Lecture 04 : Vector Data Models (link to Powerpoint file)
Lab 04: Vector Data Overview
Homework 03: Data Sets and Projections
GIS in Archaeology: Vector Data Models
Vector Data Model
Discrete data are general stored as "vector" data. There are three common basic vector data types: points, lines and polygons.
Vector Model Development
Early GIS systems visualized data as spaghetti structures.
Topological Data
Topology refers to the spatial relationships of features to one another (e.g. left side, right side, intersection, etc.). There are various ways to store topology within a GIS file. For ESRI, the standard topological data format is called a coverage. Coverages have three topological relationships:
1. Connectivity: Arcs connect to each other at nodes
2. Area definition: Areas are defined by a series of connected arcs
3. Contiguity: Arcs have directions and left and right polygons
Arc/Node Vector Model (Nodes)
Basic unit of Arc/Node model is a Node. In an arc/node model areas consist of lines and lines consist of points. A node is basically a point.
Arc/Node Vector Model (Arcs)
Arcs are line segments that connect at nodes (connectivity). Arcs link nodes in a particular direction (contiguity). Arcs can link 2 or more nodes.
Arc/Node Vector Model (Areas)
Areas are defined by a series of arcs that form a closed boundary. Arc table also contains information polygon contiguity (left/right). Area table identifies the arcs that bound the area.
Non-Topological Data
Spatial data can be stored in a topological format on in one that does not contain topological information. Non-topological data formats do not store the spatial relationship between geographic features. For ESRI, the standard non-topological data format is the shapefile. Non-topological data can be displayed much more rapidly.
Topological vs. Non-Topological Data
Non-topological data can be displayed much more rapidly. Non-topological data have a similar overall structure. Topological data are much more flexible. Topological data allow for automated data entry detection and cleaning (can easily spot open polygons or overshoots). Topology is necessary to do any spatial analysis with vector data. It used to be too computationally expensive to do spatial analysis with non-topological data.
Complex Data Models
Triangulated Irregular Networks (TIN) divide space into non-overlapping triangles and is often an efficient way for displaying topography.