Fundamental GIS Concepts

1
Fundamental GIS Concepts

• POEC 6381 Introduction to GIS
• Ronald Briggs
• University of Texas at Dallas

2
Representing Geographic Features

• How do we describe geographical features?
• by recognizing two types of data
• Spatial data which describes location (where)
• Attribute data which specifies characteristics
  at that location (what and how much)
• How do we represent these digitally in a GIS?
• by grouping into themes based on similar
  characteristics (e.g hydrography, elevation,
  water lines, sewer lines, grocery sales) and
  using either
• vector data model (coverage in ARC/INFO,
  shapefile in ArcView)
• raster data model (GRID in ARC/INFO)
• by selecting appropriate scale, projection,
  accuracy level, and resolution
• How do we incorporate into a computer application
  system?
• by using one or other of two types of computing
  environments
• relational data base model (RDBMS) ( such as
  Arc/Info)
• object oriented model (ArcView,
  Smallworld--although ArcView presents data to
  user as RDBMS)

3
Spatial and Attribute Data

• Spatial data (where)
• specifies location
• stored in a shape file in Arcview
• Attribute (descriptive) data (what and how much)
• specifies characteristics at that location,
  natural or human-created
• stored in a data base table
• GIS systems traditionally maintain spatial and
  attribute data separately, then join them for
  display or analysis
• for example, in ArcView, the Attributes of
  table is used to link a shape file (spatial
  structure) with a data base table containing
  attribute information in order to display the
  attribute data

4
Spatial Data Types

• continuous elevation, rainfall, ocean salinity
• areas
• unbounded landuse, market areas, soils, rock
  type
• bounded city/county/state boundaries, ownership
  parcels, zoning
• moving air masses, animal herds, schools of fish
• networks roads, transmission lines, streams
• points
• fixed wells, street lamps, addresses
• moving cars, fish, deer

5
Attribute data types

• Numerical(may be expressed as integer whole
  number or floating point decimal fraction)
• interval
• known distance between values
• cant say twice as much
• temperature (Celsius or Fahrenheit)
• ratio
• natural zero
• ratios make sense (e.g. twice as much)
• income, age, rainfall

• Categorical (name)(often coded to numbers eg
  SSN but cant do arithmetic)
• nominal
• no inherent ordering
• land use types, county names
• ordinal
• inherent order
• road class stream class

Attribute data tables can contain locational
information, such as addresses or a list of X,Y
coordinates. ArcView refers to these as event
tables. However, these must be converted to true
spatial data (shape file), for example by
geocoding, before they can be displayed as a map.
6
GIS Data Models Raster v. Vectorraster is
faster but vector is corrector Joseph Berry

• 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
• much data comes in this form
• images from remote sensing (LANDSAT, SPOT)
• scanned maps
• elevation data from USGS
• best for continuous features
• elevation
• temperature
• soil type
• land use

• 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
• much data comes in this form
• DIME and TIGER files from US Census
• DLG from USGS for streams, roads, etc
• census data (tabular)
• best for features with discrete boundaries
• property lines
• political boundaries
• transportation

7
Concept of Vector and Raster
Real World
Raster Representation
Vector Representation
point
line
polygon
8
Representing Data using Raster Model

• area is covered by grid with (usually)
  equal-sized cells
• location of each cell calculated from origin of
  grid two down, three over (usually from upper
  left, but lower left in ARCVIEW)
• cells often called pixels (picture elements)
  raster data often called image data
• attributes are recorded by assigning each cell a
  single value based on the majority feature
  (attribute) in the cell, such as land use type.
• easy to do overlays/analyses, just by combining
  corresponding cell values yield rainfall
  fertilizer (why raster is faster, at least for
  some things)
• simple data structure
• directly store each layer as a single table
  (basically, each is analagous to a
  spreadsheet)
• no computer data base management system required
  (although some GIS systems incorporate them)

