GEOGRAPHICAL INFORMATION SYSTEM (GIS)
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Transcript of GEOGRAPHICAL INFORMATION SYSTEM (GIS)
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CONTENTS
• Introduction
• History
• Components
• Data structure
• Procedure
• Application of GIS
• Remote sensing
• GPS
• SWOT analysis of GIS
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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
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• HISTORY
• Hippocrates – location can influence the health
• John Snow 1854 –cholera outbreak -spot map
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GEOGRAPHIC INFORMATION
• Information refers to the location of earth’s surface
• What, where, why?
• What is attribute? Where is location? Why is analytical?
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Components
• Hardware – central servers to desktop
• Software – for mapping, DBMS, analysis
• Data – spatial and non-spatial
• People
• Methods and procedures
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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
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Data structure
DATA
GRAPHIC(SPATIAL)
VECTOR
CO-ORDINATE SYSTEM
RASTER
IMAGE
ARERAL POTOREMOTE SENSED
SCANNED IMAGES
ALPHA-NUMERIC (NON-SPATIAL)
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GRAPHIC – SPATIAL DATA
• Maps and map elements
• Maps – graphic representation of area perception
• Provide 2 types of information
• Locational
• Spatial relationship
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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
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Point Features
• Spatially distributed entities, activities or events
• Points have a single geographic coordinate such as:
• Tree
• Lamp post
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Line Features
• Lines (Arcs) are a series of geographic coordinates
joined to form a line such as:
• Road
• Stream
• Railway
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Area Features
• Areas (Polygons) are a series of geographic
coordinates joined together to form a boundary
such as:
• Lake
• Soil types
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DATA
ATTRIBUTE DATA
SPATIAL DATA1.
2.
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SPATIAL DATA
Raster
Vector
Data Model And Structure
RASTER MODEL VECTOR MODEL
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• 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
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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
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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
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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
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Spatial query: Lung disease in the 1860s
District: Alston with
Garrigill
County: Cumberland
M_rate: 68.4
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Mapping through attribute query
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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
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BUFFER/PROXIMITY ANALYSIS
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NETWORK ANALYSIS
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APPLICATION OF GIS
• Construction disease maps
• Analyzing trends over space and time
• Mapping populations at risk
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Spatial Analysis
• Mapping spatial patterns of risk
• Assessing disease clustering
• Obtain new insight into possible methods of exposure
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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
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• 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.
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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.
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• Pixel to Ground Resolution
• Multi-Spectral Image
• Multi-Temporal Image
• Pseudo Colour Image
• True & False Colour Composite
IMPORTANT TERMS
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Spatial Resolutions
Sensor: WiFS
Resolution:180m
Sensor: LISS-III
Resolution: 24m
Sensor: LISS-IV
Resolution:5m
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RED
BLUE
GREEN
FCC
Multi Spectral Data
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Wheat
Mustard
Multi Temporal Images (1998-1999)
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False and True Color Composites
False Colour Composite True Colour Composite
NIR Red Green Red Green Blue
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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
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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
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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
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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
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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
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THANK YOU