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BiivedoGreen Network of Excellence-environmental informationSix key research topics in GRENE-ei

rsityemissbonionraCpage1
Overview and project coordination.

page 2
Studies on GHG emissions from biomass burning and rice paddy in East-Asiausing synergy of satellite data and ground based observations.

page 3
Climatic changes and evaluation of their eﬀects on agriculture in Asian monsoon region.

page 4
Building River Basin Resilience by Introducing an Inter-disciplinary Workbench on
Data Integration and Analysis System (DIAS).

page 5GRENE-City: Designing Resilient Cities and National Land.

page 6
Establishment of Research Platform for Developing Models to Predict Future Health Risks Posed byChanges in Climate, Land Use and Population .(Ecohealth)page 7
Environmental Information: Biodiversity and Ecosystem

GREen Network of Excellence -environmental information- (GRENE-ei)
http://grene.jp/english/
Coordinated by: Earth Observation Data Integration and Fusion Research Initiative (EDITORIA), the University of Tokyo

Abstract

The aim of GRENE-ei is to enhance green innovation and networking in the fields of earth environmental science andinformation engineering. This project has six research topics and each topic is on a different research field. The fields are
Carbon emission, Agriculture, Water, City, Health and Biodiversity. EDITORIA as a coordinator promotes interdisciplinary
researches based on Data Integration and Analysis System(DIAS) which is a centralized system containing big data andapplications in earth science domain. GRENE-ei is funded by the Ministry of Education, Culture, Sports, Science andTechnology(MEXT) in Japan.

Asia
AfricaCommittee
To contribute throughinternational programs

To apply research resultsto other local regions

Discussions andcollaborations

Biodiversity

Carbon emission
Agriculture
Water
To support decision-making
in domestic administration

CityHealthWorkshop and Symposium
To cooperate with Internationalorganizations

FAO,WHO,WMO,… etc.

To create interdisciplinary networking opportunities and research innovations in earth science
To contribute to global issues through international collaborations
To generate valuable societal benefits from research outputs

1Studies on GHG emissions from biomass burning and rice paddy in East-Asiausing synergy of satellite data and ground based observations
Univ. Tokyo, Chiba Univ., Nara woman’s Univ., Nagoya Univ., and RIHN**Research Institute for Humanity and Nature

CO2 sonde【bottom up approach】

MODIS

Vertical profiles【Top down approach】
Columnarconcentration+
Upper atmos.
concentration（Photo：NASA）

Continuous
measurements
Sampling for flux estimation

NDVI→Biomass
Fire info.
Fire radiative
power

GOSAT

CH4 emission fromrice paddy↓

Lower atmos.
concentration

Columnarconcentration

SCIAMACHY

Different
methods

Columnarconcentration+
Upper atmos.
concentration↓Target area : East-Asia (Thai, China, Indonesia)GOSAT

Synergy of various types of satellite data

Ground-based
remote sensing

CO2 and CH4 emissions
from biomass burning

Lower atmos.
concentration 2

Climatic changes and evaluation of their effects on agriculture in Asian monsoon region (CAAM)
Leader: Masaru Mizoguchi (The University of Tokyo)

Aims
1. To improve the reliability of future climate prediction , 2. To develop the information platform
which will be useful to design adaptation and mitigation strategies in agriculture against the predicted climaticchanges in Asian monsoon region

Climate change research

Agricultural effect research

Development of Agro-climatological Data-base in the DevelopingCountries
Digitization of old observational
data recorded in paper format
Agro-meteorological data base
Near real-time meteorological dataacquisition system

Estimation ofthe element ofAgricultural Meteorology

Climatic Changes and Evaluation of Their Effects on
Agriculture Based on a Field Survey
Assessment System Using Meteorological
Data and Crop Models/Evaluation of the impact of climatechange on crop production

heat balance model/Survey of cropping/Comparison of simulation
and real planting/Cultivation based on thesimulation test

Development of Information Platform to Design Adaptationand Mitigation Strategies of Major Crops
against the Predicted Climatic Changes

Impact of Land-Use/Land-Cover (LULC) Changes on the AsianMonsoon Climate - Land-Atmosphere Interaction Study /Use of climate-model output on the DIAS and adetailed land surface data

