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ArcGIS Data Models: Marine Data Model Dawn Wright - Oregon State University Pat Halpin - Duke University Michael Blongewicz - DHI Joe Breman - ESRI.

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Presentation on theme: "ArcGIS Data Models: Marine Data Model Dawn Wright - Oregon State University Pat Halpin - Duke University Michael Blongewicz - DHI Joe Breman - ESRI."— Presentation transcript:

1 ArcGIS Data Models: Marine Data Model Dawn Wright - Oregon State University Pat Halpin - Duke University Michael Blongewicz - DHI Joe Breman - ESRI

2 2 Polling Questions What is your name, organization, and ?What is your name, organization, and ? –(Add yourself to a data models user group list, and you will be sent notifications about webcasts, design studios, etc.) Which of the following ESRI data types do you most commonly use?Which of the following ESRI data types do you most commonly use? –a) Coverage –b) Shapefile –c) Geodatabase feature class Are you interested in seeing a data model webcast, participating in a design studio, and for which data model?Are you interested in seeing a data model webcast, participating in a design studio, and for which data model? Where on the web do you get data?Where on the web do you get data?

3 3 Agenda Marine data model overview and toolsMarine data model overview and tools –The use of schema and templates –Tools designed and tested with marine data model case studies. –Multidimensional modeling. Model elementsModel elements –Feature Datasets –Object classes –Relationships Historical IterationsHistorical Iterations –Subclasses versus Subtypes Current StatusCurrent Status –Ready to be used –Book coming next year Presentation of tools and uses of a Marine GeodatabasePresentation of tools and uses of a Marine Geodatabase

4 4 Thematic Content - layer stack Thematic groupings of marine and oceanographic data sets

5 5 The Data Modeling Cycle Conceptual, logical, and physical models Conceptual Model Sketches, Flow Diagrams, etc. Logical Model Diagram in CASE Tool ArcCatalog Tools Physical Model Database Schema Business Rules Real World Objects and Relationships

6 6 What is a Data Model? A practical working templateA practical working template A starting point for creating a geodatabaseA starting point for creating a geodatabase An aid to simplify the integration of similar datasetsAn aid to simplify the integration of similar datasets A way to facilitate the exchange of dataA way to facilitate the exchange of data A support to existing standardsA support to existing standards Feature ObjectIDGeometry LandObject LandObjectIDTransactionIDSystemStartDateOfficialStartDateOfficialEndDate SurveyPoint SurveyBoundary Point Measurement Computation Coordinate Project Geodatabase * * **

7 7 Whats in a Data Model Template? A pre-designed schema of ObjectsA pre-designed schema of Objects Feature classesFeature classes TablesTables RelationshipsRelationships DomainsDomains SubtypesSubtypes

8 8 Using a Design Template Schema Wizard reads repository or template to create a geodatabase

9 9 ArcGIS Data Models Web site Over 25 industry-specific data modelsOver 25 industry-specific data models Conceptual and logical diagramsConceptual and logical diagrams Case studies, Tips and Tricks documentsCase studies, Tips and Tricks documents

10 10 Path forward for multiD modeling Extend existing functionality to support time and other variables of multidimensional data.Extend existing functionality to support time and other variables of multidimensional data. –Animation manager used to control variables such as time to set the animation sequence. –Improve quality and interaction of charting and include as an animation object. –Added support for the NetCDF data format building on existing layer capabilities. –3D interpolation

11 11 Tools - netCDF at 9.2

12 12 NetCDF in ArcGIS Can be accessed as: RasterRaster FeatureFeature TableTable Direct read and write GIS data to netCDF

13 13 Make netCDF Raster, Feature (point), and table layers

14 14 Using NetCDF as a feature, raster or table in the GIS (network common data format) Behaves the same as any layer or table in:Behaves the same as any layer or table in: –Display Same display tools for raster and feature layers will work on netCDF raster and netCDF feature layers. –Charting Driven by the table just like any other chart. –Animation Multidimensional data can be animated through a variable (e.g. time, pressure, elevation) Multidimensional data can be animated through a variable (e.g. time, pressure, elevation) –Geoprocessing Tool A netCDF raster layer will work just like any other raster layer, same for feature layers and tables.

