geographical information system (gis)
TRANSCRIPT
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