Lecture 4 - GIS Subsystems

SGG 2443

PRINCIPLES OF GEOGRAPHIC INFORMATION SCIENCE

LECTURE 4 – SUBSYSTEMS IN GIS

Assoc Prof Mohamad Nor [email protected]

Lecture Outline:

• Introduction• Subsystem For Data Input • Subsystem For Data Storage &

Management• Subsystem For Data

Manipulation & Analysis• Subsystem For Data Output

LECTURE 4: GIS SUBSYSTEMS

SGG 2443 - Principles of Geographic Information Science

ArcView

Data InputData Storage

&Management

Data Display (Output)

Data Manipulation

& Analysis

GIS - 4 SUBSYSTEMS



Subsystem For Data Input• raw data is converted into digital• data: spatial & non-spatial (attribute)• requires correction; verification; updating• spatial data entry is more critical

– quality; cost; time; availability



Manual Digitizing

• records map coordinates in digital format

• data recorder (device) – digitizer• now: head-up (on-screen) digitizing• object: point; line; polygon• mode: point; stream

Field Surveying

• field data recorder: e.g. Total Station • observation: distance; bearing;

vertical angle• data: coordinates; elevation• digital file: import into GIS

Subsystem For Data Input (cont’d.)LECTURE 4: GIS SUBSYSTEMS


Photogrammetry

• uses aerial photographs• maps produced from stereomodel

(2 overlapping photos)• requires geometric correction

(rectification)• mosaic (stitched photos) = orthophoto• now: digital photogrammetry

Remote Sensing• data from satellite images • every single object reflects different

frequencies• image classified digitally• correction: radiometric & geometric• format: raster; vector conversion• image interpretation: done digitally



Subsystem For Data Input (cont’d.)



Subsystem For Data Input (cont’d.)Photogrammetric Mapping

Subsystem For Data Input – Remote Sensing

Remote Sensing Satellite

Solar PanelSensor

Ground surface being scanned

Remote Sensing Image

Image :a) Panchromaticb) Color:

• True color• False color



Earth observation satellites usually follow the sun synchronous orbits. A sun synchronous orbit is a near polar orbit whose altitude is such that the satellite will always pass over a location at a given latitude at the same local solar time. In this way, the same solar illumination condition (except for seasonal variation) can be achieved for the images of a given location taken by the satellite.




Landsat 4,5 (USA)• Sun-synchronous• optical/ infra red• 705 Km altitude• 16 days repeat cycle• resolution

– Multi Spectral Scanner (MSS) 80m– Thematic Mapper (TM) 30m– Thermal Infra Red 120m

• ground swath 185Km

SPOT (France)• Sun-synchronous• optical/ infra red• 832 Km altitude• 26 days repeat cycle• resolution

– Panchromatic 10m– Multispectral 20m


IRS (India)• Sun-synchronous• optical/ infra red• 817 Km altitude• 24 days repeat cycle• resolution

– Panchromatic 10m– Multispectral 23m





ERS (Europe)• Sun-synchronous• microwave• 782 Km altitude• 35 days repeat cycle• resolution 30m• ground swath 100Km

JERS-1 (Japan)• Sun-synchronous• microwave• 568 Km altitude• 44 days repeat cycle• resolution 18m• ground swath 75Km

RADARSAT (Canada)• Sun-synchronous• microwave• 798 Km altitude• 24 days repeat cycle• resolution: mode dependent• ground swath: mode dependent




A sample of IKONOS’s image – 1metre data merged with 4-metre multi-spectral data

IKONOS SatelliteOrbit: Sun-synchronousAltitude: 423 miles (680 Km)Speed: 17,500 mph (28,500Km/h)Resolution: Multispectral 4m; Panc 1mWeight: 720 Kg




World Trade Centre, New York – 12 Sept 2001 The Pentagon – 12 Sept 2001

Satellite images produced by IKONOS satellite




Satellite image used to support GIS analysisExample: Flood Mitigation Study




Satellite Image captured from Google Earth Quickbird Image of Johor Bahru

QuickBird – The latest Remote Sensing satellite

Launching date: 1999Orbit: medium-inclinationAltitude: 600 KmRepeat cycle: 1 to 4 days (depending on latitude)Resolution: 1m (can reach 0.6 meter)Weight: 1800 pounds (10 feet)Data collection: simultaneous collection of

panchromatic & multispectralOn-board data storage: 137 Gb (min of 64 images)




QuickBird – The latest Remote Sensing satellite

A panchromatic image sample –Bangkok (0.61 meter resolution)

A multispectral image sample –Washington DC (0.61 meter resolution)




Malaysian Center For Remote Sensing (MACRES)Now: Malaysian Remote Sensing Agency




Malaysian Ground Receiving Station (Temerloh, Pahang)




Global Positioning System (GPS)

• ground coordinates determined from satellite signals

• satellite: NAVSTAR & GLONASS• accuracy depends on measuring

techniques (1 centimeter - 100 meters)• requires coordinate transformation

Satellite 1

Satellite 2Satellite 3

Receiver

Data Logger- store coordinates- download to computer/ GIS- reformat- coordinate transformation



Subsystem For Data Input – GPS

http://www.e-trimblegps.com




GPS receivers convert SV (Space Vehicle) signals into position, velocity, and time estimates.

