Geographic Information System unit 1

OCE 552 - Geographic
Information System

Syllabus
UNIT I FUNDAMENTALS OF GIS 9
Introduction to GIS - Basic spatial concepts - Coordinate Systems - GIS and
Information Systems – Definitions – History of GIS - Components of a GIS – Hardware,
Software, Data, People, Methods – Proprietary and open source Software - Types of data –
Spatial, Attribute data- types of attributes – scales/ levels of measurements.
UNIT II SPATIAL DATA MODELS 9
Database Structures – Relational, Object Oriented – ER diagram - spatial data models –
Raster Data Structures – Raster Data Compression - Vector Data Structures - Raster vs
Vector Models TIN and GRID data models - OGC standards - Data Quality.
UNIT III DATA INPUT AND TOPOLOGY 9
Scanner - Raster Data Input – Raster Data File Formats – Vector Data Input –Digitiser –
Topology - Adjacency, connectivity and containment – Topological Consistency rules –
Attribute Data linking – ODBC – GPS - Concept GPS based mapping.
UNIT IV DATA ANALYSIS 9
Vector Data Analysis tools - Data Analysis tools - Network Analysis - Digital Education
models - 3D data collection and utilisation.
UNIT V APPLICATIONS 9
GIS Applicant - Natural Resource Management - Engineering - Navigation - Vehicle
tracking and fleet management - Marketing and Business applications - Case studies.

Text Books
1. Kang - Tsung Chang, Introduction to Geographic
Information Systems, McGraw Hill Publishing, 2nd Edition,
2011.
2. Ian Heywood, Sarah Cornelius, Steve Carver, Srinivasa
Raju, “An Introduction Geographical Information Systems,
Pearson Education, 2nd Edition,2007.

Course Objectives
 To introduce the fundamentals and components of
Geographic Information System
 To provide details of spatial data structures and input,
management and output processes.
Course Outcomes
 Have basic idea about the fundamentals of GIS.
 Understand the types of data models.
 Gain knowledge on data quality and standards.
 Get knowledge about data input and topology.
 Gain knowledge on various data analysis tools.
 Understand data management functions and data output

Unit-wise CO mapping
CO’s AIMED CO 1 CO 2 CO 3 CO 4 CO 5 CO 6
UNIT 1 3
UNIT 2 3 3
UNIT 3 3
UNIT 4 3
UNIT 5 3

Introduction to
Geographic Information
System

 A geographic information system (GIS) is
a system of hardware, software, data,
people, organization and institutional
arrangement for collecting, storing, analyzing
and disseminating information about areas of
the Earth.
a computer system for capturing, storing,
checking, and displaying data related to
positions on Earth's surface.
a system designed to capture, store,
manipulate, analyze, manage, and present all
types of geographical data.

 Geographic information system (GIS) is
defined as an information system
designed to work with data referenced by
spatial / geographical coordinates.
 Every object present on the earth can be
“geo referenced”, is the fundamental key
of associating any database to GIS.
 Geo- referencing refers to the location of
a layer of coverage in space defined by
the co-ordinate reference system.

What is a GIS?
A means of storing,
retrieving, sorting,
and comparing
spatial data
to support some
analytic process.
+
Information System
Geographic Position

Basic spatial concepts
 A Geographic Information system(GIS)
is a system of computer application that
can be used to display, manipulate and
analyze spatially varied information
from multiple sources all in one place
 GIS dataset can be separated into two
categories:
1. Spatial or Geographical information
2. Tabular or Attribute information

1. Spatial or Geographical information
Spatial data is data that is geo-referenced
or location specific shown graphically on the
computer screen. Each piece of graphical
information is called features which can be
points, line or polygon.
2. Tabular or Attribute information
It is the text based or numerical
information that describe each of the features.
The tabular information is linked to the
graphical information which includes a Unique
ID number used to represent each point, line or
polygon. Ex. of tabular data can include such
things as addresses, coordinates, area, length,
sales information, road names, etc.