/Construction of the systemfor crop simulation undervarious conditions

Validation of evaluation
system by field survey

DIAS/Elucidation of the importance of land
surface atmosphere interaction Including theimpact of anthropogenic Asian monsoon region/Collection and maintenance of information
related to land use and land management, soiland Agricultural Meteorology/Collection of basic data on greenhouse gasbalance in agricultural landBenefits

1. Development of basic environmental information and its application to decision-making in the Asian monsoon region
2. Training of young researchers to lead the study of global warming mitigation measures and adaptation research and climate change
3. Construction of information infrastructure for the realization of global warming adaptation and mitigation measures for agricultural sectors

3Building River Basin Resilience by Introducing an Inter-disciplinary Workbenchon Data Integration and Analysis System (DIAS)
Ryosuke Shibasaki, The university of Tokyoin collaboration with Kyoto University• To develop a prototype of inter-disciplinary workbench on the Data Integration andAnalysis System (DIAS) which enables to integrate global Earth observations,predictions, socio-economic data sets and models.
• To develop a supporting system for sound decision making on climate change
adaptation, water resources management, biodiversity conservation, agriculture
management and urban planning.

Inter-disciplinary workbench on DIAS

• Sharing data and information• Exchanging knowledge,
experiences and ideas• Working together

Observation

ModelsSocio-economic
Data Sets

Inter-disciplinary Workbenchon DIAS

Rural River Basins:• Shubuto River, Japan• Sangker River, Cambodia• Nyando River, Kenya

Urbanized River Basins:• Asa River, Japan• Huong River, Vietnam• Citarum River, Indonesia

Constructing knowledge infrastructure, creating scientific knowledge and building
resilience to solve environmental problems and address unanticipated situations. 4

GRENE-City: Designing Resilient Cities and National Land
- A n A p p l i c a t i o n o f E n v i r o n m e n t I n f o r m a t i o n Te c h n o l o g y Nagoya University Yoshitsugu Hayashi, Tsunetoshi Mizoguchi, Yasuhiro Suzuki, Hiroki Tanikawa, Hirokazu Kato, Naoki Shibahara
University of Tokyo Takaaki Kato, Shinji Sato, Ryosuke Shibasaki, Eiji Hato, Yoshiyuki Kawazoe

・Climate Change(Global Warming,Archive

Sea Level Rise, etc.. )・Natural Disaster(Earthquake, Tsunami, etc..)

・Eco-system Deterioration

Powered Nature

Capacity
Building

Vulnerable Society

Re-design for resilient
land and Society効果

AnalysisandDesign

Utilization
andDevelopment

Progressive
Integrated
Database onDIAS
Platform・Aging of Population
・Aging of Infrastructure
・Urban Sprawl
・Motorization- Efficiency ofCompaction- Material
Stock andFlow- Historical
Data ofDisasters

Nature

WellOrganizedLand Use andInfrastructure

HumanActivities

Implementation Plan (Smart Shrink?)

Government

Specialist

CitizenNPO

Community

Company

Extension from Japan to Asia

Users’ Request
5

Establishment of Research Platform for Developing Models to Predict Future Health Risks
Posed by Changes in Climate, Land Use and Population (“Ecohealth”)
Chiho WATNABE （Univ. Tokyo） With： Yamagata Univ., Res Inst Human and Nature

outline This project tries to analyze quantitative relationship between environmental changes including climate change,
environmental pollution or ecosystem degradation and health events by integrating the large-scale environmental informationarchived in DIAS and the local-scale information to suggest the solution and/or mitigation measures for each issue .
While many fields relevant to global-scale issues including climate, ocean, agriculture, ecosystem, and urban are closely associated with the field of health,quantitative analyses between the health area and other areas have not been well explored. Using the wide range of environmental information archived inDIAS, this project tries to explore new aspects of the relationship between health events and environment to provide the directions of mitigation/adaptation for
global-scale issues in the health area, and to demonstrate the usefulness and potential of the integrated database such as DIAS for the health field.