Four satellites are required to compute the four dimensions of X, Y, Z (position) and Time.




The SVs transmit two microwave carrier signals:• The L1 frequency (1575.42 MHz) carries the navigation

message and the SPS code signals• The L2 frequency (1227.60 MHz) is used to measure the

ionospheric delay by PPS equipped receivers.




Space Shuttle – The carrier of Navstar (GPS), Remote Sensing and other satellites

• thrust : 6.5 million pounds• fuel consumption: 11 tons per second• orbital speed: 17,466 miles per hour







Geodatabase Development - Field Data Updating With GPS (Satellite Positioning)

An Example of Original Coordinates Captured With GPS- A Conversion Into Local Coordinate System Is Required

Scanning

• using scanner - sensor (1/0)• data format: raster• accuracy: depends on scanner resolution (dpi)• problem: editing; volume• commonly coupled with screen digitizing

Existing Digital Data

• from other mapping packages (e.g. AutoCAD)• from other GIS packages• JUPEM’s digital data: CAMS/CALS• may require: format/ coordinate conversion; editing





An Example of AutoCad’s Drawing File

Raster Data Encoding• for raster GIS• cells coded (assigned codes/ attributes)• varying cell size (number of rows & columns)• problem: accuracy & volume

Attribute Data• manual data entry

– table– data values– linking the tables

• import from other systems (DBMS)– Oracle– Informix– Ingres– Dbase– MS: SQL Server; Access;Excel



Subsystem For Data Input (cont’d.)

Database Management System

(DBMS)

GEOSPATIALDATABASE

Position of Object(x,y)

Topology(relationship

between objects)

Attributes(object characteristics)

InformationRetrieval

DataInput

QueryInput

LECTURE 3: WHAT IS A GIS?


Output

Subsystem For Data Storage & Management

5m

10m

Administrative Boundaries

Road Networks

Recreational Areas

Public Institutions

Industrial Areas

Rivers

Hydrographic Chart

Shoreline Sensitivity Index

Birds Sensitivity Index

Fish Sensitivity Index

Reptile Sensitivity Index

• make use of DBMS functions• advantageous:

• organized data structure• relational data model• able to produce log file

• spatial data• copy; import/ export• edit• delete

• attribute• create table(s)• modify table structure• editing

• direct topological editing• edit -> construct topology

• interaction with user• graphical User Interface (GUI)




• spatial data manipulation: example– change of scale: transformation– generalization– change of map projection – interpolation

• attribute data manipulation: – linking two data files (tables)– sorting– Boolean query: selection & extraction– computing new data values– data summarization



Subsystem For Data Manipulation & Analysis



Subsystem For Data Manipulation & Analysis

• Information Retrieval– Browsing– Windowing– Query Window Generation– Multiple Map Sheet Query– Boolean Attribute Retrieval & Statistical Summary

• Map Generalization– Coordinate Thinning– Polygon Thinning– Dropline & Reclassification of Polygons– Edge Matching



Subsystem For Data Manipulation & AnalysisThe Main Functions

• Map Abstraction– Centroid– Contour Generation From Spot Heights– Proximal Mapping– TIN Generation (from third dimension data)

• Map Sheet Manipulation– Change of Scale– Correction of Distortion– Change of Map Projection– Coordinate Shift and Rotation




• Buffer Generation– Buffer: based on point, line or polygon– Uniform-distance or varying-distance buffer– Double-sided or single-sided buffer

• Polygon Overlay & Dissolve– Polygon (Map) Overlay: Combination of 2 or more polygons– Polygon Dissolve: Original polygons are dissolve to make one polygon

Map Aggregation– The reverse of map overlay– New map extracted from composite map

Polygon Overlay For Calculation of Area– Area of a map is computed based on other map







Creating A Buffer For River Corridor – Sg Masai

• Measurements– Measurement on point objects (e.g summation)– Measurement on linear objects (e.g distance)– Measurement on polygonal objects (e.g area; perimeter)– Measurement of surface data (e.g. volume)

• Surface Analysis– Slope/ Aspect– Viewshed & Watershed Analyses

• Network Analysis– road, water, telecommunication networks– examples: shortest or optimal path







Creating A Chainage Along A River – Sg Melayu




A 3d Surface Model Showing The Topography In The Vicinity of Sg Melayu




A 3d Surface Model With A Proposed New Road Draped On It

Subsystem For Data Output• displays

• results of a query• results of spatial analysis

• advantageous if:• able to output on various peripherals or media

• able to generate outputs in interactive & batch modes

• able to store micros• can provide various tools forcartographic design

• able to output other features than map (e.g. chart, table, etc.)

Property MarketReport

Sempadan

Daerah Banci

Lembah Klang



Subsystem For Data OutputLECTURE 4: GIS SUBSYSTEMS


An Example A Map As Output From GIS Database

Subsystem For Data OutputLECTURE 4: GIS SUBSYSTEMS


An Example A Chart As Output From GIS Database



Subsystem For Data Output

Lecture 4 - GIS Subsystems

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