Basic definition of GIS
• G (Geography) - a particular form of Information System applied to
geographical data (location, co-ordinates, maps etc..)
• I (Information) S (System) is a set of processes, executed on raw data, to
produce information which will be useful in decision-making
• A series of steps from observation and collection of data through analysis to
information (Data Handling)
• The DATA into INFORMATION PATHWAY ( Data = Facts; Information =
Facts with Meaning)
Basic Usage of GIS
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• GIS as a Toolbox
• Usage of GIS for Mapping
• Static vs. Interactive Maps
• GIS as Interactive Cartography
• The Analysis Distinction - Query to Analysis
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• GIS as an Approach to Science
• GIS as a Discipline
Origin of GIS
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Computer Aided
Cartography
(CAC)
Remote Sensing
Database
(RS) Integrated Technologies
Management
Systems
GIS
(DBMS)
Computer Aided Design/
Drafting
(CAD)
Geographic Information System (GIS)
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What Is GIS - a Brief Introduction
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GISs are simultaneously the telescope, the microscope, the computer, and the
Xerox machine of regional analysis and synthesis of spatial data. (Ron Abler,
1988)
“A powerful set of tools for storing and retrieving at will, transforming and
displaying spatial data from the real world for a particular set of purposes“
(Burrough, 1986, p. 6).
“Automated systems for the capture, storage, retrieval, analysis, and display of
spatial data." (Clarke, 1995, p. 13).
"An information system that is designed to work with data referenced by spatial
or geographic coordinates. In other words, a GIS is both a database system with
specific capabilities for spatially-referenced data, as well as a set of operations
for working with the data" (Star and Estes, 1990, p. 2).
"A geographic information system is a special case of information systems where
the database consists of observations on spatially distributed features, activities
or events, which are definable in space as points, lines, or areas. A geographic
information system manipulates data about these points, lines, and areas to
retrieve data for ad hoc queries and analyses" (Dueker, 1979, p 106).
What Is GIS - a Brief Introduction
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“A system of hardware, software, data,
people, organizations and institutional
arrangements for collecting, storing,
analyzing, and disseminating information
about areas of the earth (Dueker and Kjerne,
1989)
Use of geography to
integrate
information from
different sources
Different mapping systems:
Electronic atlases
Thematic mapping systems
Street-based mapping systems
GIS: all these things + much more
analysis, import/export, combination of different
data, dynamic map update, etc
Tools for GIS
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Information Software
Remote sensing data Desktop GIS
Geographic data
Internet GIS
Hardware CAD Software
Computer Database Software
Digitizer
Multimedia (photos,
Scanner
videos, 3D models)
Printer/Plotter
Geographic data – 80% of government data collected is associated with
some location in space
Information - attributes, or the characteristics (data), can be used to
symbolize and provide further insight into a given location
System – a seamless operation linking the information to the geography –
which requires hardware, networks, software, data, and operational
procedures
…not just software! …not just for making maps!
GIS Functional Elements
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1. Acquisition
digitizing, editing, topology building, projection transformation, format
conversion, attribute assignment etc.
2. Pre-Processing
Analogue to digital
Conversion of units
3. Management
Data archival, databases (hierarchical model, networking model,
relational databases etc.)
4. Manipulation and Analysis
Buffering, overlay, connectivity operations etc.
5. Output (Product Generation)
Thematic maps, 3D birds eye view, scaled maps etc
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Why a GIS
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Old Records/maps are poorly maintained
Poorly Updated
Inaccurate
No Sharing
No data retrieval service for maps
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Benefits of GIS
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Once a GIS is implemented, following benefits are expected:
Better Maintained data
Standard format
Easy revision,
Easy updation
Easy Units conversion
Easy to share
Easier to search, analyze and represent
Many value added products
Enhance productivity of staff
Time and Money saved
Better Decision making
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GIS as a Multi-Disciplinary Science
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Combination of following traditional sciences
Geography
Statistics
Cartography
Remote Sensing
Photogrammetry
Computer Science
Operation Research
Mathematics
Surveying
Civil Engineering
Geodesy
Urban Planning
Environmental Engineering, etc.
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Alternate Names of GIS
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Land Information System (LIS)
AM/FM-Automated Mapping and Facilities
Management
Environmental Information System (EIS)
Resource Information System (RIS)
GIS Is now becoming independent DISCIPLINE in the name of
GEOINFORMATICS, or GEOSPATIAL INFORMATION SYSTEM.
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Areas of GIS Applications
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Facilities Management
e.g. PTCL, SNGPL, Irrigation, WASA, for: locating underground pipes and
cables)
Environmental and Natural Resource management
suitable lands for crops, management of forests, EIA, Disaster Management
etc.
Street Network
Car Navigation, locating houses and streets, rescue services etc.
Planning and Engineering
DAMS, Power Projects, urban planning, regional planning
Land Information System
Board of Revenue, taxation, zoning, land acquisition.
