1 GIS in Marine and Coastal Environments I-IV AAG Centennial Meeting, Philadelphia March 17, 2004

2 A New Object-Oriented Data Model for Oceans, Coasts, Seas, and Lakes AAG Centennial Meeting, Philadelphia March 17, 2004 dusk.geo.orst.edu/djl/arcgis Dawn Wright, Oregon State University Pat Halpin, Duke University Michael Blongewicz, DHI Joe Breman and Steve Grisé, ESRI

3 ArcGIS “Custom” Data Models Basemap Administrative Boundaries Utilities Parcels Transportation Imagery etc... Conservation/Biodiv Hydro Groundwater Hydro Forestry Geology Petroleum Marine IHO-S57 Atmospheric etc...

4 Image courtesy of PISCO, OrSt Marine Data Collection

5 Figure courtesy of Anne Lucas, U. of Bergen, Norway

6 A Georelational to a Geodatabase Model coverage and shapefile data structures –homogenous collections of points, lines, and polygons with generic, 1- and 2-dimensional "behavior" can’t distinguish behaviors –Point for a marker buoy, same as point for OBS “smart features” in a geodatabase – lighthouse must be on land, marine mammal siting must be in ocean

7 basic template for implementing GIS projects –input, formatting, geoprocessing, creating maps, performing analyses basic framework for writing program code and maintaining applications –development of tools for the community promote networking and data sharing through established standards Purpose of Marine Data Model

8 Design Strategy “Generic” Marine Data Model User Group Data Model User Group Data Model User Group Data Model Project Data Model Project Data Model Project Data Model Inheritance

9 Steps in Data Modeling (1) Model the user's view of data –what are the basic features needed to solve the problem? (2) Select the geographic representation –points, lines, areas, rasters, TINs Bathymetry Sidescan sonar/Backscatter Shoreline Marine boundaries (e.g., MPAs) Geophysical time series Sub-bottom profiling Magnetics Gravity Seismics Sediment transport etc.... Marine mammal movement Atmospheric influences Sea state Wave activity Sea surface temperature Salinity Sensor calibration data Current meters Density etc.... Image by Joe Breman, ESRI

10 Users’s View of Data Steve Grisé, ESRI

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12 Steps in Data Modeling (cont.) (3) Define objects and relationships –draw a UML diagram (4) Match to geodatabase elements –specify relationships, “behaviors” (5) Organize geodatabase structure

13 MeasuredData InstantaneousPoint (ex: CTD) Measurement X Y TimeStamp MeasuringDevice MeasuredType Z InstantaneousPoints Measurement Michael Blongewicz

14 Image courtesy of the Neptune Project, University of Washington Center for Environmental Visualization

15 Measurement TimeDurationPoint (ex: moored ADCP) X Y Z TimeDurationPoints TimeSeriesTurnTable TSType TimeSeries3TimeSeries2TimeSeries1 Michael Blongewicz

16 TimeSeries3TimeSeries2 TimeSeriesPoints (ex: ADCP in series) X Y Z TimeSeriesPoints TSType TimeSeries1 TimeSeriesTurnTable Michael Blongewicz

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18 Implications (1) Inputting & Formatting Data Provides common data structures Allows control of required data fields from collection through analysis phases

19 Implications (2) Geoprocessing & Analysis Allows explicit spatial & temporal relationships to be used in geoprocessing and analysis

Build Better Models / Analysis Geographic Space Data Space Geographic Space Sample Data Model Habitat Redefine Model GIS Applications Statistical Applications 1. Sampling 2. Statistical methods 3. GIS models 4. Model validation

21 Implications (3) Data Sharing Within / Between Projects Internet Map Services (Geography Network, NSDI, OBIS…) Internet Map Services: data conflation tools DODSWMS Z39.50 FGDC Tools/Protocols: Data Type: vector datametadatamapraster data XML Distributed Generic Information Retrieval Distributed Oceanographic Data System Web Mapping Services

22 Project is Ongoing Case studies, tool development –Interested participants via web site ~275 people, 31 countries Refine UML - abstract and feature classes, descriptions, rules/behaviors 2004 ESRI UC sessions –2005 ESRI Press book Agency “buy-in” Publicizing and publishing Tie-in w/ other model efforts

23 More information dusk.geo.orst.edu/djl/arcgis inc. downloads, join MDM listserv Next talk and… Thursday, 10 a.m., Alyssa Aaby, Salon D