15 15 Geoprocessing Models Model Builder diagrams for workflow Raster in WGS84 extract_west Shifted_west Output grid name Extract_east Raster in WGS84 Extract by Rectangle (2) Output Extent Output Extent Output Extent Shift Extract by Rectangle (3) Extract by Rectangle Mosaic Output Extent

16 16 3D points displayed in volume space

17 17 3D Interpolation tool Sample resulting from collaboration between data models and ESRI developer Network (EDN) New tools based on data model prototypes and case study testing.

18 18

19 19

20 20

21 21 Demo Marine Data Model 3D interpolation tool

22 22 Marine Data Model Overview -Model elementsOverview -Model elements –Feature Datasets and feature classes –Object classes –Relationships Historical IterationsHistorical Iterations –Subclasses versus Subtypes Current StatusCurrent Status –Ready to be used –Book coming next year Presentation of tools and uses of a Marine GeodatabasePresentation of tools and uses of a Marine Geodatabase

23 23 The Feature data set Stores the spatial reference for all feature classes it contains, including the extents of their m and z values –Feature Classes Marine FeaturesMarine Features –TimeSeries Points –InstantaneousPoints »Instant, Survey, Sounding,LocationSeries –ProfileLine –Shoreline –Track –TimeDurationArea Mesh FeaturesMesh Features –MeshPoints »GridPoint, NodePoint –MeshElements indicates classes covered in detailindicates classes covered in detail Feature Data Sets and Feature Classes

24 24 Object Classes (Tables) –Object Classes SurveyInfo - stores parameters of a surveySurveyInfo - stores parameters of a survey Series - stores the parameters of a series of locationsSeries - stores the parameters of a series of locations MeasuringDevice - stores the parameters of a measuring deviceMeasuringDevice - stores the parameters of a measuring device Vehicle - stores information about the vehicle being usedVehicle - stores information about the vehicle being used Cruise - stores information associated to a cruiseCruise - stores information associated to a cruise Parameter - stores the properties of a given parametersParameter - stores the properties of a given parameters ScalarQuantity - stores magnitude data valuesScalarQuantity - stores magnitude data values VectorQuantity - stores directional data valuesVectorQuantity - stores directional data values Measurement - storing depths related to a specific MeasurementsMeasurement - storing depths related to a specific Measurements MeasuredData - storing data values associated to locationsMeasuredData - storing data values associated to locations indicates classes covered in detailindicates classes covered in detail

25 25 –Relationships One Survey can have many PointsOne Survey can have many Points One ProfileLine can have many SurveysOne ProfileLine can have many Surveys One Cruise can have many TracksOne Cruise can have many Tracks One MeshPoint can have many VectorQuantitiesOne MeshPoint can have many VectorQuantities One MeshPoint can have many ScalarQuantitiesOne MeshPoint can have many ScalarQuantities Many VectorQuantities can have one ParameterMany VectorQuantities can have one Parameter Many ScalarQuantities can have one ParameterMany ScalarQuantities can have one Parameter indicates classes covered in detailindicates classes covered in detail Relationships in the model (You may only need to use one or two of these for your individual project)

26 26 Classification Historical Iterations –Subclasses versus Subtypes

27 27 Presentation of tools and uses of the data model –Varying uses and means of adapting the data model

28 28 –a –a subclass of MeasurementPoint for representing features that are a single observation in time and space – –the X, Y coordinates plus a time-stamp create the unique point feature – –can have multiple Z locations – –an InstantaneousPoint has 4 Subtypes Instant - default valueInstant - default value SoundingSounding SurveySurvey LocationSeriesLocationSeries –Example: Bathymetric Survey, CTD Drops, X Y :00:00 Z Instantaneous Points

29 29 –SurveyID - foreignkey relating to SurveyInfoforeignkey relating to SurveyInfo – –SurveyInfo - stores properties about the survey – –StartDate – –EndDate – –Description – –DeviceID – –TrackID X Y :00:00 Z InstantaneousPoints.Survey