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GIS and DSS
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GIS is usually an important component of modern
Decision Support Systems (DSS)
DSS components:
Data Base
Statistical Analysis
Numerical Model
Input and output facility
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USE OF GIS as DSS
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Driving Forces:
Population,
Decision Making:
Health, Wealth,
Planning and Management
Technology,
Politics, Economic
Human Impacts: Development,
Analysis and Assessment by GIS Urbanization, Industrialization,
Construction, Energy Use
Environmental Change:
Land use Change,
Monitoring By
Change of Life Style,
Remote Sensing
Land Degradation,
Pollution, Climate Change
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GIS Software
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ESRI: ARC/INFO, ARC VIEW, ARC GIS
Intergraph: MGE
Grass Information Centre: GRASS*
Clark University: IDRISI
AUTODESK: ARC MAP
ILWIS: Integrated Land and Water Information System.
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http://grass.osgeo.org/ http://www.clarklabs.org/products/idrisi-taiga.cfm
Advantages and Disadvantages of GIS
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Advantages of GIS
Exploring both geographical and thematic components of data in a holistic
way
Stresses geographical aspects of a research question
Allows handling and exploration of large volumes of data
Allows integration of data from widely disparate sources
Allows analysis of data to explicitly incorporate location
Allows a wide variety of forms of visualisation
Limitations of GIS
Data are expensive
Learning curve on GIS software can be long
Shows spatial relationships but does not provide absolute solutions
Origins in the Earth sciences and computer science. Solutions may not be
appropriate for humanities research
Lets starts
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Basics of GIS
Basic Geographical Concepts
21 Spatial Objects
One of the most common
products of a GIS is a map
Points
Line/
node
Global to local Polygon
/chain
Basic Geographical Concepts
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Spatial Object: Delimited Geographical areas, with a number of
different kind of associated attributes
Point: A spatial object with no area. A key attribute is its geodetic
location. Many Attributes can be associated with a Point
Line: A spatial object, made up of a connected sequence of points. Lines
have no width, thus a specified location will be on one side of a line or
other, but never on a line.
Nodes: Special kinds of points showing start, end and junction of line
segments.
Polygon: A closed Area. Simple Polygons are undivided areas, while
complex polygons are divided into areas of different characteristics.
Chains: Special kinds of line segments, which corresponds to a portion
of the bounding edge of polygon.
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Basic Geographical Concepts
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Parcels: The allotment of some amount by dividing something
Basic Geographical Concepts
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Scale
Ratio of distance on map (or image) to their true length on the earth’s
surface
Large Scale: A scale is relatively large, if the area or length represented
on map (or image) is large
Small Scale: A scale is relatively small, if the area or length represented
on map (or image) is small
e.g.
1:10,000 is large scale as compared to 1:100,000.
Resolution
Refers to minimum size of the element which we can distinguish on a map.
For Raster Maps, it is size of cell
For Maps, it is
= (Area/No of elements)^0.5
Higher the resolution, more information are available.
RESEL=Resolution Element
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Basic Geographical Concepts
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Basic Geographical Concepts
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Attributes
Pertinent (important) information of geospatial data.
e.g. if a line is representing a road through geographic data (Lat., Long. or
Easting , Northing), then its helping information such as width, condition,
name, metaled or un-metaled etc. are its attributes.
Only those attributes should be selected/acquired which might be
required in the analysis.
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GIS data model (Database management systems-DBMS )
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A GIS stores information about the world as a collection of thematic layers
that can be linked together by geography
The basic data type in a GIS reflects traditional data found on a map
Spatial data
describes the absolute and relative location of geographic features.
Attribute data
describes characteristics of the spatial features. These characteristics can
be quantitative and/or qualitative in nature. Attribute data is often
referred to as tabular data.
SPATIAL DATA MODELS
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Three basic types of spatial data models have evolved for storing geographic
data digitally. These are referred to as:
Raster;
Vector;
Image.
Image data utilizes techniques very similar to raster data, however typically lacks the
internal formats required for analysis and modeling of the data
Raster data models
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Raster data models incorporate the use of a grid-cell data structure where the
geographic area is divided into cells identified by row and column.
For digital representations of aerial photographs, satellite images, scanned
paper maps, and other applications with very detailed images.
A raster data structure is in fact a matrix where any coordinate can be quickly
calculated if the origin point is known, and the size of the grid cells is known
Vector Data models
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Vector storage implies the use of vectors (directional lines) to represent a
geographic feature. Vector data is characterized by the use of sequential
points or vertices to define a linear segment. Each vertex consists of an X
coordinate and a Y coordinate.
Vector lines are often referred to as arcs and consist of a string of vertices
terminated by a node.
