&'()*+
,-./01 ,23%4.5).
It was administered by the Thailand Institute of Scientific and
Technological Research as a facility for ecological and
environmental research
UNESCO Biosphere Reserve Thailand Long-term Ecological Research
Sakaerat TowerNakhonratchsima, Thailand14°29’N,101°55’E, 535 m aslMixed seasonal evergreen foresta 47 m tower
in
Dr. Kasemsap
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Dr. Kasemsap
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Rubber Flux at Chachoengsao (RFC)Position
Latitude: 13º 39' 56" N
Longitude : 101º 26' 29" E
Elevation 69 m
Slope Negligeable
Terrain Type Flat
Area 6 ha plot in a 200 ha plantation
Climate Tropical monsoon climate
Mean annual air
temperature28.0degC
Mean annual
precipitation1276mm
Vegetation Type Mono-specific rubber tree (Hevea brasiliensis) plantation
Dominant Species
(Overstory)Hevea brasiliensis
Dominant Species
(Understory)Scarce shrubs and remains of previous intercrop (rattan, bamboo...)
Canopy height 20 m
Age 13 years old
LAI 3.2
Soil typeSandy-clay-loam (Kabin Buri series) characterized by a compact lateritic layer with ferralitic
concretions at ca 1 m deepDr. Kasemsap
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OCEAN AND CLIMATE RELATED PROGRAMS TO GLOBAL WARMING IN INDONESIA
Fadli Syamsudin Agency for the Assessment and Application of Technology (BPPT)
Workshop on Monsoon Asia Tropical Forest Dynamics and Sustainability , Thailand 8-11 January, 2009
• Technological roadmap on global warming• Research facilities• Ongoing programs • HARIMAU• Concluding remarks
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BPPT TECHNOLOGY ROADMAP ON GLOBAL WARMING
•Weather, Flooding, and Dryness Prediction Models•Research Vehicle for Atmospheric Aerosol
Tech
nolo
gy C
onte
nt
2007 2008 2009 2010 - 2014
•Flooding Prediction Model
•Weather, Flooding, and Dryness Prediction Models
•Weather, Flooding, and Dryness Prediction Models
CH4 Monitoring &
Capture in Landfill
Atmospheric aerosol
deposition
Air Pollution
Monitoring by
FTIR
Study of emision &
desposition of aerosol
CO2 reduction by
air-sea interaction
CO2 reduction by
phytoplankton
Global warming induced Sea level rise
CO2 Budget
Fadli Syamsudin
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4. Development and Application of Remote Sensing Model for Seaweed Distribution Mapping and Measurement of
Harvesting Potential in Indonesia
Activities (2008-2009)
$ Seaweed mapping using high resolution images of Formosat-2
$ Algorithm development using hyperspectral satellite and in situ
$ measurements for Sargassum sp. identification
$ Seasonal distribution mapping for Sargassum sp.
$ Estimation on harvesting potency of Sargassum sp.
$ Satellite validation using in situ method
BPPT in cooperation with BRKP
Fadli Syamsudin
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]-#6T(T&`(=%#-.
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Thank you