1. URBDP 422 URBAN AND REGIONAL GEO-SPATIAL ANALYSIS
Lecture 1: Principles of GIS
Class Overview
Lab Session:
Exercise 1: Revisiting ARCGIS
Jan 7, 2014

2. URBDP 422 URBAN AND REGIONAL
GEO-SPATIAL ANALYSIS
Class Overview

3. Karis Tenneson (Puruncajas) Office: Gould 432 E-mail: karist@uw.edu
Instructor:
Karis Tenneson (Puruncajas)
Office: Gould 432
Co-instructors:
Karen Dyson
Gould

4. Objectives 1. Develop an understanding of spatial data
and principles of spatial analysis.
2. Acquire skills to design, develop and maintain
a geo-database.
3. Learn how to structure and perform spatial
data analysis and modeling.
4. Develop critical skills in the analysis and
evaluation of spatial data.

5. Class Structure
Lectures
Lab Exercises
Team Project
Mid-Term
Final Exam

6. Readings Required and Recommended Articles and Book Chapters
are posted on line on the Web Site

7. Lecture Topics Principles of GIS Spatial Data Models
Building a Geo-Database
Spatial Data Exploration
Describing the Urban Landscape
Classifying the Urban Landscape
Quantifying the Urban Landscape I: Vector Analysis
Quantifying the Urban Landscape II: Raster Analysis
Vector vs. Raster Analysis
Exploring the Effect of Scale
Surface Analysis and Interpolation
Urban Modeling
Landscape Change Modeling
Environmental Modeling
Data Representation and Mapping
Errors and Quality Control

8. Team Project Project idea Project design Data preparation
Spatial analysis
Final report
Presentation

9. Performance Grades are calculated as follows: Lab Exercises 20%
Team Project 30%
Mid-term exam 25%
Final exam 25%

10. Class Web Site:

11. Lecture 1: Outline What is a Geographic Information System?
What is powerful about GIS? What is challenging?
Why is GIS Useful to Planners?
Spatial Data Models: Vector vs. Raster
Building a Geo-database
What is Topology?
ARCGIS overview

12. Geospatial analysis
Geospatial analysis provides a distinct perspective on the world, a unique lens through which to examine events, patterns, and processes that operate on or near the surface of our planet.

13. Geographic Information Systems
A Geographic Information System (GIS) is a computer-based information system that enables to efficiently capture, store, update, manipulate, analyze, and display all forms of geographically referenced information.
Worboys 1995

14. The GIS Data Model Data is organized by layers, coverages, or themes.
Layers are integrated using explicit location on
the earth’s surface.

15. Geo-referenced data
Geo-referenced data describes objects from the real world in terms of:
- their positions with respect to a coordinate system
- their attributes that are unrelated to position
- their spatial interrelations with each other

16. Geo-referenced data + Geo-reference: xy coordinates Attribute Data:
i.e. Land Use
Dwelling Units
Land Value
Topology:
Arc-Node
Polygon-Arc
Left-Right

17. Which of these are spatial queries? All? None?
“What is the % of people driving to
work at each location?”
“How many people living within 2 miles
from a bus station do drive to work?”
“What is the shortest route passing
through a number of given locations?

18. Types of questions Source: Burrough 1986 - Where is object A?
- Where is A in relation to B?
- How many occurrence of type A are there within
distance D of B?
- What is the value of function Z at position X?
- How large is B? (Area, Perimeter)
- What is the result of intersecting layer A and layer B?
- What is the path of least cost or distance from X to Y
along pathway P?
- What is at points X1, X2,…?
- What objects are next to objects having certain attributes?
- Reclassify objects having certain combination of attributes.
- Simulate the effect of process P over time T for a given
scenario S.
Source: Burrough 1986

19. Example: Urban growth patterns in central Puget Sound

20. Space Matters!
A geospatial perspective starts from the assumption that spatial relationships (i.e. co-location, distance, direction, adjacencies, neighborhood) on the Earth surface can explain and predict Earth’s phenomena.
Spatial heterogeneity
Spatial probability
Spatial dependence
Spatial autocorrelation

21. Geospatial Analysis
Geospatial analysis allow us to determine the magnitude of the effect of spatial relationships on such phenomena.
Geospatial analysis support science through:
-integrating layers of data
-search for pattern
-testing hypotheses
-dynamic modeling

22. What is powerful about GIS?
- The ability to perform multiple spatial analytical functions
The use of location to integrate multiple diverse data sets
- The detection of spatial patterns not readily apparent
- The capacity to represent multiple data sets spatially
- The interface with multiple data base and models -

23. What is challenging about GIS?
Complexity of database development
Integration of data from diverse source
Accuracy of data input and maintenance
Representation of dynamic data
Representation of fuzzy data

24. Why is GIS Useful to Planners?
– Government and public service
Tax Assessment/Zoning/Monitoring
– Business service and planning
Business Location
– Transportation planning
Routing Optimization
– Logistics and transportation
Emergency Evacuation
– Environment
Land Use Change

25. Why is GIS Useful to Planners?
Planning Applications
Examples
Government and public service
Tax Assessment/Zoning
Transportation planning
Routing Optimization
Growth management
Built-out/Capacity Analysis
Environment
Critical and Sensitive Areas
Transportation
Route selection/Traffic analysis
Hazard Management
Emergency Evacuation
Neighborhood Planning
Walkable pedestrian catchments
Business service
Business Location

26. Why is GIS Useful to Planners?
Mapping locations: GIS can be used to identify and map locations: where certain features are.
Mapping quantities: GIS can be used to quantify features that meet certain criteria or relationships between features.
Mapping patterns: GIS can be used to explore patterns. For example a density map can be used to examine the spatial distributions of features and detect patterns.
Mapping distances: GIS can be used to find out what's occurring within a set distance of a feature.
Mapping change: GIS can be used to monitor change through time and assess the results of a policy.