Spatial data
(ARC functions)
Attribute data
(INFO or TABLES functions)
1 (Universe polygon)
2 3
4 5
GIS Storage
3
COV# ZONE ZIP
1 0
2 C-19 22060
3 A-4 22061
4 C-22 22060
5 A-5 22057
3 A-4 22061

Types of spatial data
 Raster data
It is in the form of images such as aerial
photographs or imported scans of old maps.
The raster data stores the location and color
value of each pixel that forms the image.
 Vector data
The information is stored using a
combination of location specific point, lines or
Arcs.(XY Coordinates)
Raster images can loss quality and become
blurred when scaled. However, Vector data is
scalable to any size without losing any
integrity.

Representing Spatial
Elements
• RASTER
• VECTOR
• Real World

Representing Spatial Elements
Raster
Stores images as rows and columns of numbers with a
Digital Value/Number (DN) for each cell.
Units are usually represented as square grid cells that are
uniform in size.
Data is classified as
“continuous” (such as in an
image), or “thematic”
(where each cell denotes a
feature type.
Numerous data formats
(TIFF, GIF, ERDAS.img etc)

Vector
Allows user to specify specific spatial locations and
assumes that geographic space is continuous, not
broken up into discrete grid squares
We store features as sets of X,Y coordinate pairs.
Representing Spatial Elements

Entity Representations
Points - simplest
element
Lines (arcs) - set of
connected points
Polygons - set of
connected lines
We typically represent objects in space as
three distinct spatial elements:
We use these three spatial elements to represent real world features and attach
locational information to them.

GIS FUNCTIONALITY
(What do they do?)

GIS Functions
 Data Assembly
 Data Storage
 Spatial Data Analysis and
Manipulation
 Spatial Data Output

GIS Functions
Data Assembly
Maps RSI
Intel Database Direct Entry
Keyboard
GPS

GIS Functions
 Common Manipulation
◦ Reclassification
◦ Map Projection changes
 Common Analysis
◦ Buffering
◦ Overlay
◦ Network
Spatial Data Manipulation and Analysis

Spatial Analysis
 Overlay function creates new
“layers” to solve spatial problems

GIS Functions
 Tables
 Maps
 Interactive Displays
 3-D Perspective View
Spatial Data Output

Coordinate Systems
 Coordinate system is a reference system for
identifying locations on the curved surface of the
earth.
 Locations on the earth’s surface are measured in
angular units from the center of the earth relative
to two planes: the plane defined by the equator
and the plane defined by the prime meridian
(which crosses Greenwich England). A location is
therefore defined by two values: a latitudinal value
and a longitudinal value.
 Coordinate Systems for Chennai
13.0827° N, 80.2707° E
 Coordinate Systems for Canada
56.1304° N, 106.3468° W

 Locations on the earth’s surface are
measured in angular units from the
center of the earth relative to two
planes:
1. the plane defined by the
equator(latitude value)
2. the plane defined by the prime
meridian.(longitude value)

 A map projection bridges the two
types of coordinate systems(x and y
coordinates)
The process of projection transforms
the Earth’s surface to a plane, and
the outcome is a map projection,
ready to be used for a projected
coordinate system.

The angular measures of longitude and latitude may be
expressed in degrees-minutes-seconds (DMS),
decimal degrees (DD), or radians (rad). Given that 1
degree equals 60 minutes and 1 minute equals 60
seconds, we can convert between DMS and DD. For
example, a latitude value
of 45°52'30" would be equal to 45.875° (45 + 52/60 +
30/3600). Radians are typically used in computer
programs. One radian equals 57.2958°, and one
degree equals 0.01745 rad.

Datum
 Mammoth collection of monument
locations in the late 1800s. Researchers
installed brass or aluminum disks at each
reference location. Each monument location
was connected using mathematical
techniques like triangulation
 NAD27 - North American Datum of 1927 . It
is a network of standardized horizontal
positions on North America. Researchers
gathered approximately 26,000 stations in
the United States and Canada. At each
station, surveyors collected latitudes and
longitude coordinates

 NAD83 - Researchers benchmarked
approximately 250,000 stations. This set
of horizontal positions formed the basis
for the North American Datum of 1983
(NAD83). In 1983, the NAD27 datum
was eventually replaced with NAD83. It
provides latitude and longitude and
some height information
 WGS84 - Unifying a Global Ellipsoid
Model with GPS. The radio waves
transmitted by GPS satellites enable
extremely precise Earth measurements
across continents and oceans.