30 30 Demo of the Marine Data Model Survey Point Example

31 31 –a feature class designated for deriving additional along a line. – –Properties HasM and HasZ are set to TRUE – –has a many-to-many relationship with SurveyInfo via SurveyKey –one ProfileLine can be associated to many Surveys –many Survey can be associated to many ProfileLines –Example: Transects, Coastline Evolution ProfileLine

32 32 Inheritance The Design and Intent of ProfileLine

33 33 Demo of Marine Data Model ProfileLine Example

34 34 –a subclass of MeasurementPoint – –fixed in space (X,Y) – –multiple Z Values via Measurement Table – –Example: Moored Buoy, ADCP TimeSeriesPoint

35 35 TimeSeriesPoint with Measurements 1 *

36 36 –includes feature classes: MeshElement (polygon)MeshElement (polygon) MeshPoint (points)MeshPoint (points) – –includes object classes: Mesh - identifies the features making up a Mesh VectorQuantity - vector values for each point for each time step ScalarQuantity - scalar values for each point for each time step Parameter - information about a given parameter – –Example: 2D Model results Design and Intent of Mesh Features

37 37 Relationships

38 38 Demo Marine Data Model MeshPoint Example

39 39 Geodatabase Diagrammer Create graphical representation of geodatabase once complete

40 Framework and Publication of: ArcMarine Marine data model book

41 41 ArcMarine Purpose Your Geodatabase TemplateYour Geodatabase Template –Data collection at sea/shore … to final geoprocessing, analysis Control of required data fields, common data structureControl of required data fields, common data structure –Simplify enterprise GIS project implementation E.g., cruises, MPA networks, habitat mappingE.g., cruises, MPA networks, habitat mapping Program Coding/Application DevelopmentProgram Coding/Application Development –Common/shared tool development –Rapid prototyping –Linkage to processing models Data Sharing/NetworkingData Sharing/Networking Schooling in the GdbSchooling in the Gdb

42 42 ArcMarine Design Strategy Image modified from original by P. Halpin, Duke

43 43 Implementation Process Design Engineering Database Engineering Deployment/Rollout Since Oct 2001: 3 workshops, 3 ESRI UC sessionsSince Oct 2001: 3 workshops, 3 ESRI UC sessions ArcMarine Interest List: over 350 people, 32 countriesArcMarine Interest List: over 350 people, 32 countries Approaching final UML: feature classes, attributes, rules/behaviorsApproaching final UML: feature classes, attributes, rules/behaviors Case studies/tool development in 2005Case studies/tool development in 2005 ESRI Press Book in 2006ESRI Press Book in 2006 More info at dusk.geo.orst.edu/djl/arcgis/about.htmlMore info at dusk.geo.orst.edu/djl/arcgis/about.html

44 44 ArcMarine: A Geospatial Framework for Ocean and Coastal Analysis ESRI Press, 2006ESRI Press, 2006 –By Wright, Blongewicz, Halpin, Breman Full background documentation with ~10 case studiesFull background documentation with ~10 case studies Chapter 1 - Introduction (Why ArcMarine?)Chapter 1 - Introduction (Why ArcMarine?) Chapter 2 - Conceptual Framework and Common Marine Data TypesChapter 2 - Conceptual Framework and Common Marine Data Types

45 45

46 46 ArcMarine Thematic Layers

47 47 ArcMarine Thematic Layers

48 48 Marine ArcMarine … Chapters 3-6

49 49 Ch. 3 - Marine Surveys e.g., Inst. Points, Time Duration Line, Survey & Cruise object tables Louisiana Subsidence Heather Mounts, PhotoScience, FL Essex MG&G Survey Brian Andrews, USGS-Woods Hole, MA

50 50 Source: Sea Turtle Tracks (Caretta caretta) Sea Surface Temperature (WCR) Source: (Read & McClellan2004) OBIS, Pat Halpin et al., Duke U. Ch. 4 - Marine Animal Tracking e.g., Location Series Points, Time Duration Lines and Areas, object tables and rasters

51 51 Ch. 5 - Time Series & Measurements e.g., Time Series Points, Profile Line, Time Series/Meas object tables North Atlantic, Irish Sea Martina Hennesey et al., Marine Institute, Galway, IRELAND Eamonn Doyle, Rob Morrison, ESRI-IRELAND

52 52 Ch. 6 - Nearshore & Coastal Analysis e.g., Shorelines, ProfileLines, Marine Areas, object tables Martin County, FL Artificial Reefs, Hurricane Tracking Rob Hudson, PhotoScience; Kathy Fitzpatrick et al., Martin County Govt.

