22nd apan meeting in singapore national university of singapore, july 17-21, 2006 operational...
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22nd APAN Meeting in SingaporeNational University of Singapore, July 17-21, 2006
Operational Fisheries Application of RS/GIS
in Japan
Sei-Ichi SAITOH*, Hidetada KIYOFUJI*, Daichi TACHIKAWA**, Mihoko ABE**, Kazuhiko TATEYAMA** and Motoki
HIRAKI*** * Hokkaido University ** FUJITSU Hokkaido Systems Limited *** GIS Hokkaido Limited
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Contents
• Background• Objectives
•ubiquitous Information System• Overview of Information Transfer• Hierarchical Product Structure• WebGIS and Onboard GIS• Concluding Remarks
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Sea Ranching
Stock Release
Aquaculture
logistics
ウニ
特売
Retail
Fisheries as Social Systems
Fishing
Consumer
Fish Market
RS/GIS
Sustainability
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Fisheries-GIS
InteractionAtmosphere and
Ocean Rapid Temporal ChangeHorizontal ChangeVertical Change
Sporadic dataObserved by vessels
Cloud area on satellite image
BiologyFood chain
Complicated Scale/ Plankton,Fish, Fishing ground, Resource.
Plankton
Vertical constructionWater mass distribution
• 4-D (x,y,z,t) Geographical Information System4-D (x,y,z,t) Geographical Information System• Dynamic Information of Oceanic FeaturesDynamic Information of Oceanic Features
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Objectives
• To develop fisheries information system
• To produce high value-added fisheries oceanographic information
• To provide such information in near real time in anytime and at anywhere (Ubiquitous)
For sustainable use and fisheries management……
…..using remote sensing and GIS
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Satellite Receiving ModuleSatellite Receiving ModuleNOAA・ Aqua/Terra
Datebase ModuleOracleOracle
WebGIS
ArcIMSArcIMS
OnboardGIS
GeoBaseGeoBase
Clients
GIS Module
InternetSatelliteCommunication
TeraScanTeraScan
Fisheries Information System
SSTChlSea Ice
Real time andautomatic processing
Analysis Module
• Calculate• Overlay• raster to vectorERDAS/ImagineERDAS/ImagineArcIGISArcIGIS
L&X-band
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Characteristics
• WebGIS(ArcIMS) and Onboard GIS (GEOBASE)• Ubiquitous information system using satellite co
mmunication (WIDE-STAR and SUPERBIRD)• High value-added fisheries oceanographic informati
on (Hierarchical Structure)• Near real time with automatic data processing (ERD
AS/Imagine and ArcGIS) and data base management system (ORACLE)
For sustainable use and fisheries management……
…..using remote sensing and GIS
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MODIS Database Analysis
Communication satellite
GPSDisplayOverlayMeasure
Internet
WIDE-STAR(64Kbps)SUPERBIRD(6Mbps)J-SAT(3Mbps)
Overview of Information Transfer
WebGIS(Land)
Onboard GIS(Offshore)
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Satellite Communication
• SUPERBIRD-D 110 E Coverage
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Target Species
• Japanese common Squid (Todarodes pacificus)
• Pacific Saury (Cololabis saira)
• Albacore (Thunnus alalunga)
• Skipjack (Katsuwonus Pelamis)
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October 13, 1998
Squid
Pacific saury
Fishing fleets detected by OLS/DMSP
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Distribution and Migration
Okhotsk SeaBering Sea
Northwestern Pacific
SkipjackSquid
sauryAlbacore
Sea of Japan
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Service Regions
Squid
saury
Albacore
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Level 1 Product Processing
Level 2 Product Combination
Level 3 Product Integration
Level 4 Product Potential Fishing Ground
Hierarchical Structure
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Brief descriptions of each product level
Product level and Product description1 Raster-image data from the Terascan system2 Single-image processing such as SST gradient or
contour line3 Integration of Level 1 and Level 2 products4 Estimated potential fishing ground5 Predicted one- or two-days-forward fishing ground
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Shatsky Rise
Kuroshio Kuroshio Extension
Oyashio Subarctic Front
Subtropical Front
Japan
Emperor Seamount Chain
(www.ncfisheries.net/fishes/)
Albacore tuna (Thunnus alalunga)
Questions of interest:Why albacore – abundantWhat oceanographic factors – habitatHow to determine – proxy indicators
How to make potential fishing ground
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NASA,RSSand AVISO