MAP PROJECTION
A map projection transforms the geographic
coordinates on an ellipsoid into locations on a
plane. The outcome of this transformation
process is a systematic arrangement of
parallels and meridians on a flat surface
representing the geographic coordinate
system.
Three types of map projections are
 Cylindrical
 Conic
 Azimuthal

Cylindrical Map Projections
 straight coordinate lines with
horizontal parallels crossing meridians
at right angles

Conic Map Projections
These maps are defined by the cone constant,
which dictates the angular distance
between meridians

Common Map Projection
 Robinson Projection
 Transverse Mercator Projection
 Lambert Conformal Conic
 Space Oblique Mercator

Robinson Projection
• World maps “look right” rather than
measure precisely.
• Used in many popular maps such
as the Rand McNally series (from
the 1960s) and the National
Geographic Society (since 1988)

Transverse Mercator Projection
 The Transverse Mercator projection is
widely used around the world and works
especially well for mapping areas smaller
than a few degrees longitudinally, such as
a state or country

Lambert Conformal Conic
 This projection is one of the best to use
for middle latitudes and is often used for
aeronautical charts, aviators, and maps
with wide east-west extents

Space Oblique Mercator
 This map projection was developed fairly
recently, in 1976, for the specific
purpose of mapping of imagery from an
orbiting satellite around the ellipsoidal
Earth

GIS and INFORMATION SYSTEM
 In a GIS, user
connect data with geography.
 Geographic Information Systems really
comes down to just 4 simple ideas:
 Create geographic data
 Manage it.
 Analyze it and…
 Display it on a map.
 It’s REALLY hard to visualize the locations
of latitudes and longitudes coordinates
from a spreadsheet.

 But when user add these positions on
a map, it’s like magic to the reader.

GIS and INFORMATION
ARCHITECTURE
 The Architecture (structure) of a GIS
can be split into three main
components,
1. A user-interface / client: allows the user to
interact and use GIS tools through a graphical
user interface (GUI).
2. An application engine / server: the collection of
tools available for the user to manipulate and
analyze GIS data
3. A database: the data stored as files or web
services and the associated database
management software

COMPONENTS OF GIS
 Five Components of Geographic
Information System are:
◦ Hardware
◦ Software
◦ Data
◦ People
◦ Methods

1.Hardware: Hardware is Computer on which
GIS software runs.
Main Hardware Components are:
 Motherboard
 Hard Drive
 Processor
 RAM
 Printer
 External Disk
 Monitor

2.Software: Next component is GIS
software which provide tools to run and
edit spatial information.
 It helps to query, edit, run and display
GIS data.
 It uses RDBMS (Relational Database
Management System) to store the
data.
 Few GIS software list: ArcGis, ArcView
3.2, QGIS, SAGA GIS.

 Software Components:
 GIS Tools: Key tools to support the
browsing of the GIS data
 RDBMS
 Query Tools
 GUI: Graphical User Interface that helps
user and Software to interact well.
 Layout: Good layout window to design
map.

3.Data: The most important and expensive
component of the Geographic Information
System is Data which is generally known
as fuel for GIS.
GIS Data Types:
 Raster: Raster image store information
in a cell based manner.
 Vector: Vector data are discrete. It store
information in x, y coordinate format.
There are three types of Vector data:
Lines, Points and Area.

4.People: People are user of
Geographic Information System. They
run the GIS software.
5. Methods: For successful GIS
operation a well-designed plan and
business operation rules are important.

Proprietary and
Open-source GIS
Software

Proprietary and Open-source
GIS Software
 GIS software is broadly classified in two types
1. Proprietary GIS Software or Commercial
2. Open-source GIS Software
 Proprietary Software:
Proprietary software, also known as "closed-source
software", is a non-free computer software for
which the software's publisher or another person
retains intellectual property rights
 Open source Software:
The term "open source" refers to something people
can modify and share because its design is publicly
accessible.

