It’s the Geography, Cupid!

GTECH 201

Lecture 04Introduction

to Spatial Data

Today’s Content

Types of spatial data

World models

Spatial data models

Spatial data structures

The geo-relational principle

Types of Spatial Data

Locations or regions Relative positions

Points, lines, or areas

Regular vs. irregular

Continuous vs. discrete

Geostatistical Data –aka random field data

Measurements taken at fixed locations

Spatially continuous

Small-scale variation

Tobler’s Law of Geography

Lattice Data

Regular lattice Satellite image

Irregular lattice Polygon map

Spatial Point Patterns

Distribution of locations

e.g., bald eagles or earth quakes

Why do we Need Models?

It wont fit!

Vector View

Raster / Image View

What is where? versus Where is what?

“What is where?” – Vector

space is occupied by objects that are described by their attributes

“Where is what?” – Raster

variation of an attribute as a continuous field

Raster Vector

Each world view presents different aspects of the “real” world

Thus we can:• ask different questions (e.g. apply different

operations)

• get different answers (e.g. apply different analytical tools)

…….. so choose carefully

Raster Vector continued

Converting between the raster and vector data models results in error

Chrisman’s Spheres

ANSI-SPARC Model for Software Development

GIS are systems to model the world

User Model

Conceptual Model

Operational Model

GIS are Systems to Model the World

User Model – how we intuitively think

Conceptual Model

Operational Model

ANSI-SPARC Model for software development

User Model

Conceptual Model

Operational Model

ANSI-SPARC Model for software development

how we systematically define ideas

GIS are Systems to Model the World

User Model

Conceptual Model

Operational Model how we fuse systematic thinking into

a technologically defined context

GIS are Systems to Model the World

The ANSI/SPARC Model and Chrisman’s Spheres

computer science

geoinformation theory

application disciplines context discipline

spatial modeling

conceptual modelinglogical data modelingphysical data modeling

OPERATIONAL

Digital Maps as Models

• Representing a complex reality

• Continuous variation

• Spatial Data: spatial, temporal and thematic

• Data Models

What sort of Models are These?

Raster Model - The world as regular tessellations defined by areal property

Vector Model - The world as points, lines, areas and attributes….. making objects

Object Model - The world as interacting entities with spatial dimensions

Vector Data Models

Spaghetti model

Topological models

A file of spatial data that is a just a collection of co-ordinate strings. Each entity (or piece of spaghetti) is represented by one data entry. There is no topology.

Topology refers to the spatial relationships between objects. The topological model represents spatial relationships such as:

- length - area - connectivity - contiguity

Raster Models

Pros : Simple, computer friendly, scanner friendly, field- friendly, compressible

Cons : Large, unstructured, inflexible

Vector Models

Pros : Structure, cognitive consonance(!), compactness(?), accuracy

Cons : Inflexibility, complexity, spuriously precise(?), atemporal

Object-centered Models

Pros : Structure, power, potential process links, consistency(?)

Cons : Extreme complexity, power hungry

Data Structure

Attributes

unique stand number

dominant cover group

avg. tree height

stand site index

stand age

001 deciduous 3 G 100

002 dec/con 4 M 80

003 dec/con 4 M 60

004 coniferous 4 G 120

Forest Inventory

Geo-Relational Principle

Database Relations

Further Reading

ANSI/SPARC model

Laurini & Thompson. Fundamentals of GIS, p.357-362

Chrisman’s Spheres

Chrisman, N. 1997. Exploring Geographic Information Systems

Key Text for Concepts

De Mers, M. 2004. Fundamentals of Geographic Information Systems. NY: John Wiley & Sons