It’s the Geography, Cupid!

GTECH 201 Lecture 04 Introduction 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 modeling logical data modeling physical 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 001deciduous3G dec/con4M dec/con4M coniferous4G 120 Forest Inventory

Geo-Relational Principle

Database Relations

Further Reading ANSI/SPARC model Laurini & Thompson. Fundamentals of GIS, p Chrisman’s Spheres Chrisman, N Exploring Geographic Information Systems Key Text for Concepts De Mers, M Fundamentals of Geographic Information Systems. NY: John Wiley & Sons