Th Ft f GIS dS ti l The Future of GIS andSpatial Analyses in Fisheries: Analyses in Fisheries: Challenges and Opportunities Willi L Fi h William L. Fisher U S Geological Survey Oklahoma Coop Fish and Wildlife Research Unit Oklahoma State University
Th F t f GIS d S ti lThe Future of GIS and Spatial Analyses in Fisheries:Analyses in Fisheries:
Challenges and Opportunities
Willi L Fi hWilliam L. Fisher
U S Geological SurveyOklahoma Coop Fish and Wildlife Research Unit
Oklahoma State University
Presentation OutlinePresentation Outline
k d• Background– History– Evolution
• Review: applications, challenges, opportunitiesReview: applications, challenges, opportunities– Marine ecosystemsInland freshwater ecosystems– Inland freshwater ecosystems
– Aquaculture
F• Future– Challenges and opportunities
Background of GIS/SABackground of GIS/SA
Old World MapOld World Map
Future PerspectiveFuture Perspective
• The future is only a projection, missing many details. – Joseph J. Dewey
Model of Fisheries GIS/SAORGANISMS
/
Maps of pspecies
distributions
Overlay Overlay
GIS/SA
Maps of habitat
Maps of fishing
Overlay
/
conditionsg
effort
HABITATS PEOPLEFisher (2004)
History of GIS/SAy /
1st international1960s – Birth of GIS1970s – Computer mapping 1 international
fisheries GIS/SA symposium
1970s Computer mapping1980s – Spatial database management1990s – Map analysis and modeling2000s Multimedia mapping
1st fisheries
symposium2000s – Multimedia mappingBerry (2007) Beyond Mapping III
Canadian GIS
1 fisheries GIS publication
GPSGIS GPS
Landsat Radarsat
1960 19801970 20001990
Landsat Radarsat
1960 19801970 20001990
Fisheries GIS/SA PublicationsFisheries GIS/SA Publications
40
50
ons 300
350
ons
30
40
publ
icat
io
200
250
publ
icat
io
20
mbe
r of p
100
150
mul
ativ
e p
0
10
Num
0
50 Cum
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Meaden (2001) Fisher (2007)Meaden (2001) Fisher (2007)
Evolution of GIS/SAEvolution of GIS/SA
“GIS technology has evolved from a softwareGIS technology has evolved from a software tool used in computer labs to a common language that our global society is using tolanguage that our global society is using to communicate, collaborate, and make better
b l ”decisions about our planet.”
28th ESRI International User Conference
Evolution of GIS/SAEvolution of GIS/SA
Holland (2005) ArcUser
Mega technologiesMega‐technologies
Three most important emerging and evolving fields in the 21st centuryevolving fields in the 21 century
1 Biotechnology1. Biotechnology
2. Nanotechnology
3. Geotechnology
Gewin (2004) Nature
Geotechnology Community EvolutionGeotechnology Community Evolution
(RS, GIS, GPS, WWW)
Berry (2007) Beyond Mapping III
Review of GIS/SAReview of GIS/SA
Future PerspectivesFuture Perspectives
• The future is only a projection, missing many details. – Joseph J. Dewey
• There is (are) no data on the future. – Laurel Cutler
MethodsMethods
R i d GIS/SA bli ti• Reviewed GIS/SA publications– Primary literatureSymposia proceedings– Symposia proceedings
– Organization/agency reports– Industry magazines– Industry magazines
• Queried other GIS/SA keynote speakers– Geoff Meaden– Geoff Meaden– Pepe AguilarManjarrez– Jim KapetskyJim Kapetsky
• Attended recent GIS/SA meeting/symposium– American Fisheries SocietyAmerican Fisheries Society
Spatial Analyses in Fisheries GISSpatial Analyses in Fisheries GIS
Nishida and Booth (2001) Fisher (2007)
StatisticalQUANTITATIVE ANALYSES
Non‐statisticalMultiple Parameter
Single Parameter
QUALITATIVE ANALYSES Multiple
Parameter
Single Parameter
Marine Ecosystems: ApplicationsMarine Ecosystems: Applications
• Mapping
• Site selectionSite selection
• Vessel monitoring
• Distribution and abundance patterns
• Species‐environmental relationshipsSpecies environmental relationships
• Modeling and forecasting catch and harvest
• Manage marine conservation areas
Marine Ecosystems: MappingMarine cosystems: Mapping
• Objective: Assess efficacy Side‐scanj yof sides‐can sonar, image classification & GIS to
Side scan sonar map
map sea floor bottom
• Analysis: UnsupervisedAnalysis: Unsupervised classification 20 spectral classesclasses
