Download Week 13 GIS Intro

INTRODUCTION TO GIS

Used to describe computer facilities which
are used to handle data referenced to the
spatial domain.

Has the ability to inter- relate datasets and to
carry out functions to improve their analysis
and the presentation of the results.
DEFINITON OF GIS
GIS is defined as
“ a set of tools for collecting, storing, retrieving at
will, transforming and displaying spatial data
from the real world for a particular set of
purposes.”
 A computerized system for capturing, checking,
manipulating analyzing and displaying data
related to positions on or near the earth’s
surface.

EVOLUTION (from mapping
to GIS)

Topological technique permitted the data not
only to determine where a point or a line or
an area was located but also to analyze
those features.

GIS data can be assembled by
-existing databases
-digitized or scanned from existing maps
-GPS surveying techniques
DEVELOPMENT WITH
MODERN GIS

Modern GIS developments are based on a data
theory.

There are several aspects are considered:
 GIS specific characteristic
a) location-coordinates and street address
b) attributes-features that being analyzed

GIS activities can be by two board field
a) geographic
b) cultural
ADVANTAGES of GIS
Storage and easily update data
 Sort and store spatial features
 Allow to zoom into section of data to graphic
and text which may be hidden
 Analyze both entities and data using
sophisticated computer programs
 Allow user to prepare maps

Allow user to use data to prepare maps at
different scales
 Allow to import stored data electronically and
save the cost of collecting data
 Build and augment a database
 Create new maps by modeling or reinterpreting
existing data

COMPONENTS OF A GIS

It can be divided into 4 major activities:
- Data collection and input.
- Data storage and retrieval.
- Data analysis.
- Data output and display.
GIS FUNCTIONAL
ELEMENTS
Analogue
Image Copy
Data Collection
and Input
Data Storage and
Management
Digital
Data
Manipulation and
Analysis
Data Display
Hard Copy
Data Retrieval
GIS TYPICAL COMPONENTS:

The computer with GIS software is the main
component and typically uses Microsoft or Unix
operating systems.

Data collection can be divided into geometrics
components that are:
- Field surveying,
- Remote sensing,
- Digitalization of existing maps and plans,
- Digital data transfer via Internet or CD/DVD



Computer storage:
- Hard disks,
- Optical disks etc.
Software designed are to download, edit, sort and
analyze data.
It also designed to process and present data in the
form of graphics and maps and/or plans.
SOURCES FOR GIS DATA:



The most important part of GIS is the collection of
data.
If data can be obtained from other sources, the
efficiency of the process increases.
Traditional sources for data collection:
- Field surveying.
- Remotely sensed images.
- Existing topographic maps, plans etc.
- Electronic transfer of previously digitalized data
from Government agencies or commercial firms.
DATA SOURCES
DATA
SOURCES:
Structural,
Construction,
Hydrology,
Environmental.
GIS
DATA
MANIPULATI
ON:
Highway
design, Site
planning,
Landscape
planning,
Drainage
analysis.
DATA CATEGORISATION
Node
• point
•
•
point with
vertical
information
arc junction
Arc
Polygon
Independent arc
Independent
Independent
single polygon multiple
polygon
Independent multiple
arcs
Contiguous
polygon
Point in
polygon
Connected arcs
network
overlap
noncontiguou
s
GIS DATA STRUCTURE

GIS data structure can be divided into
 Spatial data
 Attribute data
GIS DATA STRUCTURE
Attribute
Spatial
Vector
data
format positional data
is represented in
form of
coordinates
Raster
data
format –
consists of a set
or matrix of
cells or pixels
of a specific
size and area.
Digital datarecord data by
using computer
software.
Example
computer
programming
Non- Digital
date – record data
by writing manually.
Example file.
VECTOR DATA FORMAT

In vector data format, the basic unit of
spatial information are points, lines and areas.

Each units is composed as a series of one or
more coordinate points.

By using vector systems, there are 3 types of
objects possible:
 Nodes
 Arcs
 Polygons
RASTER DATA FORMAT

Consists of a set or matrix of cells or pixels of a
specific size and area.

The image represent a scanned map or an aerial
photograph of the site to be modeled.

Point is represented by a single grid cell, a line by
consecutively neighboring cells and an area by a
cluster of neighboring cells.

Can be for merging and investigating the vectorising
method for a specific purpose
 Example : raster image with a vector image for movement of
river
COMPARISON OF VECTOR AND RASTER
VECTOR DATA
Represent feature shape more accurately
RASTER DATA
Rectangular representation and more
generalized.
Represent feature with well- defined
Represent a more generalized view.
boundaries.
Compact data structure represented by
The data structure relatively simple. It uses
simple points, lines and polygons with
rows and column of grid cell having uniform
topological relationship.
size.
Resolution of data depends on compilation
The data resolution depends on the cell size.
method and scale of source data.
Easy to represent topological relationships.
Difficult to represent topological
relationships.
GEOREFERENCING:

Most geographic data users have the same earthreference techniques that the data can be shared
by using various computer systems.

Coordinate Grids:
 The plane coordinate grid systems 1983
(SPCS83) has been applied to all states.
 Software programs readily convert coordinates
based on one projection.

Transformation:
 If a GIS is tied to a specific coordinate grid and
orientation, the new data needs to be transformed to fit
the working model.

Transformations can be made in:
- Grid reference,
- Scale
- Orientation.

The computer programs designed to translate
from one grid reference to another, convert the
scale, and rotate to appropriate orientation.
DATABASE MANAGEMENT:

To organize the data so that the information about
entities and their attributes can be accessed by
rapid computerized search and retrieval
techniques.

Data collections can range in complexity.