9
Representing Data using the Vector Model
general concept

• The fundamental concept of vector GIS is that all
  geographic features in the real work (or on a
  map) can be represented either as
• points or dots (nodes) trees, poles, fire
  plugs, airports, cities
• lines (arcs) streams, streets, sewers,
• areas (polygons) land parcels, cities, counties,
  forest, rock type
• Which is used in a particular instance depends on
  scale, among other things airport or manhole may
  be a point or polygon
• Because representation depends on shape, ArcView
  refers to files containing spatial data as
  shapefiles (altho. these used for both vector and
  raster)

10
Representing Data using the Vector Model formal
application
.

• point (node) 0-dimension
• single x,y coordinate pair
• zero area
• tree, oil well, label location
• line (arc) 1-dimension
• two (or more) connected x,y coordinates
• road, stream
• polygon 2-dimensions
• four or more ordered and connected x,y
  coordinates
• first and last x,y pairs are the same
• encloses an area
• census tracts, county, lake

y2
Point 7,2
x7
Line 7,2 8,1
Polygon 7,2 8,1 7,1 7,2
11
Representing Data using the Vector Model data
implementation

• Features in the theme (coverage) have unique
  identifiers--point ID, polygon ID, arc ID, etc
• common identifiers provide link to
• coordinates table (for where)
• attributes table (for what)

Y

• concepts are those of a relational data base,
  which is really a prerequisite for the vector
  model (or need object-oriented computing
  environment)

12
Scale, Projection, Accuracy and Resolutionkey
project parameters

• Scale the ratio of distance on a map to the
  equivalent distance on the ground
• in theory GIS is a scale independent but in
  practice there is an implicit range of scales
  for any project
• Projection the method by which the curved 3-D
  surface of the earth is represented by X,Y
  coordinates on a 2-D map/screen surface.
• distortion is inevitable
• Accuracy most fundamentally, how close, on
  average, features in the GIS are to their true
  location on the earth
• Resolution the size of the smallest feature
  which can be recognized
• for raster data, it is the pixel size

The tighter the specification, the higher the
cost.
13
Computing Environments Classical Data Base

• Classical Data Base Computing Environments
• data strictly separated from computer code
  (instructions/programs) which process that data
• data is maintained in a data base
• relational data base management systems (RDBMS)
  contain multiple tables made up of rows
  (entities, such as counties) and columns
  (attributes, such as population counts)
• tables can be joined together (related) on the
  fly based on common identifiers (ids) (such as
  county name)
• until recently, this was considered to be
  compute intensive
• because spatial data has even more stringent
  performance requirements (to produce graphics
  with reasonable response time), GIS systems
  traditionally used proprietary , special purpose
  RDBMS (such as INFO)
• now, the GIS industry is incorporation industry
  standard RDBMSs (ORACLE, INGRES, INFORMIX,
  SYBASE)

14
RDBMS Example
15
Computing Environments Object Oriented
Environment

• Object Oriented Computing Environment
• Object an entity that contains data (or
  properties) and the code to act on that data.
• thus, code is integrated with data
• especially suited to complex data types, which
  can not easily be represented in row/column
  format, such as multi-media and spatial data
• objects are intended to be reusable components,
  which can be combined to produce other
  applications or desired results
• most new GIS software implementations (including
  ArcView) are object based
• object components for doing fundamental GIS
  operations (e.g. draw map, pan, zoom,
  projections) can also be purchased (e.g ESRIs
  Map Objects)

16
Data Representation and Project Designthe
relevance of these issues for GIS Projects

• selecting vector or raster as basis for project
• usually dependent on the nature of the data
• natural resource people favor raster urban folks
  favor vector
• decision is reflected in the choice of GIS
  software package
• selecting software which uses either the raster
  or the vector model for internal data
  representation,
• most have conversion capabilities for the other
  data type
• some (eg ARC/INFO GRID) also have analysis
  capabilities
• however, accuracy/performance/capability hit if
  data doesnt match software model
• if use vector, electing to represent features as
  point or polygon, or line or polygon
• every real-world feature has some area
• generally depends on scale
• manhole generally a point, unless facilities
  management at 150 scale
• traditional computing environment v. object
  oriented approach
• if starting from scratch, have the option to
  select the latest technology
• if established, can be exceedingly costly (data,
  training) to convert
• Critical decisions in initial project planning,
  especially the first two.
• Can be major stumbling-blocks in joint projects
  between different agencies/depts..