• Results: Classified 9bottom habitat typesbottom habitat types, weakly correlated with 2 fish species occurrence
Bottom habitat type
Lathrop et al. (2006) Estuarine, Coastal & Shelf Sci
fish species occurrence map
Marine Ecosystems: Modelingy gAcoustic survey
Trawl• Objective: Estimate Station
jbiomass and distribution of herrings with acoustic gsurveys and trawling
• Analysis: Omni‐
Atlantic thread herring Scaled herring
Analysis: Omnidirectional spherical variograms krigingvariograms, kriging
• Results: Spatial structure of 4 herrings
ScadRound sardinella
structure of 4 herrings related to temperatureupwellingsPáramo and Roa (2003) Fish Res
upwellings
Marine Ecosystems: Web GISMarine Ecosystems: Web GISNational Estuaries Restoration Inventory: web portalNational Estuaries Restoration Inventory: web portal
http://neri.noaa.gov
Marine EcosystemsMarine Ecosystems
• Challenges and Opportunities*– Fishery‐based or area‐based managementy g
– Cooperation or competition among fishery groups
Different boundaries: spatial research– Different boundaries: spatial, research, management, social
f / i l– Loss of GIS/SA specialness
– Lack of awareness of GIS/SA availability, capability and potential for spatially‐based management
*Geoff Meaden
Freshwater Ecosystems: ApplicationsFreshwater Ecosystems: Applications
• Mapping
• Site selectionSite selection
• Distribution and abundance patterns
• Species‐environmental relationships
• Habitat modeling at multiple spatial scalesHabitat modeling at multiple spatial scales
• Catchment conservation and management
Freshwater Ecosystems: ModelingFreshwater Ecosystems: Modeling
(a)(a)Obj ti Id tif ti lSampling unit
2
120 m
(a)
22 22
120 m120 m120 m
(a)
2222
• Objective: Identify spatial patterns of river minnows at two spatial scales 1
3
Rs
Dis4
F
11
333
Rs
Dis4
Rs
Dis44
F
two spatial scales
• Analysis: GLM, CHLOE (moving window analysis)
(b)
Refuge/resting habitat (Rs)Feeding habitat (Fj)
Sampling unit (i)
Spawning habitat
Rs
Fs
(b)
Refuge/resting habitat (Rs)Feeding habitat (Fj)
Sampling unit (i)
Spawning habitat
Refuge/resting habitat (Rs)Feeding habitat (Fj)
Sampling unit (i)
Spawning habitat
Rs
Fs(moving window analysis) ANAQUALAND (hydrographic distance)
Feeding habitat patch
Rs
Djs 7Djs
Rs
Djs 77Djs
(hydrographic distance)
• Results: Supplementation for feeding habitat patches and
50 m
N
5
Fj
Fs
Djs 6
50 m
N
55
Fj
Fs
Djs 66
feeding habitat patches and complementation with spawning habitat patches.
Le Pichon et al. (2006)
spawning habitat patches. Variables used to evaluate the spatial
structure of sampling units at two scales
Freshwater Ecosystems: ModelingFreshwater Ecosystems: Modeling
• Objective: Develop spatial statistical models for stream networks
• Methods: kernel (moving average function), kriging
• Results: Predict at esu s ed c aunsampled locations using stream flow and gstream distance
VerHoef et al. (2006) Environ Ecol Stat Predicted chemical concentrationslg circle = actual, sm circle = predict, shaded = std err
Freshwater Ecosystems: Web GISFreshwater Ecosystems: Web GIS
http://www.niwa.cri.nz/rc/freshwater/fishatlas
Freshwater EcosystemsFreshwater Ecosystems
• Challenges and Opportunities– Sparse data and collectionsp
– Geostatistical and distributional modeling of fishes
Remote sensing and sensor networks– Remote sensing and sensor networks
– Spatially‐explicit fish population modeling
– Global climate change and predicted species distributions
Aquaculture: ApplicationsAquaculture: Applications
• Mapping
• Site suitability and selectionSite suitability and selection
• Inventory and monitoring
• Assess environmental impacts
• Strategic planningStrategic planning
Aquaculture: ModelingAquaculture: Modeling
BackgroundNot suitableMarginally suitable
• Objectives: Assess carp farming potential using
g yModerately suitableVery suitableGIS
• Analysis: Multi Criteria Evaluation with weighted linear combinations
• Results: 58% of the area very and moderately
Suitable sites for carp farm development in Barhatta Upazilla, Bangladesh.
