ArcGIS Data Models: ArcGIS Data Models: Marine Data ModelMarine Data Model

Dawn Wright - Oregon State UniversityDawn Wright - Oregon State UniversityPat Halpin - Duke UniversityPat Halpin - Duke University

Michael Blongewicz - DHIMichael Blongewicz - DHIJoe Breman - ESRIJoe Breman - ESRI

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Polling QuestionsPolling Questions

• What is your name, organization, and email?What is your name, organization, and email?– (Add yourself to a data models user group list, and you will be (Add yourself to a data models user group list, and you will be

sent notifications about webcasts, design studios, etc.)sent notifications about webcasts, design studios, etc.)

• Which of the following ESRI data types do you most Which of the following ESRI data types do you most commonly use?commonly use?– a) Coveragea) Coverage– b) Shapefileb) Shapefile– c) Geodatabase feature classc) Geodatabase feature class

• Are you interested in seeing a data model webcast, Are you interested in seeing a data model webcast, participating in a design studio, and for which data participating in a design studio, and for which data model?model?

• Where on the web do you get data?Where on the web do you get data?

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AgendaAgenda

• Marine data model overview and toolsMarine data model overview and tools– The use of schema and templatesThe use of schema and templates– Tools designed and tested with marine data model case studies.Tools designed and tested with marine data model case studies.– Multidimensional modeling.Multidimensional modeling.

• Model elementsModel elements– Feature DatasetsFeature Datasets– Object classesObject classes– RelationshipsRelationships

• Historical IterationsHistorical Iterations– Subclasses versus SubtypesSubclasses versus Subtypes

• Current StatusCurrent Status– Ready to be usedReady to be used– Book coming next yearBook coming next year

• Presentation of tools and uses of a Marine GeodatabasePresentation of tools and uses of a Marine Geodatabase

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

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The Data Modeling CycleThe Data Modeling Cycle Conceptual, logical, and physical modelsConceptual, logical, and physical models

Conceptual ModelConceptual ModelSketches, Flow Diagrams, Sketches, Flow Diagrams,

etc.etc.

Logical ModelLogical ModelDiagram in CASE ToolDiagram in CASE Tool

ArcCatalog ToolsArcCatalog Tools

Physical ModelPhysical ModelDatabase SchemaDatabase Schema

Business RulesBusiness Rules

Real World Real World Objects and RelationshipsObjects and Relationships

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What is a Data Model?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

FeatureFeature

ObjectIDObjectIDGeometryGeometry

LandObjectLandObject

LandObjectIDLandObjectIDTransactionIDTransactionIDSystemStartDateSystemStartDateOfficialStartDateOfficialStartDateOfficialEndDateOfficialEndDate

SurveyPointSurveyPoint SurveyBoundarySurveyBoundary

PointPoint

MeasurementMeasurement

ComputationComputation

CoordinateCoordinate

ProjectProject

Geodatabase

**

**

** **

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What’s in a Data Model Template?What’s in a Data Model Template?

• A pre-designed schema of ObjectsA pre-designed schema of Objects• Feature classesFeature classes• TablesTables• RelationshipsRelationships• DomainsDomains• SubtypesSubtypes

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Using a Design TemplateUsing a Design TemplateSchema Wizard reads repository or template to create a geodatabaseSchema Wizard reads repository or template to create a geodatabase

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ArcGIS Data Models Web siteArcGIS Data Models Web sitehttp://support.esri.com/datamodelshttp://support.esri.com/datamodels

• 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

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Path forward for multiD modelingPath forward for multiD modeling

• Extend existing functionality to support time and Extend existing functionality to support time and other variables of multidimensional data.other variables of multidimensional data.

– Animation manager used to control variables such as Animation manager used to control variables such as time to set the animation sequence.time to set the animation sequence.

– Improve quality and interaction of charting and include Improve quality and interaction of charting and include as an animation object.as an animation object.

– Added support for the NetCDF data format building on Added support for the NetCDF data format building on existing layer capabilities.existing layer capabilities.

– 3D interpolation3D interpolation

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Tools - netCDF at 9.2Tools - netCDF at 9.2

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NetCDF in ArcGISNetCDF in ArcGIS

Can be accessed as:Can be accessed as: • RasterRaster• FeatureFeature• TableTable

Direct read and writeDirect read and writeGIS data to netCDFGIS data to netCDF

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

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Using NetCDF as a feature, raster or table in the GISUsing NetCDF as a feature, raster or table in the GIS(network common data format)(network common data format)

• Behaves the same as any layer or table in:Behaves the same as any layer or table in:– DisplayDisplay

Same display tools for raster and feature layers Same display tools for raster and feature layers will work on netCDF raster and netCDF feature will work on netCDF raster and netCDF feature layers.layers.