ClimateChangeGlobalwarming

subtheme１： Developing a predictive model regarding health effects ofatmospheric environment integrating human mobility and social change
・endpoints: mortality or respiratory diseases in the urban areas of developing countries.
・ developing models integrating human mobility and social and public health infrastructure.
・ developing methods to link large-scale observation data to local exposure data.

Change in flood, draft,
precipitationsubtheme2： Developing a vector-associated infectious disease trans-mission
model using Health and Demographic Surveillance System （HDSS）

Commuting, air pollution
Heat island

・ endpoints: schistosomiasis and Thai liver fluke in rural areas in developing countries.
・ the effect of climate change as well as social changes on the distribution of vector snails anddistribution of their water habitats will be integrated.
・ exploring the possibility of linking HDSS and DIAS.

Population increase,
Low-income cluster

Social change

subtheme3： Developing a predictive model for water-associated infectious
diseases due to changes in natural and anthropogenic environment
・endpoints: risk of water-associated infectious diseases, especially those associated withurban flood events.
・ developing a model integrating secondary infection and behavioral patterns.

Integration
Applying socialand CC scenario

Exploring
Coupling ofgenerated models

Evaluating theModel output withhealth economics

Indicate the possible solutions for the targeted local issues
Develop predictive models extendable to other localities sharing similar health issues
Demonstrate the usefulness and potential of Data integrated systems to health/medical society

6

GRENE (Green Network of Excellence)

Environmental Information: Biodiversity and Ecosystem

Flux

University of Tokyo, Hokkaido University, Tohoku University, and National Institute for Environmental Studies

Aim of ProjectSpecies

Community Accumulation of biodiversity and ecosystem information
 Providing these data under standard ontologies
 Providing biodiversity and ecosystem data as maps through the use ofother environmental information as backgroundModeling andPrediction of Species
Distribution© K.
Hosokawa© scott.zona onFlickr

Sciadopitys verticillata

Dynamics

Glaucidium palmatum© M. Ito

Pterocarya rhoifolia

Of ca. 5,000 speciesof seed plants
indigenous to Japan, ca.
2,000 species had been
analyzed by Ecological
Niche Modeling (Fig. 1).
The predicteddistribution maps areavailable from theDatabase(http://acacia.c.utokyo.ac.jp/spdist/).

Fig. 1 Examples of predicted natural distribution of Japanese plants using Ecological
Niche Modeling. S. verticillata and G. palmatum are endemic to Japan at genus level.

Community
Compiling Plant
Community
Distribution Map
Evergreen Forest

Swamp Grassland
Fig. 2 Some plant community types in Japan

Deciduous Forest

Alpine Grassland

Based on plantcommunity census
data (more than 10,000 sites areavailable in Japan, an example
on right) and species distribution
maps, we are now compilingplant community distribution
map, complemented bycommunity modeling (Figs. 2and 3).

Acknowledgement. This project is supported by the grant from MEXT, Japan. We thank to data providers including Biodiversity Center ofJapan, MOE, National Museum of Nature and Science, and GBIF-Japan (The Global Biodiversity Information Facility in Japan).

Species Distribution

LayersDefining Layer Structure inBiodiversity and Ecosystem
Information
Flux
Dynamics of ecosystem
Species community
structure
Species distribution

Flux
Observation data＋Complementwith Estimation
Model

Dynamics

Observation data＋Complementwith Estimation
ModelCommunity

Observation data＋
Complement withEstimation Model

Species
Distribution

Fig. 3 Relationships of the four layers.

Dynamics and Flux
JapanFluxJaLTERJaLTERFlux
JaLTER

Seasonal pattern of NEP
JapanFlux

Birch-Oak forest (Takayama)

Modeling andEstimation ofCommunity
Dynamics andFlux
Using plantcommunityinformation, we areplanning to makeprediction modelfor dynamics andflux (Figs. 3 and 4).

Fig. 4 Ecosystem Net Production(ENP) Comparison between JapanFlux
data and JaLTER(Japan Long Term Ecological Research Network) data7

This project has started in FY 2011 and is supported by
the Ministry of Education, Culture, Sports, Science and Technology.
for more information please visit http://grene.jp/english/