y ysuitable for carp culture
Salam et al. (2004) Aquaculture
Aquaculture: Web GISAquaculture: Web GIS
http://www.fao.org/fishery/gisfish/index.jsp
Aquaculture: Web GISAquaculture: Web GIS
http://pdacrsp.oregonstate.edu/
AquacultureAquaculture
• Challenges and Opportunities*– Involvement of administrators in GIS deploymentp y
– Communication & collaboration among organizations & institutions about GISorganizations & institutions about GIS
– Employing GIS in developing countries
i i– More GIS training
– Limited availability of GIS data
– Socio‐economic GIS studies
– Free and open source GIS/SA softwareFree and open source GIS/SA software*Pepe AguilarManjarrez & Jim Kapetsky
Future of GIS/SAFuture of GIS/SA
New World map
Future PerspectivesFuture Perspectives
• The future is only a projection, missing many details. – Joseph J. Dewey
• There is (are) no data on the future. – Laurel Cutler
• The future is only the past again, entered through another gate. – Arthur Wing Pinero
Cycles of GIS/SACycles of GIS/SA
Berry (2007) Beyond Mapping III
Challenges and OpportunitiesChallenges and Opportunities
• Multidimensional GIS
• Sensors and networks• Sensors and networks
• GeoWeb
Multidimensional GISMultidimensional GIS
Dimensions
• 2D: x (easting), y (northing)2D: x (easting), y (northing)
• 3D: x, y, z (altitude)
• 4D: x, y, z, t (time) ~ animation
Multidimensional GISMultidimensional GIS
S i i id d li• Static coincidence modeling– Cartesian system
– 2D square grid
– 3D cube– 3D cube
• Dynamic flows modeling – Hexagonal systemg y
– 2D hexagon grid
3D polyhedron– 3D polyhedron Berry (2007) GeoWorld
Multidimensional GISMultidimensional GIS
• Dynamic flows modeling– Track movements over space and time in 3D pgeographic space
– Current 2D applicationsCurrent 2D applications• Transportation patterns and traffic simulation
• Hazard evacuation planning• Hazard evacuation planning
– Potential 3D applicationsRi fl d i l i• River flood simulation
• Fish movements
Sensors and NetworksSensors and Networks
• Types– Wireless sensor networks
– Global sensors
GPS enabled mobile devices– GPS‐enabled mobile devices
• Provide– Real‐time, wireless geospatial data
– Location‐based contentLocation based content
Wireless Sensor NetworksWireless Sensor Networks
3D underwater acoustic sensor networkhttp://www.ece.gatech.edu/research/labs/bwn/UWASN/index.html
Global Sensor NetworksGlobal Sensor Networks
http://nosa.noaa.gov
Global Sensor NetworksGlobal Sensor NetworksOceanic and Atmospheric Research network
http://nosa.noaa.gov
GPS enabled Mobile DevicesGPS‐enabled Mobile Devices
• Cell phones with GPS & camera
Photo tag of fly fisherman in Ithaca, NY
GeoWebGeoWeb
• “GeoWeb” or Geospatial Web – ability to locally/globally integrate and share geospatial y g y g g pinformation via the Internet.
• “Neogeography” – use of geographical techniques and tools for personal and community activities or for utilization by acommunity activities or for utilization by a non‐expert group of users.
Wikipedia (2008)
GeoWebGeoWeb
Use
Serve
AuthorAuthor
ContentMaps, Data, Models
Dangermond (2007) ArcNews
GeoWeb: PortalsGeoWeb: Portals
http://www.fao.org/fishery/gisfish/index.jsp
GeoWeb: Google OceanGeoWeb: Google OceanSea Surface Temperature ‐ 24 Aug 08p g
GeoWeb: Google EarthGeoWeb: Google EarthUser‐created content: photo of cast netting, Rio de Janeiro, Brazil
GeoWebGeoWeb
Is resulting in…• Democratization of GIS• Democratization of GIS
• Geospatial citizen science
• Ubiquitous, real‐time, accurate geospatial informationinformation
• Geospatially‐enabled social networking
• Caution: issues of privacy, confidentiality, propriety, integrityp p y, g y
Future PerspectiveFuture Perspective
• The future is only a projection, missing many details. – Joseph J. Dewey
• There is (are) no data on the future. – Laurel Cutler
• The future is only the past again, entered through another gate. – Arthur Wing Pinero
• The most profound revolutionary technologies are those that disappear –Mark Weiserare those that disappear Mark Weiser
Fisheries GIS/SA Community EvolutionFisheries GIS/SA Community Evolution
(RS, GIS, GPS, WWW)
Berry (2007) Beyond Mapping III
Evolution of Fisheries GIS/SAEvolution of Fisheries GIS/SA
Fisheries GIS/SA
Holland (2005) ArcUser
/
Thank youThank you