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

Contents

• Background• Objectives

•ubiquitous Information System• Overview of Information Transfer• Hierarchical Product Structure• WebGIS and Onboard GIS• Concluding Remarks

Sea Ranching

Stock Release

Aquaculture

logistics

ウニ

特売

Retail

Fisheries as Social Systems

Fishing

Consumer

Fish Market

RS/GIS

Sustainability

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

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

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

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

MODIS Database Analysis

Communication satellite

GPSDisplayOverlayMeasure

Internet

WIDE-STAR(64Kbps)SUPERBIRD(6Mbps)J-SAT(3Mbps)

Overview of Information Transfer

WebGIS(Land)

Onboard GIS(Offshore)

Satellite Communication

• SUPERBIRD-D 110 E Coverage

Target Species

• Japanese common Squid (Todarodes pacificus)

• Pacific Saury (Cololabis saira)

• Albacore (Thunnus alalunga)

• Skipjack (Katsuwonus Pelamis)

October 13, 1998

Squid

Pacific saury

Fishing fleets detected by OLS/DMSP

Distribution and Migration

Okhotsk SeaBering Sea

Northwestern Pacific

SkipjackSquid

sauryAlbacore

Sea of Japan

Service Regions

Squid

saury

Albacore

Level 1 Product　　　 Processing

Level 2 Product Combination

Level 3 Product Integration

Level 4 Product Potential Fishing Ground

Hierarchical Structure

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

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

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

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

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

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

Space Fish LLP (Limited Liability Partnership)

SpaceFishSpaceFish LLP was estabulished on June 20, 2006

TOREDAS: start to fish

TraceableOperationalResourcesEnvironmentDataAcquisitionSystem

MODIS Database Analysis

Communication satellite

GPSDisplayOverlayMeasure

Internet

WIDE-STAR(64Kbps)SUPERBIRD(6Mbps)J-SAT(3Mbps)

Overview of Information Transfer

WebTOREDAS(Land)

Onboard TOREDAS (Offshore)

Web TOREDAS

Onboard TOREDAS

MODIS Database Analysis

Communication satellite

GPSDisplayOverlayMeasure

Internet

WIDE-STAR(64Kbps)SUPERBIRD(6Mbps)J-SAT(3Mbps)

Overview of Information Transfer

WebTOREDAS(Land)

Onboard TOREDAS (Offshore)

Antenna for Satellite Communication

-Diameter:60cm-Ku band

Receiver

Notebook PC

Sahara

Panasonic - Tough Book

Panasonic - Tough Book

-Hard Duty-Touch Panel-Protect water

For Fishermen

A: clear, B: distance measurements, C: trip history, D: search the nearest predicted fishingground, E: change menu.

A: clearB: distance measurementsC: trip historyD: search the nearest predicted fishing groundE: change menu.

A B C D E

Web TOREDAS

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

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)

Database

MODISSatellite

Fishing fleet

Future

TOREDAS never sleep 24 hours/365 days

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