Geometry and Topology of Vector data
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The most popular method of retaining spatial relationships among features is to
explicitly record adjacency information in what is known as the topologic data
model
The topologic data structure is often referred to as an intelligent data structure
Topology is a mathematical concept that has its basis in the principles of feature adjacency and connectivity
Image Data models
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Image data is typically used in GIS systems as background display data (if
the image has been rectified and georeferenced); or as a graphic attribute
Image data must be converted into a raster format (and perhaps vector) to
be used analytically with the GIS
Attribute data models
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Attribute data refers to pertinent information attached to each geo-spatial
data. A variety of different database models exist for the storage and
management of attribute data. The most common are:
1. Tabular (Outdates in GIS !), 2. Hierarchial
3. Network 3. Relational
5. Object Oriented
The hierarchical database organizes data in a tree structure. Data is
structured downward in a hierarchy of tables.
The network database organizes data in a network or plex structure. Any
column in a plex structure can be linked to any other
The object-oriented database model manages data through objects.
An object is a collection of data elements and operations that together are
considered a single entity.
The object-oriented database is a relatively new model. This approach has
the attraction that querying is very natural, as features can be bundled
together with attributes at the database administrator's discretion.
Note
A separate data model is used to store and maintain attribute data for GIS
software.
These data models may exist internally within the GIS software, or may be
reflected in external commercial Database Management Software (DBMS)
Attribute database models
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Examples of object-
oriented data model
Hierarchial and network database models have not gained any noticeable acceptance
for use within GIS
Attribute data models
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A relational database organizes data in tables. Each table, is identified by a
unique table name, and is organized by rows and columns. Each column within
a table also has a unique name.
UNIQUE DOMINANT AVG. TREE STAND SITE STAND AGE
STAND COVER HEIGHT INDEX
NUMBER GROUP
001 DEC 3 G 100
002 DEC-CON 4 M 80
003 DEC-CON 4 M 60
004 CON 4 G 120
The relational database model is the most widely accepted for managing
the attributes of geographic data.
Relational Attribute model
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Basic linkages between a vector spatial data (topologic model) and attributes maintained
in a relational database file (From Berry)
Relational Attribute model
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Attribute data consists of qualitative or quantitative data. Qualitative data
specify the types of object, while quantitative data can be categorized into
ratio data, data measured in relation to a zero starting point; interval data,
data arranged into classes; and ordinal data, which specify quality by using
text.
Choice between raster and vector data
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‘Which is best? depends in 4 issues
coordinate precision
speed of analytical processing
mass storage requirements
characteristics of phenomena
Choice between raster and vector data
Spatial Data Layers (layers)
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Data on different themes are stored in separate “layers”
As each layer is geo-referenced layers from different sources can easily be
integrated using location
This can be used to build up complex models of the real world from widely
disparate sources
The definition of data layers is fully dependent
on the area of interest and the priority needs
of the GIS. Layer definitions can vary greatly
depending on the intended needs of the GIS
Required Data Sources for GIS
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As data acquisition or data input of geospatial data in digital format is most
expensive (about 80% of the total GIS project cost) and procedures are time
consuming in GIS
Advantages of Raster data
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The geographic location of each cell is implied by its position in the cell
matrix. Accordingly, other than an origin point, e.g. bottom left corner, no
geographic coordinates are stored.
Due to the nature of the data storage technique data analysis is usually easy
to program and quick to perform.
The inherent nature of raster maps, e.g. one attribute maps, is ideally suited
for mathematical modeling and quantitative analysis.
Discrete data, e.g. forestry stands, is accommodated equally well as
continuous data, e.g. elevation data, and facilitates the integrating of the two
data types.
Grid-cell systems are very compatible with raster-based output devices, e.g.
electrostatic plotters, graphic terminals.
Disadvantages of Raster data
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The cell size determines the resolution at which the data is represented.;
It is especially difficult to adequately represent linear features depending on
the cell resolution. Accordingly, network linkages are difficult to establish.
Processing of associated attribute data may be cumbersome if large amounts
of data exists. Raster maps inherently reflect only one attribute or
characteristic for an area.
Since most input data is in vector form, data must undergo vector-to-raster
conversion. Besides increased processing requirements this may introduce data
integrity concerns due to generalization and choice of inappropriate cell size.
Most output maps from grid-cell systems do not conform to high-quality
cartographic needs.
Advantages of Vector data
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Data can be represented at its original resolution and form without
generalization.
Graphic output is usually more aesthetically pleasing (traditional cartographic
representation);
Since most data, e.g. hard copy maps, is in vector form no data conversion is
required.
Accurate geographic location of data is maintained.
Allows for efficient encoding of topology, and as a result more efficient
operations that require topological information, e.g. proximity, network
analysis.
Disadvantages of Vector data
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The location of each vertex needs to be stored explicitly.
For effective analysis, vector data must be converted into a topological
structure. This is often processing intensive and usually requires extensive data
cleaning. As well, topology is static, and any updating or editing of the vector
data requires re-building of the topology.
Algorithms for manipulative and analysis functions are complex and may be
processing intensive. Often, this inherently limits the functionality for large
data sets, e.g. a large number of features.
Continuous data, such as elevation data, is not effectively represented in
vector form. Usually substantial data generalization or interpolation is
required for these data layers.
Spatial analysis and filtering within polygons is impossible
Comparison b/w raster and vector data
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Thank you !
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