JAFICDATA BASE
Fisheries Satellite RS
Probability of environmental map
Potential albacorehabitat
Monthly 1998-2003
T/P-ERS MergedSSHA
T/P-ERS MergedSSHA
SeaWiFS SSC
SeaWiFS SSC
TRMM/TMI-AVHRRSST
TRMM/TMI-AVHRRSST
Classifiedfishing data
Simple predictionhabitat
Oceanic features:eddies,fronts
High catch data
Statistical modelfor prediction CPUE
ArcGIS
EnhancementVisualization
ExaminationVisualization
Spatial analyst
Geostatisticalanalyst
GAM-GLM
How to make potential fishing ground
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Method 1 : Simple prediction map
SSHA
Chl-a
SST
Output map
High catch range(mean ± one SD)
19.5 ± 1.52 °C
0.3 ± 0.11 mg m-3
13.5 ± 19.16 cm
CombineInput map
ArcGIS: Spatial analyst
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Method 2 : Environmental probability map
SSHA
Chl-a
SST
Fishing effort CPUE
Prob. Each interval
Prob. Each interval
+
+
+
Average
Output map
1.Fishing efforts : indices of fish availability (Andrade & Garcia, 1999)2.CPUEs: indices of fish abundance (Bertrand et al., 2002)
Input map
ArcGIS: Spatial analyst
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Method 3 : Statistical model for prediction
SSHA
Chl-a
SST
Satellite data Catch data
GAM
Piecewise GLM
Stepwise GLM-Residual deviance-AIC -F-statistic
Significant equation
Output map
Input map
ArcGIS: Geostatistical analyst
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Space Fish LLP (Limited Liability Partnership)
SpaceFishSpaceFish LLP was estabulished on June 20, 2006
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TOREDAS: start to fish
TraceableOperationalResourcesEnvironmentDataAcquisitionSystem
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MODIS Database Analysis
Communication satellite
GPSDisplayOverlayMeasure
Internet
WIDE-STAR(64Kbps)SUPERBIRD(6Mbps)J-SAT(3Mbps)
Overview of Information Transfer
WebTOREDAS(Land)
Onboard TOREDAS (Offshore)
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Web TOREDAS
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Onboard TOREDAS
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MODIS Database Analysis
Communication satellite
GPSDisplayOverlayMeasure
Internet
WIDE-STAR(64Kbps)SUPERBIRD(6Mbps)J-SAT(3Mbps)
Overview of Information Transfer
WebTOREDAS(Land)
Onboard TOREDAS (Offshore)
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Antenna for Satellite Communication
-Diameter:60cm-Ku band
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Receiver
Notebook PC
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Sahara
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Panasonic - Tough Book
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Panasonic - Tough Book
-Hard Duty-Touch Panel-Protect water
For Fishermen
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A: clear, B: distance measurements, C: trip history, D: search the nearest predicted fishingground, E: change menu.
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A: clearB: distance measurementsC: trip historyD: search the nearest predicted fishing groundE: change menu.
A B C D E
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Web TOREDAS
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Operational Fisheries Oceanography
Research and Development
Operational Fisheries Oceanography-Measurements:Measurements: systematic, long-term, routine
-Interpretation of data:Interpretation of data: fast(near real-time)-Dissemination of results:Dissemination of results: rapid, e.g. internet
USERSGovernments, Regulatory Authorities,
Commercial Enterprises, Research Institutes
-Raw data-Statistics-etc
-Models-Technology(Observing/sampling)
-Funding-Data-Application
-Products
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Concluding Remarks
• Support ubiquitous RS(MODIS)/GIS assisted fisheries operation
• Contribute to save energy and fuel for optimum fishing activities
• Improve understanding fishing ground formation and fish migration
• Promote to develop “Operational” Fisheries Oceanography
For sustainable use and fisheries management……
This project is supported by Ministry of Economy, Trade and Industry (METI)
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Database
MODISSatellite
Fishing fleet
Future
TOREDAS never sleep 24 hours/365 days
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Future System•VMS (Vessel Management
System) : Operation Management and Resource Management
•Safety Operation: Weather and Wave Information
•Economic Usage: Fish Market Information
•Traceable: Food safety
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