Some examples of Proprietary Software and Open source
Software are given in the table below:
S.No Proprietary GIS Software Open Source GIS Software
1 ESRIs ArcGIS GeoDa
2 AutoCAD Map3D and
Autodesk Geospatial
GRASS
3 Bentley Map gvSIG
4 GeoMedia ILWIS
5 Global Mapper MapWindow
6 Manifold System OpenJump
7 MapInfo QGIS
8 Maptitude SAGA GIS
9 Smallworld uDig
10 TerrSet

Types of data –
Spatial, Attribute
data

TYPES OF DATA
 A geodatabase is a database that is in
some way referenced to locations on the
earth.
 GIS data can be separated into two
categories: spatially referenced data
which is represented by vector and raster
forms (including imagery) and attribute
tables which is represented in tabular
format. Within the spatial referenced data
group, the GIS data can be further
classified into two different types: vector
and raster.

 Every house, every tree, every city
has its own unique latitude and
longitude coordinates.
 The two primary types of spatial data
are vector (Discrete) and raster
(Continuous) data.

Discrete versus continuous data
 A second subdivision of the values
assigned to each cell are the values
representing discrete or continuous data.
 Discrete data
Discrete data, sometimes called
categorical data, most often represents
objects. These objects usually belong to a
class (for example, soil type), a category (for
example, land-use type), or a group (for
example, political party).
Discrete data is best represented by
ordinal or nominal numbers.

 Continuous data
 A continuous raster dataset or surface can
be represented by a raster with floating-
point values (referred to as a floating-point
raster dataset) or occasionally by integer
values.
 The value for each cell in the dataset is
based on a fixed point (such as sea level),
a compass direction, or the distance of
each location from a phenomenon in a
specified measurement system (such as
the noise in decibels monitored at various
sites near an airport).

Vector data
 Vector data is not made up of a grid of
pixels. Instead, vector graphics are
comprised of vertices and paths.
 The three basic symbol types for
vector data are points, lines and
polygons (areas).

 Points
Vector points are simply XY coordinates.
Generally, they are a latitude and longitude
with a spatial reference frame.
In this case, maps often use points to
display cities.

 Lines
Vector lines connect each vertex with paths.
Basically, connecting the dots in a set order
and it becomes a vector line with each dot
representing a vertex.
 For example, maps show rivers, roads and
pipelines as vector lines

 Polygons
When user join a set of vertices in a particular order
and close it, this is now a vector polygon feature.
In order to create a polygon, the first and last
coordinate pair are the same.
For example, a building footprint has a square
footage and agricultural fields have acreage.

Raster Data
 Raster data is having two types; one is the grid
type data, another one is the image type
data. They are usually regularly-spaced and
square .
 Rasters often look pixelated because each pixel
has its own value or class.
 Now each cell in case of grid we call as a cell,
in case of image we call as pixel.
 So, each cell will represent one attribute one
value it may be in case of remote sensing data,
it may be reflection value, it may be emitted
value, it may be temperature value, or in normal
case may be rainfall value or any other value,
but only single value per cell or per pixel.

Difference between Image and
Grid
Characteristics Image Cell
Unit Pixel Cell
Value Only positive integers Both positive and
negative integers

Pixel value
 For a grayscale and color images, the
pixel value is a single number that
represents the brightness of the pixel.
 The most common pixel format is the
byte image, where this number is stored
as an 8-bit integer giving a range of
possible values from 0 to 255.
Typically zero is taken to be black, and
255 is taken to be white.
 To represent color images, separate red,
green and blue (RGB)components must
be specified for each pixel.24 Bit
integer(255,255,255)

Difference between Vector and
Raster
Characteristic Vector Structure Raster Structure
Data Structure Complex Simple
Ease of learning Difficult ; Software is complex Ease
Positional Precision Can be very precise and accurate Precision increased with increase
data storage
Attribute Precision Good for polygon, line and point
data. Not good for continuous data
Good for continuous data
Analysis capability Good for spatial query. Analysis
limited to intersections.
Not good for spatial query but good
for spatial analysis and filtering
Storage requirement Relatively small but complex Relatively large and simple but may
be complex
Cost Inexpensive Expensive
Output Map quality Very good – Looks like a map Poor
Ability to work with image data Poor – Data can be vectorized first Good

TYPES OF ATTRIBUTES
 Each geographic feature has one or more
attributes that identify what the feature is,
describe it, or represent some magnitude
associated with the feature.
 In point data, it will have spatial
information of x,y coordinates. It can have
n number of attributes. For an example,
about ground water well, who owns the
well, what is the depth of well, what are
the different levels during monsoon,
premonsoon, postmonsoon and water
quality.

