Georelational Vector Data Model

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1 Georelational Vector Data Model

2 Contents Georelational Data Model Representation of Simple Features Topology Non-topological Vector Data Data Models for Composite Features

3 Geo-relational Looking at a paper map, we can tell: what map features are like. how they are spatially related to each other. Idaho borders Montana, Wyoming, Utah, Nevada, Oregon, Washington, and Canada, and contains several Indian reservations. How can computer "see" the same features and their 1 relationships?

4 Vector Data Preparation The vector data model prepares data in two basic steps: First, It uses points and their x-, y-coordinates to represent spatial features as points, lines, and areas. Second, it organizes geometry objects and their spatial relationships into digital data files that the computer can access, interpret, and process. So that the computer can process the data.

5 Vector Data Models The vector data model has undergone more changes over the past two decades than any other aspect of GIS. ESRI, Inc. has introduced a new vector data model with each new software package: Coverage with Arc/Info, Shape-file with Arc View, and Geodatabase with ArcGIS. The coverage and shape file are examples of the georelational data model, whereas the geodatabase is an example of the object-based data model.

6 GEORELATIONAL DATA MODEL Geospatial data comprise the spatial and attribute components. Spatial data describe the locations of spatial features, whereas attribute data describe the characteristics of spatial features. The georelational data model stores spatial and attribute data separately in a split system: Spatial data ("geo") in graphic files. Attribute data ("relational") in a relational database.

7 REPRESENTATION OF SIMPLE FEATURES The vector data model uses the geometric objects of point, line, and area to represent simple spatial features. A point has 0 dimension and has only the property of location. It may also be called a node, vertex, or 0-cell. A point feature is made of a point or a set of separate points. Examples: Wells, benchmarks, and gravel pits.

8 A line is one-dimensional and has the property of length. It has two end points and points in between to mark the shape of the line. It is also called an edge, link, chain, or 1-cell. A line feature is made of lines. Roads, streams, and contour lines are examples of line features.

9 An area is two-dimensional and has the properties of area (size) and perimeter. An area may contain holes, such as a national forest containing private land parcels (holes). The existence of holes means that the area has both external and internal boundaries. An area is also called a polygon, face, zone, or 2-cell.

10 Feature Representation and Scale The representation of simple features using points, lines, and areas is not always straightforward. It can depend on map scale. For example, a city on a 1:1,000,000 scale map may appear as a point, but the same city may appear as an area on a 1:24,000 scale map.

11 TOPOLOGY Topology expresses explicitly the spatial relationships between features. Topology is the study of those properties of geometric objects that remain invariant under certain transformations such as bending or stretching. For example, a rubber band can be stretched and bent without losing its intrinsic property of being a closed circuit, as long as the transformation is within its elastic limits.

12 Adjacency and Incidence If a line joins two points, the points are said to be adjacent and incident with the line. The adjacency and incidence relationships can be expressed explicitly in matrices.

13 Node 11 joined node 12 by line 2. Line 5 is incident from node 14, and incident to node 12 Adjacency Matrix nodes Incidence Matrix

14 TIGER TIGER: Topologically Integrated Geographic Encoding and Referencing. In the TIGER database, points are called 0- cells, lines 1-cells, and areas 2-cells. The TIGER database includes the spatial relationships between points, lines, and areas.

15 Topology in the TIGER database involves O-cells or points, 1-cells or lines, and 2-cells or areas.

16 Using the built-in spatial relationships, we can associate a block group with the streets or roads that make up its boundary. Likewise, we can identify an address on either the right side or the left side of a street.

17 ESRI's Coverage Model Coverage is a topology-based vector data format. The coverage model supports three basic topological relationships: Connectivity: Arcs connect to each other at nodes. Area definition: An area is defined by a series of connected arcs. Contiguity: Arcs have directions and left and right polygons.

18 Coverage Data Structure The coverage model incorporates the topological relationships into the structure of feature data. The data structure of a point coverage contains feature identification numbers (IDs) and pairs of x- and y-coordinates.

19 The data structure of a line coverage

20 The data structure of polygon coverage

21 Importance of Topology Topology-based data sets require additional data files to store the spatial relationships between features. Topology has at least two main advantages. The first is the assurance of data quality. It enable us to detect lines that do not meet correctly polygons that are not closed properly. avoid incomplete features and ensure data integrity. Second, topology can enhance GIS analysis.

22 NONTOPOLOGICAL VECTOR DATA Shapefile is a standard nontopological data format. Geometry of a shapefile is stored in two basic files: The.shp file stores the feature geometry. The.shx file maintains the spatial index of the feature geometry.

23 NONTOPOLOGICAL DATA s Advantages They can display more rapidly on the computer monitor than topology-based data. This advantage is particularly important for people who use, rather than produce, GIS data. They are nonproprietary and interoperable, meaning that they can be used across different software packages.

24 DATA MODELS FOR COMPOSITE FEATURES Composite features refer to those spatial features that are better represented as composites of points, lines, and polygons. ESRI s coverage model, for example, includes such composite features as TINs (triangulated irregular networks), regions, and routes. The inputs to a TIN include point, line, and area features.

25 Data Structure of A TIN

26 TOPOLOGY RULES

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