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A Hierarchical Vector Data Model for Distributed Geospatial Processing Eric B. Wolf Barbara P. Buttenfield University of Colorado at Boulder NSF BCS 0451509 Presentation for the AAG National Conference 2007
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A Hierarchical Vector Data Model for Distributed Geospatial Processing

Jan 04, 2016

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A Hierarchical Vector Data Model for Distributed Geospatial Processing. Eric B. Wolf Barbara P. Buttenfield University of Colorado at Boulder NSF BCS 0451509. Presentation for the AAG National Conference 2007. The Problem. Spatial data is compiled by NMAs at fixed scales: - PowerPoint PPT Presentation
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Page 1: A Hierarchical Vector Data Model for Distributed Geospatial Processing

A Hierarchical Vector Data Model for Distributed Geospatial

Processing

Eric B. WolfBarbara P. ButtenfieldUniversity of Colorado

at BoulderNSF BCS 0451509

Presentation for the AAG National Conference 2007

Page 2: A Hierarchical Vector Data Model for Distributed Geospatial Processing

The Problem

Spatial data is compiled by NMAs at fixed scales:

• E.g., 1:24,000, 1:100,000, 1:1,000,000 Mixing fixed-scale data corrupts topology. Incorrect generalization -> incorrect modeling

output. Lack of persistent storage for generalized

representations.

Presentation for the AAG National Conference 2007

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Our Project: MRVIN

MRVIN: Multiple Representations for Vector INformation. A hierarchical architecture for vector geospatial data. Provides multiple representations across a range of

resolutions. Preserves topology within each data theme and between

data themes. Sustains distributed data retrieval through standard

interfaces.

Presentation for the AAG National Conference 2007

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Previous Work

Ramer 1972, Douglas-Peucker 1973 Ballard 1981 Herschberger and Snoeyink 1992 Saalfeld 1999 Bertolotto and Egenhofer 1999 Buttenfield 2002

Presentation for the AAG National Conference 2007

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Ballard Strip Tree (1981)

• HierarchicalMBR

• Efficient storage search

• Complete RDP order

Page 6: A Hierarchical Vector Data Model for Distributed Geospatial Processing

Creation of Strip-Trees

Presentation for the AAG National Conference 2007

Page 7: A Hierarchical Vector Data Model for Distributed Geospatial Processing

MRVIN Data Structure

Presentation for the AAG National Conference 2007

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Mathematical Topology

A topology on a set X is a collection T of subsets of X having the following properties:

1. Ø and X are in T

2. The union of elements of any

subcollection of T is in T

3. The intersection of the elements of any finite subcollection of T is in T

Munkres, J. R. 2000. Topology. Second ed. Upper Saddle River, NJ: Prentice Hall. P. 76.

Presentation for the AAG National Conference 2007

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Examples of Topologies

Equivalent Topologies Comparable Topologies

Presentation for the AAG National Conference 2007

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Internal & Relative Topology

Presentation for the AAG National Conference 2007

Self-Crossing Feature

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Preserving Topology

“If two convex hulls do not overlap, the contents of those hulls will not overlap.” (Saalfeld 1999)

Presentation for the AAG National Conference 2007

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Preserving Topology in Multi-Part Features

Compound Vectors are stored as “groves” of “trees”

The convex hull for each tree is calculated and stored.

A convex hull for the grove is calculated and stored.

Saalfeld’s test is applied among all trees in each grove and among groves.

Presentation for the AAG National Conference 2007

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Preserving Relative Topology

Presentation for the AAG National Conference 2007

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MRVIN Architecture

Presentation for the AAG National Conference 2007

Page 15: A Hierarchical Vector Data Model for Distributed Geospatial Processing

Extending MRVIN to points and polygons. Managing dimensional collapse (when a

polygon becomes a line or a point) ArcGIS script like “TerraServer Download”. Merge MRVIN into PostGIS and extend

Minnesota Map Server to create tiles from MRVIN for WMS access.

Keyhole Markup Language output for Google Earth.

Future Research

Presentation for the AAG National Conference 2007