Eco System Research:Assessment Research based on Remote Sensing Data
Makoto Ooba*National Institute for Environmental Studies
*Corresponding Author: [email protected]
LoCARNet 3rd Annual Meeting, Research Session for Remote Sensing and Sustainable Forestry Management. Nov. 26th, 2014 (Bogor)
Recent situation of renewable energy and woody biomass in Japan
Ecological and economical modeling of wood biomass production in a small region in central Japan
Integrate impact assessment by an ecological-footprint-like index (the occupancy time rate index, ORT)
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
Biomass usage in JapanTotal energy consumption in Japan
Source: Japan Center for Climate Change Actions
Source: Mizuho Research Institute
1950 2000
2002
600
(Unit, 1013 kcal)
Coal
Oil
LNGHydro power
Nuclear power Renewable energyincluding solar, wind, and geothermal, and various biomass energy
2012
2010 2012(Unit, 104 kL eq.)
Biomass use in JapanNot increase, innovatively, despite of intensive research and development by both governmental and private sectors
400
Biomass
Plastic Waste
Ecosystem Services from Forest
Unmanaged forest(No understory vegetation)
Troubles with wildlife
http://www.komeri-npo.org/record/downpour/gihu/h12/14/index.html
Disaster by driftwoodsfrom unmanaged forests
0
10
20
30
1960 1970 1980 1990 2000 2005
Needle-leafBroad-leafArea
Increase of timber volume accumulation and forest area in Japan
Year
Water resource
Conservation of biodiversity
Biomass production
Nutrient & sediment flowWater purification
Carbon sequestration
Land conservation
Control of flood
Recreation
Abundant Wood Biomass in Japan Forest ecosystems also provide
the ecosystem services to human society
Google EarthVo
lum
e (1
08m
3 ), A
rea
(104
km2 )
Difficulties: Sustainable biomass use Energy & heat from biomass is renewable and carbon
neutral Sustainable usage of domestic wood biomass will conduct
promoting domestic forestry and enhancing conservation of forest ecosystems in Japan
Wood biomass can be supplied continuously from the forests without serious disturbance on ecosystems ?
Relatively high costs for forest managements and biomass productions in Japan.
Integrated assessments are needed for production & usage of domestic wood biomass.
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
Objectives
Biomass production and related environmental effects are simulated for a long-term (-2200) by ecological and cost calculation models in a selected small area
Form the simulation results, impacts under various scenarios of forest management are assessed by a ecological-footprint-like index (the occupancy time rate index)
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
Scenarios:Managed area, Rotation length, Tinning schedule (timing, strength, usage rate)
Forest ecosystem model
BGC-ES(Ooba et al., 2010)
Forest map/statistical data
Cost calculation model(Kinoshita et al., 2010)
Study Framework
Forestry economic model
Forest GIS
Calculation of ORT(Occupancy Rate Time)
For an object,
ORT = A P / C,
A: Amount of the object P: Occupation periodC: The capacity of the
object, i.e., the potential amount, total area, purification ability, and available labor.
Environmental Assessment
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
Development of GIS database
GIS Database
Forest Database
InventoryDatabase
Forest Maps
InventoryData Sets
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
Ooba et al. (2010) Ecological Modelling 221: 1979-1994.
