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22nd APAN Meeting in Singapore National University of Singapore, July 17-21, 2006 Operational Fisheries Application of RS/GIS in Japan Sei-Ichi SAITOH*,

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Presentation on theme: "22nd APAN Meeting in Singapore National University of Singapore, July 17-21, 2006 Operational Fisheries Application of RS/GIS in Japan Sei-Ichi SAITOH*,"— Presentation transcript:

1 22nd APAN Meeting in Singapore National 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

2 Contents Background Objectives ubiquitous Information System Overview of Information Transfer Hierarchical Product Structure WebGIS and Onboard GIS Concluding Remarks

3 Sea Ranching Stock Release Aquaculture logistics Retail Fisheries as Social Systems Fishing Consumer Fish Market RS/GIS Sustainability

4 Fisheries-GIS 4-D (x,y,z,t) Geographical Information System 4-D (x,y,z,t) Geographical Information System Dynamic Information of Oceanic Features Dynamic Information of Oceanic Features

5 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

6 Satellite Receiving Module NOAA Aqua/Terra Datebase ModuleOracle WebGIS ArcIMS OnboardGIS GeoBase Clients GIS Module Internet Satellite Communication TeraScan Fisheries Information System SST Chl Sea Ice Real time and automatic processing Analysis Module Calculate Overlay raster to vectorERDAS/ImagineArcIGIS L&X-band

7 Characteristics WebGIS(ArcIMS) and Onboard GIS (GEOBASE) Ubiquitous information system using satellite communication (WIDE-STAR and SUPERBIRD) High value-added fisheries oceanographic information (Hierarchical Structure) Near real time with automatic data processing (ERDAS/Imagine and ArcGIS) and data base management system (ORACLE) For sustainable use and fisheries management…… …..using remote sensing and GIS

8 MODIS Database Analysis Communication satellite GPS Display Overlay Measure Internet WIDE- STAR(64Kbps) SUPERBIRD(6Mbps) J-SAT(3Mbps) Overview of Information Transfer WebGIS(Land) Onboard GIS (Offshore)

9 Satellite Communication SUPERBIRD-D 110 E Coverage

10 Target Species Japanese common Squid (Todarodes pacificus) Pacific Saury (Cololabis saira) Albacore (Thunnus alalunga) Skipjack (Katsuwonus Pelamis)

11 October 13, 1998 Squid Pacific saury Fishing fleets detected by OLS/DMSP

12 Distribution and Migration Okhotsk Sea Bering Sea Northwestern Pacific Skipjack Squid saury Albacore Sea of Japan

13 Service Regions Squid saury Albacore

14 Level 1 Product Processing Level 2 Product Combination Level 3 Product Integration Level 4 Product Potential Fishing Ground Hierarchical Structure

15 Brief descriptions of each product level Product level and Product description 1 Raster-image data from the Terascan system 2 Single-image processing such as SST gradient or contour line 3 Integration of Level 1 and Level 2 products 4 Estimated potential fishing ground 5 Predicted one- or two-days-forward fishing ground

16 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 – abundant What oceanographic factors – habitat How to determine – proxy indicators How to make potential fishing ground

17 NASA,RSS and AVISO JAFIC DATA BASE Fisheries Satellite RS Probability of environmental map Potential albacore habitat Monthly T/P-ERS Merged SSHA SeaWiFS SSC TRMM/TMI-AVHRR SST Classified fishing data Simple prediction habitat Oceanic features: eddies,fronts High catch data Statistical model for prediction CPUE ArcGIS Enhancement Visualization Examination Visualization Spatial analyst Geostatistical analyst GAM-GLM How to make potential fishing ground

18 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 ± cm CombineInput map ArcGIS: Spatial analyst

19 Method 2 : Environmental probability map SSHA Chl-a SST Fishing effortCPUE 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

20 Method 3 : Statistical model for prediction SSHA Chl-a SST Satellite dataCatch data GAM Piecewise GLM Stepwise GLM -Residual deviance -AIC -F-statistic Significant equation Output map Input map ArcGIS: Geostatistical analyst

21 Space Fish LLP (Limited Liability Partnership) SpaceFish SpaceFish LLP was estabulished on June 20, 2006

22 TOREDAS: start to fish Traceable Operational Resources Environment Data Acquisition System

23 MODIS Database Analysis Communication satellite GPS Display Overlay Measure Internet WIDE- STAR(64Kbps) SUPERBIRD(6Mbps) J-SAT(3Mbps) Overview of Information Transfer WebTOREDAS(Land) Onboard TOREDAS (Offshore)

24 Web TOREDAS

25 Onboard TOREDAS

26 MODIS Database Analysis Communication satellite GPS Display Overlay Measure Internet WIDE- STAR(64Kbps) SUPERBIRD(6Mbps) J-SAT(3Mbps) Overview of Information Transfer WebTOREDAS(Land) Onboard TOREDAS (Offshore)

27 Antenna for Satellite Communication -Diameter:60cm -Ku band

28 Receiver Notebook PC

29 Sahara

30 Panasonic - Tough Book

31 -Hard Duty -Touch Panel -Protect water For Fishermen

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

33 A: clear B: distance measurements C: trip history D: search the nearest predicted fishing ground E: change menu. A B C D E

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38 Web TOREDAS

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46 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 USERS Governments, Regulatory Authorities, Commercial Enterprises, Research Institutes -Raw data -Statistics -etc -Models -Technology (Observing/sampling) -Funding -Data -Application -Products

47 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)

48 Database MODIS Satellite Fishing fleet Future TOREDAS never sleep 24 hours/365 days

49 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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