– ChartingChartingDriven by the table just like any other chart.Driven by the table just like any other chart.

– AnimationAnimation Multidimensional data can be animated through Multidimensional data can be animated through

a variable (e.g. time, pressure, elevation)a variable (e.g. time, pressure, elevation)– Geoprocessing ToolGeoprocessing Tool

A netCDF raster layer will work just like any other A netCDF raster layer will work just like any other raster layer, same for feature layers and tables.raster layer, same for feature layers and tables.

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Geoprocessing ModelsGeoprocessing Models Model Builder diagrams for workflowModel 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

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3D points displayed in volume space3D points displayed in volume space

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3D Interpolation tool3D Interpolation toolSample resulting from collaboration between data Sample resulting from collaboration between data

models and ESRI developer Network (EDN)models and ESRI developer Network (EDN)

New tools New tools based on based on data model data model prototypes prototypes and case and case study testing.study testing.

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Demo Marine Data ModelDemo Marine Data Model

3D interpolation tool3D interpolation tool

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Marine Data ModelMarine Data Model

• Overview -Model elementsOverview -Model elements– Feature Datasets and feature classesFeature Datasets and feature classes– Object classesObject classes– RelationshipsRelationships

• Historical IterationsHistorical Iterations– Subclasses versus SubtypesSubclasses versus Subtypes

• Current StatusCurrent Status– Ready to be usedReady to be used– Book coming next yearBook coming next year

• Presentation of tools and uses of a Marine GeodatabasePresentation of tools and uses of a Marine Geodatabase

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The Feature data setThe Feature data setStores the spatial reference for all featureStores the spatial reference for all feature classes it classes it

contains, including the extents of their m and z valuescontains, including the extents of their m and z values– Feature ClassesFeature Classes

• Marine FeaturesMarine Features– TimeSeries PointsTimeSeries Points– InstantaneousPointsInstantaneousPoints

» Instant, Instant, Survey, Survey, Sounding,LocationSeriesSounding,LocationSeries– ProfileLineProfileLine– ShorelineShoreline– TrackTrack– TimeDurationAreaTimeDurationArea

• Mesh FeaturesMesh Features– MeshPointsMeshPoints

» GridPoint, NodePointGridPoint, NodePoint– MeshElementsMeshElements

• indicates classes covered in detailindicates classes covered in detail

Feature Data Sets and Feature ClassesFeature Data Sets and Feature Classes

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Object Classes (Tables)Object Classes (Tables)– Object ClassesObject Classes

• SurveyInfoSurveyInfo - stores parameters of a survey - 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• ParameterParameter - stores the properties of a given parameters - stores the properties of a given parameters• ScalarQuantityScalarQuantity - stores magnitude data values - stores magnitude data values• VectorQuantityVectorQuantity - stores directional data values - stores directional data values• MeasurementMeasurement - storing depths related to a specific Measurements - 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

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– RelationshipsRelationships• 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 modelRelationships in the model(You may only need to use one or two of these for your (You may only need to use one or two of these for your

individual project)individual project)

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ClassificationClassification

Historical IterationsHistorical Iterations– Subclasses versus SubtypesSubclasses versus Subtypes

-CruiseID : esriFieldTypeInteger

MeasurementPoint

-PointType : esriFieldTypeInteger = 4

LocationSeries

-PointType : esriFieldTypeInteger = 2

Sounding

-TimeValue : esriFieldTypeDate-ZValue : esriFieldTypeDouble-SurveyID : esriFieldTypeInteger-SeriesID : esriFieldTypeInteger«SubtypeField» -PointType : esriFieldTypeInteger = 1

InstantaneousPoint{GeometryType = esriGeometryPoint}

-PointType : esriFieldTypeInteger = 3

Survey

-PointType : esriFieldTypeInteger = 1

Instant Subtype

TimeSeriesPoint{GeometryType = esriGeometryPoint}

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Presentation of tools Presentation of tools and uses of the data modeland uses of the data model

– Varying uses and means of adapting the data modelVarying uses and means of adapting the data model

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– 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, Example: Bathymetric Survey, CTD Drops,