27. GIS Data Structures Attribute Data Spatial Data flat files
hierarchical databases
relational databases
object-oriented database
Spatial Data
raster data structure
vector data structure

28. DIGITAL SPATIAL DATA RASTER VECTOR Real World
Source: Defense Mapping School
National Imagery and Mapping Agency

29. Spatial Data Structures
Raster Representation
Vector Representation
point
line
polygon

30. Spatial Data Structures
Vector data model
location referenced by x,y coordinates, which can be linked to form lines and polygons
attributes referenced through unique ID number to tables
Examples
DIME and TIGER files from US Census
DLG from USGS for streams, roads, etc
best for features with discrete boundaries: i.e. soil type, land use
Raster data model
location is referenced by a grid cell in a rectangular array (matrix)
attribute is represented as a single value for that cell
Examples
images from remote sensing (LANDSAT, SPOT)
elevation data from USGS
best for continuous features:
i.e. elevation, temperature
Source: Briggs 1997

31. Spatial Data Structures
Raster data are described by a cell grid, one value per cell
Vector
Raster
Point
Line
Zone of cells
Polygon

32. Points
A point is a 0 dimensional object and has only the property of location (x,y)
Points can be used to Model features such as a well, building, power, pole, sample location ect.
Other name for a point are vertex, node
Point

33. Lines
A line is a one-dimensional object that has the property of length
Lines can be used to represent road, streams, faults, dikes, maker beds, boundary, contacts etc.
Lines are also called an edge, link, chain, arc
In an ArcInfo coverage an arc starts with a node, has zero or more vertices, and ends with a node
Linea

34. Areas (Polygons)
A polygon is a two-dimensional object with properties of area and perimeter
A polygon can represent a city, geologic formation, dike, lake, river, etc.
Other name for polygons face, zone
Area

35. GIS associates spatial and attribute
information in a geo-referenced database
ARC
Source: ESRI 2004

36. Relational Data Bases

37. Object-oriented Data Bases
Feature
Object
Relationship

38. Topology
Topology is the term that describes the spatial relationships between points, lines and areas.
Technically it is a geometrical term, which describes the properties of an object that are unaffected by continuos distortion. You can distort a square to a parallelogram, but all four sides still connect at the corners.

39. If a map is distorted, some of its properties change:
- distances
- angles
- relative proximity
Other properties remain constant, including:
- adjacencies
- most other relationships, such as "is contained in", "crosses", etc.
- types of spatial objects - areas remain areas, lines remain lines, points remain points.
Topological properties are those which remain unchanged after distortion

40. ArcGIS Topology
Source: ESRI 2004

41. How Is Topology Implemented in ArcGIS?
Topology is implemented as a set of integrity rules that define the behavior of spatially related geographic features and feature classes.
Topology rules, when applied to geographic features or feature classes in a geodatabase, enable GIS users to model such spatial relationships.
For example:
-Containment (do parcel polygons overlap?)
Connectivity (are all of road lines connected?)
Adjacency (are there gaps between parcel polygons?).
Topology is also used to manage the integrity of spatial databases (i.e., coincidence between different features)
Source: ESRI 2004

42. Topology in ArcGIS Topology is used to o Integrate feature geometry
o Validate feature geometry
o Define relationships between features

43. Three views of GIS
Source: ESRI 2004

44. Building a Geodatabase
Source: ESRI 2001

45. The ArcGIS Desktop
ArcGIS Desktop is a suite of integrated applications including
ArcMap, ArcCatalog, ArcToolbox, ModelBuilder, and ArcGlobe.
Using these applications together, you can perform any GIS task,
simple to advanced, including mapping, data management,
spatial analysis, data editing, geoprocessing and visualization.

46. ArcMap ArcMap is the central application in ArcGIS for all map-based
tasks including cartography, map analysis, and editing.
Source: ESRI 2004

47. ArcCatalog The ArcCatalog application organizes and manages all
GIS information such as maps, globes, data sets, models,
metadata, and services.
Source: ESRI 2004

48. ArcGlobe ArcGlobe, part of the ArcGIS 3D Analyst extension,
provides continuous, multiresolution, interactive viewing
of geographic information.
Source: ESRI 2004

49. Geoprocessing With ArcToolbox and ModelBuilder
Geoprocessing involves deriving information through analysis
of existing GIS data and is a critical function in all GIS software
modeling language for building work flows and scripts.
ArcToolbox ArcToolbox contains a comprehensive set of geoprocessing
functions including tools for data management, data conversion,
data processing, Geocoding, and statistical analysis
ModelBuilder The ModelBuilder interface provides a modeling framework for
designing and implementing geoprocessing models that can
include tools, scripts, and data. Models are data flow diagrams
that link together a series of tools and data files.
Source: ESRI 2004

50. Application Servers
ArcGIS Server: a platform for building server-side GIS applications in enterprise and Web computing frameworks.
ArcIMS (Internet Map Server): GIS Web server to publish maps, data, and metadata through open Internet protocols.
ArcSDE (Spatial Data Engine): an interface for managing geodatabases in different relational database management systems (RDBMS).