1. Nicholas A. Procopio, Ph.D, GISP
Environmental GIS
Nicholas A. Procopio, Ph.D, GISP

2. Data Types In GIS, there are three main types of data Spatial
Attribute
Metadata
Zygo, Lisa, Baylor University, Lecture Notes, 2002

3. Data Sources Data Types
Primary – Measurements collected through first-hand observations
Secondary – Measurements collected through a secondary source (i.e., neighborhood surveys)

4. Metadata Data documentation Data about the data
Explains the form, content, accuracy, precision, usability, creator, purpose, etc.
Metadata standards exist
Metadata is a part of geospatial data

5. Metadata Metadata information includes
Identification – title, area, dates, owners, organizations, etc.
Data quality – attribute accuracy and spatial precision, consistency, sources of info, and methods of data production
Spatial data organization – raster-vector format and organization of features in the data set, data model
Spatial reference – map projections, datums, and coordinate system

6. Metadata Metadata is created to… Protect investment in data
Staff turnover, memory loss
Makes it easier to reuse and update data
Provides documentation of sources, quality
Easier to share data
Helping the user understand the data
Provides consistent terminology
Focuses on key elements
Helps user determine fitness for use
Facilitates data transfer, interpretation by new users

7. Federal Geographic Data Committee
Under Executive Order No , all federal agencies and organizations must document their geospatial data using the FDGC Content Standard for Digital Geospatial Metadata

8. Federal Geographic Data Committee
Compliance with this executive order will…
Minimize duplication of data
Foster cooperative digital data collection activities
Establish a national framework of quality data

9. Metadata
Use ArcCatalog to create and edit metadata

10. Database Models
Database – a collection of non-redundant data, which can be shared by different application systems
Geographic database – database linked to geographic data for a particular area and subject.

12. Attribute Data The “where” of GIS is determined by the spatial data
The “what” is determined by the attribute data
The attribute data is just as important as the spatial data

13. Databases
Attribute data are stored in database tables

14. Databases Advantages of a DBMS include
Reduced redundancy of data duplication
Various data access methods are possible (queries)
Data is stored independently of the application for which they will be used
Access to data is controlled and data is centralized
Ease of updating and maintaining data

15. Creating a database Consider the following… Storage media
How will the database change over time?
What security is needed?
Should the database be distributed or centralized?
How should database creation be scheduled?

16. Codd’s Principles for Databases
Only one value per cell
All values in a column are about the same subject
Each row is unique
No significance to the sequence of columns
No significance to the sequence of rows
Keep your table simple!

17. Attribute Types Qualitative No measurement or magnitude
Non-numeric descriptions
No numeric meaning, even if shown as code numbers (i.e., 1=category 1)

18. Attribute Types Quantitative Numeric and have mathematical meaning
Serve as measurements or magnitudes of the features they refer
Example: city population

19. Types of Databases Relational
Presents data organized in a series of two-dimensional tables, each containing records for one entity

20. Relational Database
Flexible approach to linkages between records comes closest to modeling the complexity of spatial relationships between objects
Links attributes contained in separate files with a key attribute
The key attribute is usually a non-redundant, unique identification number for each record
The most popular DBMS model for GIS

21. Data Most data is input into a database by keycoding
Other data may be obtained through government sources
USGS
US Census
NOAA
State Agencies
Data may also be obtained from other projects

22. Methods of Spatial Data Entry
Manual “heads-up” digitizing
Scanners
Appropriate for encoding raster data since this is the output format for most scanners.
Problems may include
Scanning unwanted information
Optical distortion
The higher the resolution, the more volume of data produced

23. Methods of Spatial Data Entry
Electronic Data Transfers
Downloading data from the internet
Downloading data from a GPS unit
Consider when obtaining electronic data
What data is available
Cost
Media
Format

24. Sources of Electronic Data
United States Geological Survey (USGS)
Digital Line Graphs (DLG)
Digital Elevation Models (DEM)
Digital Orthophoto Quads (DOQ)
United States Census Bureau (USCB)
Topologically Integrated Geographic Encoding Reference System (TIGER)
First comprehensive GIS database at street level for entire U.S.
National Oceanographic and Atmospheric Agency (NOAA)
Satellite and radar images
Bathymetry maps

25. Other Sources of Spatial Data
Field Data
Global Positioning System (GPS)
Locating position from receiving a signal from orbiting satellites
Manual Input
Remote Sensing
Utilizing satellite images to develop a base view of area of interest

26. Spatial Data Models

27. Spatial Databases Real world is infinitely complex
Database size is limited
Data model converts real world into elements that can be stored in a database

28. Toward Realism: Layers
A GIS breaks down reality into different layers (themes)
A layer can be composed of identical entities such the locational information for trees, manholes, buildings, etc.
Layers can be overlapped to show the spatial relationship between various entities
Layers can also represent different times

29. Spatial Databases
There are two primary models for spatial data in a GIS
Raster
a data structure or model based on grid cells
Vector
a data structure composed of nodes, vertices, and arcs or connected points

30. Raster Data Models
Individual cells are used as the building blocks for creating point, line, and polygon entities
Size of the cell very important because it will reflect how entities are displayed (i.e., more specific shape with greater number of cells).
Cell represents some attribute or a reference ID to a table of attributes

31. Raster Data Model
Raster data are ideal for continuous data such as air temperatures, water pH, etc.
What happens when two categories occupy the same cell?