XX

YY

23.06.05 18:00:0023.06.05 18:00:00

ZZ

Instantaneous PointsInstantaneous Points

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– SurveyID - SurveyID - • foreignkey relating to SurveyInfoforeignkey relating to SurveyInfo

– SurveyInfo - • stores properties about the survey

– StartDate– EndDate– Description– DeviceID– TrackID

XX

YY

23.06.05 18:00:0023.06.05 18:00:00

ZZ

InstantaneousPoints.SurveyInstantaneousPoints.Survey

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Demo of the Marine Data ModelDemo of the Marine Data ModelSurvey Point ExampleSurvey Point Example

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– a feature class designated for deriving additional along a line.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 Surveysone ProfileLine can be associated to many Surveys– many Survey can be associated to many ProfileLinesmany Survey can be associated to many ProfileLines

– Example: Transects, Coastline EvolutionExample: Transects, Coastline Evolution

ProfileLineProfileLine

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InheritanceInheritance

-FeatureID : esriFieldTypeInteger-FeatureCode : esriFieldTypeString

MarineFeature

MarineLine

-Orientation : esriFieldTypeDouble-RecordedTime : esriFieldTypeDate-TransectType : DHI_LineTypes = 1

-TransectSource : esriFieldTypeString

DHI_Transect{GeometryType = esriGeometryPolyline,

HasM = True,

HasZ = True}

DHI_Baseline

{GeometryType = esriGeometryPolyline,HasM = True}

-SurveyID : esriFieldTypeInteger

-StartDate : esriFieldTypeDate-EndDate : esriFieldTypeDate-StartJDay : esriFieldTypeInteger

-EndJDay : esriFieldTypeInteger-SurveyDesc : esriFieldTypeString

-SourceFile : esriFieldTypeString-MDeviceID : esriFieldTypeInteger

SurveyInfo

1

*

1*

ProfileLine{GeometryType = esriGeometryPolyline,

HasM = True,

HasZ = True}

-FeatureID : esriFieldTypeInteger-SurveyID : esriFieldTypeInteger

SurveyKey

The Design and Intent of ProfileLineThe Design and Intent of ProfileLine

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Demo of Marine Data ModelDemo of Marine Data ModelProfileLine ExampleProfileLine Example

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– a subclass of MeasurementPointa subclass of MeasurementPoint – fixed in space (X,Y)– multiple Z Values via Measurement Table

– Example: Moored Buoy, ADCP

TimeSeriesPointTimeSeriesPoint

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TimeSeriesPoint with MeasurementsTimeSeriesPoint with Measurements

11**

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– includes feature classes: 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 FeaturesDesign and Intent of Mesh Features

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RelationshipsRelationships

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Demo Marine Data ModelDemo Marine Data Model MeshPoint ExampleMeshPoint Example

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Geodatabase DiagrammerGeodatabase DiagrammerCreate graphical representation of geodatabase once completeCreate graphical representation of geodatabase once complete

Framework and Publication of:Framework and Publication of:

ArcMarineArcMarine

Marine data model bookMarine data model book

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ArcMarine PurposeArcMarine Purpose

• YourYour Geodatabase Template Geodatabase Template– Data collection at sea/shore … to final geoprocessing, analysisData 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 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 developmentCommon/shared tool development– Rapid prototypingRapid prototyping– Linkage to processing modelsLinkage to processing models

• Data Sharing/NetworkingData Sharing/Networking• ““Schooling” in the GdbSchooling” in the Gdb

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ArcMarine Design StrategyArcMarine Design Strategy

Image modified from original by P. Halpin, Duke

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Implementation ProcessImplementation Process

DraftLogical Design

DraftConceptual Design

Prototype

UpdatedConceptual Design

UpdatedLogical Design

Pilot Project

UpdatedConceptual Design

UpdatedLogical Design

Production

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

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ArcMarine: A Geospatial Framework ArcMarine: A Geospatial Framework for Ocean and Coastal Analysisfor Ocean and Coastal Analysis

• ESRI Press, 2006ESRI Press, 2006– By Wright, Blongewicz, Halpin, BremanBy Wright, Blongewicz, Halpin, Breman

• Full background documentation with ~10 case Full background documentation with ~10 case studiesstudies

• Chapter 1 - Introduction (Why ArcMarine?)Chapter 1 - Introduction (Why ArcMarine?)• Chapter 2 - Conceptual Framework and Chapter 2 - Conceptual Framework and