 There are two components to GIS data:
spatial information (coordinate and
projection information for spatial
features) and attribute data. Attribute
data is information appended in tabular
format to spatial features.
 The spatial data is the where and
attribute data can contain information
about the what, where, and
why. Attribute data provides
characteristics about spatial data.

Types of Attribute Data
 character,
 integer,
 floating,
 date, and
 BLOB.

 Character Data
The character property (or string) is for
text based values such as the name of a
street or descriptive values such as the
condition of a street.
For example, a character field may contain
the categories for a street: avenue,
boulevard, lane, or highway.

 A character field could also contain the
rank, which is a relative ordering of
features.
 For example, a ranking of the traffic load of
the street with “1” being the street with the
highest traffic.
 Character data can be sorted in ascending
(A to Z) and descending (Z to A) order.
 Since numbers are considered text in this
field, those numbers will be sorted
alphabetically which means that a number
sequence of 1, 2, 9, 11, 13, 22 would be
sorted in ascending order as 1, 11, 13, 2,
22, 9.

Numeric Data
 Integer and floating are numerical values
 Within the integer type, there is a further
division between short and long integer
values.
 Floating point attribute values
store numeric values with fractional
values. Therefore, floating point values
are for numeric values with decimal
points

 Numeric values will be sorted in
sequentially either in ascending (1 to 10)
or descending (10 to 1) order.
 Numerical value fields can have
operations performed such as
calculating the sum or average
value. Numerical field values can be a
count (e.g. the total number of students
at a school) or be a ratio (e.g. the
percentage of students that are girls at a
school).

 Date/Time Data
Date fields contains date and time values.
 BLOB Data
BLOB stands for binary large object and
this attribute type is used for storing
information such images, multimedia, or
bits of code in a field.

Scales / Levels of
measurements

Scales of Measurements
 Attribute measurement scales for spatial
data, including map scale (expressed as
a representative fraction), coordinate
grids, and map projections
1. Ratio
2. Interval
3. Ordinal / Rank
4. Nominal / Category
5. Cyclic
6. Counts and amounts

Ratio
 The values from the ratio measurement
system are derived relative to a fixed zero
point on a linear scale.
 Mathematical operations can be used on
these values with predictable and
meaningful results. Examples of ratio
measurements are age, distance, weight,
and volume.

 Interval
Time of day, calendar years, the Fahrenheit
temperature scale, and pH values are all
examples of interval measurements.

Ordinal / Rank
 Ordinal values determine position. These
measurements show place, such as first,
second, and third, but they do not
establish magnitude or relative proportions
 Knowing the winners only by place, user
do not know how much faster the first-
place runner was compared with the
second-place runner.

Nominal / Category
 Values associated with this measurement
system are used to identify one instance from
another. They may also establish the group,
class, member, or category with which the
object is associated.
 These values are qualities, not quantities,
with no relation to a fixed point or a linear
scale.
 Other nominal values are social security
numbers, ZIP Codes, and telephone
numbers.

Directional /Cyclic
 In GIS, it is sometimes necessary to
deal with data that can be directional or
cyclic, including flow direction on a map
or a compass direction or longitude.
 Example:
◦ In earth Rotation , Number follows 359 is 0
◦ In week ,Saturday follows Sunday

Counts and amounts:
 Counts and amounts shows total
numbers. A count is the actual number
of features on the map. An amount can
be any measurable quantity associated
with feature.
 Example: District wise population in
map

HISTORY OF GIS
 GIS – At first
 Was just a combination of ideas from
quantitative cartography, and the
computer systems that existed at that
time.
 was basically the work of cartographers
and geographers who tried to adapt their
knowledge and their needs to a
technology that looked promising.
 Since then, a large number of other
disciplines have contributed to the field of
GIS.

Geographic Information System unit 1

Geographic Information System unit 1

More Related Content

What's hot

Similar to Geographic Information System unit 1

More from sridevi5983

Recently uploaded

Geographic Information System unit 1