32. Raster Spatial Databases
Single objects displayed by shading individual cells
Linear features displayed by shading a sinuous series of connected cells
Polygon features displayed by shading a group of connected cells
Relief can be shown by assigning a certain value to each selected cell

33. Raster Data Models
Cells may be homogenous (each cells contains the same feature) or heterogeneous (one cell contains varying features)
Heterogeneity may be resolved by
Simply looking for the presence or absence of features
Looking at the cell center to determine placement of index code
Dominant area analysis
Transition cells
Percentages

34. Spatial Databases Advantages of Raster Format Simple data structure
Compatible with remotely sensed or scanned data
Simple spatial analysis procedures

35. Spatial Databases Disadvantages of Raster Format
Requires large storage space
Graphical output may be less pleasing (depending on resolution)
Projection transformations more difficult
Difficult to maintain topology

36. Vector Spatial Databases
Vector data models arose in the early 1960’s in relation to the development of the hierarchical attribute data structure
The first generation were simply lines with an arbitrary start and ending point
Files would typically consist of a few long lines and many short lines
Often referred to as cartographic spaghetti

37. Spatial Databases Vector Data Model
Uses two-dimensional Cartesian coordinates to store the shape of a spatial entity.
The point is the basic building block from which all other spatial entities are constructed.
Lines and areas are constructed by connecting a series of points

38. Vector Data Models
Uses two-dimensional Cartesian coordinates to store the shape of a spatial entity.
The point is the basic building block from which all other spatial entities are constructed.
Lines and areas are constructed by connecting a series of points (nodes and vertices)

39. Vector Spatial Databases
Advantages
Requires less storage space
Topology easily maintained
Graphical output usually more pleasing

40. Vector Spatial Databases
Disadvantages
More complex data structure
Not compatible with remotely sensed data
Spatial analysis operations more difficult
Selecting appropriate number of points to display feature
Too few points would compromise shape or spatial properties (area, perimeter, etc.)
Too many points means possible data duplication and increase costs in terms of data storage

41. Advancing Toward Topology
The arc/node model developed as a “hierarchy” for spatial data
Based on the principle that each type of structure consists of features built upon simpler features
Coordinates make up points
Connected points make lines
Connected lines make polygons
Allows the user to differentiate between points, line, and polygons, but requires maintenance of links between features

42. Topologic Models This new model allowed for drawing a line only once
For example:
If two polygons shared a side, that shared side would have to be traced when both polygons were drawn
This would allow for the possibility of gaps or slivers between the individual lines (topological error)
The new system avoided the error because the one arc “told” which polygon was to the left and which polygon was on the right

43. Topological Terms Nodes Nodes Arcs Vertices Arcs Vertices
Where a line begins, ends, or where two lines intersect
Vertices
Where a line bends
Arcs
Line segment between two nodes
Nodes
Arcs
Vertices

44. Topology Example 6 2 3 4 5 1 7 9 10 11 8 A 1 x y 2 x y 3 x y 4 x y
1 1,2,3,4,5,6,7
2 1,7,8,9,10,11
Arcs File 6 2 3 4 5 1 7 9 10 11 8 A
1 x y
2 x y
3 x y
4 x y
5 x y
6 x y
7 x y
8 x y
9 x y
10 x y
11 x y
Points File
A: 1, 2, Area, Attributes
Files of arcs by polygons

45. Topology Example
Topology not attained!
Sliver
Topology is attained!

46. Summary of Data Models Real World 1 Raster Windmills 0 = No Data
Raster Windmills
0 = No Data
1 = Windmill
Vector Windmills

47. Summary of Data Models Raster Vector Every location given an object
Every object is given a location

48. Data Conversion
Data can be transformed from one of these data models to the other
You always loose some information when going from one data format to the other
Vectorization
Rasterization

49. Rasterization Loose topological features Positional accuracy decreases
Vector Format
Raster Format
Zygo, Lisa, Baylor University, Lecture Notes, 2002

50. Vectorization
Features look “jagged” or “pixelated” in the vector representation
Topology is created
Raster Format
Vector Format
Zygo, Lisa, Baylor University, Lecture Notes, 2002

51. Vector Representations of Surfaces
A vector surface is modeled by creating a series of irregularly placed points as vertices
Each of the vertices has an explicit topographic value
Any 3 points are connected to represent an area of the same topography (triangle)
Triangulated irregular network (TIN) a vector data model that uses Delaunay triangulation as a means of explicitly storing surface information

52. The topology of a TIN

53. TINs Contain separate files for arcs triangles
Became a popular way to show elevation, etc. for visualization and engineering
Allowed for contouring, 3-D views, water flow directions, etc.
Many CAD GIS systems use TINs

54. Aronoff, 1993. Geographic Information Systems: A Management Perspective. Ottawa : WDL Publications.

55. Digital Elevation Model

56. Examples of applications that use the TIN data model
Landslide risk map for Pisa, Italy (Courtesy of Earth Science Department, University of Siena, Italy)
(B) Yangtse River, China
(Courtesy of Human Settlements Research
Center, Tsinghua University, China)