Common Marine Data TypesCommon Marine Data Types

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ArcMarine Thematic LayersArcMarine Thematic Layers

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ArcMarine Thematic LayersArcMarine Thematic Layers

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Marine Marine Marine

ArcMarine …Chapters 3-6

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Ch. 3 - Marine SurveysCh. 3 - Marine Surveyse.g., Inst. Points, Time Duration Line, Survey & Cruise object tablese.g., Inst. Points, Time Duration Line, Survey & Cruise object tables

Louisiana SubsidenceLouisiana SubsidenceHeather Mounts, PhotoScience, FLHeather Mounts, PhotoScience, FL

Essex MG&G SurveyEssex MG&G SurveyBrian Andrews, USGS-Woods Hole, MABrian Andrews, USGS-Woods Hole, MA

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Source: http://www.po.gso.uri.edu/SST/

Sea Turtle Tracks (Caretta caretta)Sea Surface Temperature (WCR)

Source: http://obis.env.duke.edu/datasets/ (Read & McClellan2004)

OBIS, OBIS, Pat Halpin et al., Duke U.Pat Halpin et al., Duke U.

Ch. 4 - Marine Animal TrackingCh. 4 - Marine Animal Trackinge.g., Location Series Points, Time Duration Lines and Areas, e.g., Location Series Points, Time Duration Lines and Areas,

object tables and rastersobject tables and rasters

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Ch. 5 - Time Series & MeasurementsCh. 5 - Time Series & Measurementse.g., Time Series Points, Profile Line, Time Series/Meas object tablese.g., Time Series Points, Profile Line, Time Series/Meas object tables

North Atlantic, Irish SeaNorth Atlantic, Irish SeaMartina Hennesey et al., Marine Institute, Galway, IRELANDMartina Hennesey et al., Marine Institute, Galway, IRELAND

Eamonn Doyle, Rob Morrison, ESRI-IRELANDEamonn Doyle, Rob Morrison, ESRI-IRELAND

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Ch. 6 - Nearshore & Coastal AnalysisCh. 6 - Nearshore & Coastal Analysise.g., Shorelines, ProfileLines, Marine Areas, object tablese.g., Shorelines, ProfileLines, Marine Areas, object tables

Martin County, FL Artificial Reefs, Hurricane TrackingMartin County, FL Artificial Reefs, Hurricane TrackingRob Hudson, PhotoScience; Kathy Fitzpatrick et al., Martin County Govt.Rob Hudson, PhotoScience; Kathy Fitzpatrick et al., Martin County Govt.

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Ch. 6 - Nearshore & Coastal AnalysisCh. 6 - Nearshore & Coastal Analysise.g., Shorelines, ProfileLines, Marine Areas, object tablese.g., Shorelines, ProfileLines, Marine Areas, object tables

Hawaiian Reef Fish and MPAsHawaiian Reef Fish and MPAsAlyssa Aaby, UH; Dawn Wright, OSUAlyssa Aaby, UH; Dawn Wright, OSU

Ch. 7 - Model MeshesCh. 7 - Model Meshese.g., finite element Mesh Points, Mesh Elements, Scientific Meshe.g., finite element Mesh Points, Mesh Elements, Scientific Mesh

Juergen Schulz-Olberg, BSHJuergen Schulz-Olberg, BSH(Federal Maritime & Hydrographic Agency of Germany)(Federal Maritime & Hydrographic Agency of Germany)

Michael Blongewicz, DHI Michael Blongewicz, DHI

Ch. 8 - Multidimensional GISCh. 8 - Multidimensional GISe.g., linking ArcMarine with ArcHydro and other DMse.g., linking ArcMarine with ArcHydro and other DMs

Joe Breman, ESRI; Michael Blongewicz, DHI; Pat Halpin, Duke Joe Breman, ESRI; Michael Blongewicz, DHI; Pat Halpin, Duke

Ch. 9 - Customizing ArcMarineCh. 9 - Customizing ArcMarineespecially tools for data import, filter, extraction, synching, modelingespecially tools for data import, filter, extraction, synching, modeling

ArcMarine Poster, UML/XMI, Tool SuiteArcMarine Poster, UML/XMI, Tool Suiteon accompanying web siteon accompanying web site

More informationMore information

dusk.geo.orst.edu/djl/arcgisdusk.geo.orst.edu/djl/arcgisincludes downloads, new tutorialincludes downloads, new tutorial

support.esri.com/datamodelssupport.esri.com/datamodels

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ArcMarine Data ModelArcMarine Data Model