Carbon sequestration
Water runoff
Nitrogen leaching
Timber volume
Erosion preventionQuantitativeEvaluationFrom the past to futures under various scenarios
Caron emission, climate regulation
Water resource
Woody biomass
Water quality
Disaster control, water quality
Forest biogeochemical model: BGC-ES
Output:Ecosystem services
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
0
1000
2000
3000
4000
5000
6000
Machine CostCm
Labor CostCl
Cost calculation model
FellingChainsaw
BurkingChainsaw
LoggingSwing yarder
Chipper
TransportTrack
Forwarding: Grapple loader
JPY
m-3
C = (1+)(Cm+Cl)+Cst+Croad
Kinoshita et al. (2010)
Cm i cost of forestry machines Cl i cost of labor
Croad access-road clearing cost
Cst fixed cost rate for overhead cost
Machinery CostCm
Labor CostCl
Logging distance 250 mTransport distance 5 km
8,590 JPY m-3(66 EUR m-3)
Example:
The model was parameterized according to their comprehensive research and data about costs and usage of various forestry machineries in Japan Harvester
Arbro400Shttp://www.forest-machine.jp/catalog/hervester_afm_arbro400.html
Swing Yarder
http://www.iwafuji.co.jp/lineup/forest/sw.htm
Chipper
FPC1700http://www.furukawarockdrill.co.jp/products/chipper/spec/FPC1700.htmOoba (NIES): Ecosystem Assesments based on Remote Sensing
Study area
40N
30N
Asahi and Inabu regions in Aichi prefecture, Japan
Ooba et al., (2013) SDEWES conference, Dubrovnik, Croatia, Ooba et al., (2014) J. Cleaner Production. (Submitting)
Ooba (NIES): Ecosystem Assesments based on Remote Sensing Ooba (NIES): Ecosystem Assesments based on Remote Sensing
Forest conditions in the study areaTree type
Area (ha)Plantation Other forest
Cedar 5,789 Cypress 5,376
Pine 75 239 Needle leaf 82 3 Broad leaf 3,353
total 11,322 3,595
Distribution
Forest type
Legend
Cedar
Cypress
Pine
Broad leaf
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
Simulated forest scenarios
Management Type*
Forestry Activity
Conversion to Secondary
Forest
BAU Business as usual Standard Low No
FM1 Intensive management Modified Low No
FM2Intensive &
extended management
Modified 2 times higher No
CNV Forest conversion Modified 2 times higherYes
(30%)
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
Convert to secondary forests (30%).
CNV scenarioCurrentDistribution
Economically poor productivity plantations(Steep slope, far from roads, bad soil condition, etc)
Secondary and natural forest provide relatively high quality habitat and biodiversity
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
Simulation results
0
100
200
300
400
0
100
200
300
0
200
400
600
800
0
500
1000
1500
2000
0
500
1000
0
1
2
3
2000 2100 2200year
Accumulated volume(m3 ha-1)
Averaged forest age(year)
Harvested timber(kgC ha-1 y-1)
2000 2100 2200year
2000 2100 2200year
Water runoff(mm y-1)
Carbon sequestration(kgC ha-1 y-1)
Nitrogen leaching(kgN ha-1 y-1)
Legend BAU FM1 FM2 CNV
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
FM1Cost calculation
0
10000
20000
30000
40000
0
0.5
1
1.5
Prod
uctio
n C
ost
(JPY
ha-
1y-
1 )La
bor w
ork
(per
son-
day
ha-1
y-1 )
2000 2100 2200year
2000 2100 2200year Chubu Forest Management, Co. Ltd.
BAU
FM2 CNV
Material [kg]Landuse [km2]Labor [person]
Span [year]Stock [kg]
Total land [km2]Population [person]
Pollution [kg]Water use [m3]
Absorb capacity [kg/year]Annual precipitation [m3/year]
ORT
OccupancyRate Time [year]
OA TM TA
CA TSEach value of ORT for any object has the temporal dimension, and it can be compared to others. Sum of ORT provides an index for the all impacts
Fijii et al. (2010, 2013)
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
ORT Calculation in this studyLanduse Carbon balance
(1) Absorb (2) EmissionLabor
Artificial (plantation)forest
Study area
18,000(ha)
Potential carbon absorb rate in the area
* Maximum absorb rate 5.0 Mg-C y-1 ha-1
90 Gg-C y-1
(3) Offset
Potential workloadin the area45,000 person-days
Denominator(Constant)
Numerator(Simulated)
Estimated workload
*Estimated from number of forestry worker
Ooba (NIES): Ecosystem Assesments based on Remote Sensing
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
2000 2100 2200
Carbon balance between absorptions and practices
20
Occ
upan
cy ti
me
rate
(O
RT)
(y)
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
year2000 2100 2200
Occ
upan
cy ti
me
rate
(O
RT)
(y)
Combustion Offset
year
Integrating ORTs
0
0.5
1
1.5
0
0.5
1
1.5
0
0.5
1
1.5
0
0.5
1
1.5
0
0.5
1
1.5
Landuse (y)
Carbon balance (y)
Labor
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