53 53 Ch. 6 - Nearshore & Coastal Analysis e.g., Shorelines, ProfileLines, Marine Areas, object tables Hawaiian Reef Fish and MPAs Alyssa Aaby, UH; Dawn Wright, OSU

54 Ch. 7 - Model Meshes e.g., finite element Mesh Points, Mesh Elements, Scientific Mesh Juergen Schulz-Olberg, BSH (Federal Maritime & Hydrographic Agency of Germany) Michael Blongewicz, DHI Ch. 8 - Multidimensional GIS e.g., linking ArcMarine with ArcHydro and other DMs Joe Breman, ESRI; Michael Blongewicz, DHI; Pat Halpin, Duke Ch. 9 - Customizing ArcMarine especially tools for data import, filter, extraction, synching, modeling ArcMarine Poster, UML/XMI, Tool Suite on accompanying web site

55 More information dusk.geo.orst.edu/djl/arcgis includes downloads, new tutorial support.esri.com/datamodels

56 56 ArcMarine Data Model Marine Modeling Applications Implications: Allows explicit spatial & temporal relationships to be used in geoprocessing and analysis Allows for advanced tool development P.N. Halpin 2005

57 57 ArcGIS 9.2… Developments Python ScriptingPython Scripting ModelBuilderModelBuilder Geodatabase Raster SupportGeodatabase Raster Support NetCDF support NetCDF support P.N. Halpin 2005

58 58 Turtles: Cayman Islands Dive Profiles: ~4D Data (X,Y,Z,T m…m) Z X Y T m m m Geospatial tools for marine apps will need to model multiple dimensions with variable data quality… P.N. Halpin 2005

59 59 At large spatial scales: At finer spatial scales: Marine mammal distribution Bathymetric and water temperature gradients Prey availability Temporal lags Marine animal distribution Oceanography (winds,currents) Primary productivity Spatio-Temporal Models Geospatial tools for marine apps will need to model time lags… P.N. Halpin 2005

60 60 Marine mammal distribution Time Space Persistent SST Event SST in Mid-Atlantic Spatio-Temporal Models Statistical modeling approach will allow for antecedent oceanographic conditions to be used to more accurately predict potential habitat. Geospatial tools for marine apps will need to model events… P.N. Halpin 2005

61 61 Geospatial tools for marine apps will need to forecast… The emerging management applications are at these finer temporal scales… P.N. Halpin 2005

62 62 Integrating statistical models ArcRstats Multivariate Modeling Script for ArcGIS This script can be used with ArcGIS to produce predictive maps based on different techniques using the free and robust R statistical package: Generalized Linear Model (GLM) Generalized Linear Model (GLM) Generalized Additive Model (GAM) Generalized Additive Model (GAM) Classification and Regression Tree (CART) Classification and Regression Tree (CART) Best, B. D., S. Loarie, S. Qian, P. Halpin, D. Urban, ArcRstats - multivariate habitat modeling with ArcGIS and R statistical software. Available at Geospatial tools for marine apps will need to integrate multivarite statistical models…

63 63 Predicted Blue Rockfish habitat area Benthic habitat affinity models Geospatial tools for marine apps will need to integrate multivarite statistical models… P.N. Halpin 2005

64 SST Chl Depth Sampling through time and data layers… Geospatial tools for marine apps will need to automate time series data acquisition & processing… Python script NetCDF or HDF imagery Observation data time P.N. Halpin 2005

65 65 Geodatabase model structure will help with… Multivariate statistical models Multivariate statistical models Temporally dynamic data acquistion & sampling Temporally dynamic data acquistion & sampling Time sensitive predictions Time sensitive predictions ArcMarine Data model and tool development P.N. Halpin 2005 Data model standardization will promote usability of common tools and extensions…


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