Marine Modeling ApplicationsMarine Modeling Applications

Implications:Implications:

Allows explicit spatial & temporal relationships Allows explicit spatial & temporal relationships to be used in geoprocessing and analysisto be used in geoprocessing and analysis

Allows for advanced tool development Allows for advanced tool development

P.N. Halpin 2005P.N. Halpin 2005

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ArcGIS 9.2… DevelopmentsArcGIS 9.2… Developments

• Python ScriptingPython Scripting

• ModelBuilderModelBuilder • Geodatabase Raster Geodatabase Raster SupportSupport

• NetCDF supportNetCDF support

P.N. Halpin 2005P.N. Halpin 2005

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Turtles: Cayman IslandsTurtles: Cayman Islands

Dive Profiles:Dive Profiles:~4D Data (X,Y,Z,T m…m~4D Data (X,Y,Z,T m…m))

Z X

Y

T

m mm

Geospatial tools for marine apps will need to model Geospatial tools for marine apps will need to model multiple multiple dimensions with variable data qualitydimensions with variable data quality……

P.N. Halpin 2005P.N. Halpin 2005

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At large spatial scales:

At finer spatial scales:

Marine mammaldistribution

Bathymetric and water temperature gradients

Preyavailability

Temporal lagsTemporal lags

Marine animaldistribution

Oceanography (winds,currents)

Primaryproductivity

Spatio-Temporal Models

Geospatial tools for marine apps will need to model Geospatial tools for marine apps will need to model time lagstime lags……

P.N. Halpin 2005P.N. Halpin 2005

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Marine mammaldistribution

Time

2002-122002-12

2003-012003-01

2003-022003-02

2003-032003-03

2003-042003-04

2003-052003-05

Space

“Persistent” SST Event

SST in Mid-Atlantic

Spatio-Temporal Models

Statistical modeling approach will Statistical modeling approach will allow for allow for “antecedent”“antecedent” oceanographic conditions to be oceanographic conditions to be used to more accurately predict used to more accurately predict potential habitat.potential habitat.

Geospatial tools for marine apps will need to model Geospatial tools for marine apps will need to model eventsevents……

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Geospatial tools for marine apps will need to Geospatial tools for marine apps will need to forecastforecast……

The emerging management applications are at these finer temporal scales…The emerging management applications are at these finer temporal scales…

P.N. Halpin 2005P.N. Halpin 2005

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Integrating statistical models Integrating statistical models

ArcRstatsArcRstatsMultivariate Modeling Script for ArcGISMultivariate Modeling Script for ArcGISThis script can be used with ArcGIS to produce This script can be used with ArcGIS to produce predictive maps based on different techniques predictive maps based on different techniques using the free and robust R statistical package:using the free and robust R statistical package:

• Generalized Generalized LinearLinear Model (GLM) 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, 2005. ArcRstats - multivariate habitat modeling with ArcGIS and R statistical software. Available at http://www.nicholas.duke.edu/geospatial/software .

Geospatial tools for marine apps will need to Geospatial tools for marine apps will need to integrate integrate multivarite statistical modelsmultivarite statistical models……

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Predicted Blue Rockfish habitat area

Benthic habitat affinity modelsBenthic habitat affinity models

Geospatial tools for marine apps will need to Geospatial tools for marine apps will need to integrate integrate multivarite statistical modelsmultivarite statistical models……

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1998-08

1998-07-01

SSTSST

ChlChl

DepthDepth

Sampling through time and data layers…Sampling through time and data layers…

Geospatial tools for marine apps will need to Geospatial tools for marine apps will need to automate time automate time series data acquisition & processingseries data acquisition & processing……

1998-07-02

1998-07-04

1998-07-03

Python scriptPython scriptNetCDF or HDF NetCDF or HDF

imageryimagery

Observation dataObservation data

timetime

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Geodatabase model structure will help with…Geodatabase model structure will help with… • Multivariate statistical modelsMultivariate statistical models

• Temporally dynamic data acquistion & samplingTemporally dynamic data acquistion & sampling

• Time sensitive predictionsTime sensitive predictions

ArcMarine Data model and tool developmentArcMarine Data model and tool development

P.N. Halpin 2005P.N. Halpin 2005

Data model standardization will Data model standardization will promote usability of common promote usability of common tools and extensions…tools and extensions…