geographical information system (gis)

CONTENTS

• Introduction

• History

• Components

• Data structure

• Procedure

• Application of GIS

• Remote sensing

• GPS

• SWOT analysis of GIS

GEOGRAPHICAL INFORMATION SYSTEM

• Computer database management and mapping programme that

organizes, stores and displays large amount of multipurpose

information

• Geographic – location – geocoding

• Information – data in GIS – yield useful knowledge

• System – several interrelated and linked components

• Database system

• Analysis system

• HISTORY

• Hippocrates – location can influence the health

• John Snow 1854 –cholera outbreak -spot map

GEOGRAPHIC INFORMATION

• Information refers to the location of earth’s surface

• What, where, why?

• What is attribute? Where is location? Why is analytical?

Components

• Hardware – central servers to desktop

• Software – for mapping, DBMS, analysis

• Data – spatial and non-spatial

• People

• Methods and procedures

SOFTWARES AVAILABLE

GIS Image Processing

ARC INFO

ArcView

MapInfo

MGE

Geomedia

Geoconcept

WINGIS

Microstation

AutoCAD

ERDAS

ER Mapper

ILWIS

ENVI

PCI

ArcView image analysis

TNTMIPS

Ecognition

Data structure

DATA

GRAPHIC(SPATIAL)

VECTOR

CO-ORDINATE SYSTEM

RASTER

IMAGE

ARERAL POTOREMOTE SENSED

SCANNED IMAGES

ALPHA-NUMERIC (NON-SPATIAL)

GRAPHIC – SPATIAL DATA

• Maps and map elements

• Maps – graphic representation of area perception

• Provide 2 types of information

• Locational

• Spatial relationship

Maps

• Features and surfaces

• Features

• Point features – single geographic coordinate

• Line features – series of coordinates join to form line

• Area features – series of coordinates join to form boundaries

• Surfaces

• Topography , temperature , air pressure

Point Features

• Spatially distributed entities, activities or events

• Points have a single geographic coordinate such as:

• Tree

• Lamp post

Line Features

• Lines (Arcs) are a series of geographic coordinates

joined to form a line such as:

• Road

• Stream

• Railway

Area Features

• Areas (Polygons) are a series of geographic

coordinates joined together to form a boundary

such as:

• Lake

• Soil types

DATA

ATTRIBUTE DATA

SPATIAL DATA1.

2.

SPATIAL DATA

Raster

Vector

Data Model And Structure

RASTER MODEL VECTOR MODEL

• Attributes can be numeric or alfanumeric data that is assigned to a point, line or area spatial features

• Example

• Name/number of the building, Road name etc

Attribute Data

Procedure 1. spatial data acquisition with computers

2. spatial data processing – image to vectorized data

3. query and analysis

Spatial analysis

Proximity

Overlay

Network analysis

4. data display

5. data output

6. decision and policy making

Querying GIS data

• Attribute query• Select features using attribute data

• Results can be mapped or presented in conventional database form

• Can be used to produce maps of subsets of the data

• Spatial query• Clicking on features on the map to find out their attribute values

• Used in combination these are a powerful way of exploring spatial patterns in your data

Attribute query: Lung disease in the 1860sSpatial data: Registration

Districts, 1/1/1870

Attribute data: Mortality

rate per 1,000 from lung

disease among men aged

45-64

Source: Registrar

General’s Decennial

Supplement, 1871

Query: Select areas

where mortality rate >

58.0

Spatial query: Lung disease in the 1860s

District: Alston with

Garrigill

County: Cumberland

M_rate: 68.4

Mapping through attribute query

ANALYSIS – OVERLAY METHODJoins two layers to create a new layer

The output layer will contain both the spatial

AND attribute data from both of the input layers

BUFFER/PROXIMITY ANALYSIS

NETWORK ANALYSIS

APPLICATION OF GIS

• Construction disease maps

• Analyzing trends over space and time

• Mapping populations at risk

Spatial Analysis

• Mapping spatial patterns of risk

• Assessing disease clustering

• Obtain new insight into possible methods of exposure

Public Health Practice• Find out geographical distribution and variation of diseases

• Analyze spatial and temporal trends

• Identify gaps in immunization

• Map populations at risk and stratify risk factors

• Document health care needs of a community and assess resource allocations

• Forecast epidemics

• Plan and target interventions

• Monitor diseases and interventions over time

• Manage patient care environments, materials, supplies and human resources

• Monitor the utilisation of health centres

• Route health workers, equipments and supplies to service locations

• Publish health information using maps on the Internet

• Locate the nearest health facility.

REMOTE SENSING

• Real information of geography at real times through Satellites.

• Started in 1970’s with the prime objective of obtaining Information about Natural Resources.

• LANDSAT – 1….6 was the first Satellite series launched in the World by Europian Countries.

• Indian Space Programme (Dept. of Space) was set up in 1972.

• Pixel to Ground Resolution

• Multi-Spectral Image

• Multi-Temporal Image

• Pseudo Colour Image

• True & False Colour Composite

IMPORTANT TERMS

Spatial Resolutions

Sensor: WiFS

Resolution:180m

Sensor: LISS-III

Resolution: 24m

Sensor: LISS-IV

Resolution:5m

RED

BLUE

GREEN

FCC

Multi Spectral Data

Wheat

Mustard

Multi Temporal Images (1998-1999)

False and True Color Composites

False Colour Composite True Colour Composite

NIR Red Green Red Green Blue

MSI in health

• Retinal Health Assessment is a multispectral imaging

• (MSI) device that is useful for the early detection of optic nerve and retinal disease

GPS

• space-based satellite navigation

system

• provides location and time

information in all weather

conditions, anywhere on or near

the Earth

• where there is an unobstructed line

of sight to four or more GPS

satellites

SWOT ANALYSIS

• STRENGTH

• Fast and efficient

• Better insight in spatial patterns and of spatial needs

• GIS allows for multilevel modeling

• Useful in exploratory research

• Possibility to do predictions

• Visualization of time series

• Saves time

WEAKNESS

• The complexity of the software

• Costs of the software

• limitations associated with data sources and data validity

• The clarity of certain maps can be misleading

• overlook important humanitarian aspects

OPPORTUNITIES

• Spread information derived from the data to a broad public

• Costs of data are likely to go down

• The costs and the availability of software will go down

THREAT• Epidemiologists are often not educated and not aware

• Data, facilities and skilled staff are needed

• Confidentiality cannot be guaranteed

THANK YOU