introduction to remote sensing and geographical information system
TRANSCRIPT
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Prof. Samir P Parmar
Associate Professor, Dharmasinh Desai University, Nadiad, Gujarat, India
Mail: [email protected]
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2 Disclaimer
This presentation is on net just for educational purposeonly. The person, places, brands mentioned here are notpromoted by author. The copyright material might be herebut it is expected that the purpose of violation is justeducational hence should be waved. Thank You
- Prof. Samir P Parmar
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REMOTE SENSING DEFINITION
Science of acquiring information about a physical phenomenon of an object or surface of the earth measured at a distance without being in physical contact with the object of interest
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REMOTE SENSING PROCESS
PRISM
Energy Source or Illumination (A)Radiation and the Atmosphere (B)Interaction with the Target (C)Recording of Energy by the Sensor (D)Transmission, Reception and Processing (E)Interpretation and Analysis (F)Application (G)
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Electro Magnetic Radiation
Wavelength Frequency
Electro Magnetic Spectrum
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Satellite electromagnetic sensors “see” reflected and emitted radiation8
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Blue sky
Day timeEarth
Atmosphere
BG
R
Earth
Sunset
Blue
Red
Sun
Sun
9 Scattering Phenomenon
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Remote Sensing Process Components
• A. Energy Source or Illumination
• B. Radiation and the Atmosphere
• C. Interaction with the Target
• D. Recording of Energy by the
• Sensor
• E. Transmission, Reception,
• and Processing
• F. Interpretation and Analysis
• G. Application
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Source Effect
Ionospheric effects ± 5 meter
Ephemeris errors ± 2.5 meter
Satellite clock errors ± 2 meter
Multipath distortion ± 1 meter
Tropospheric effects ± 0.5 meter
Numerical errors ± 1 meter or less
Sources of error 12
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Common Platforms
(1) Ground-Based
(2) Airborne
(3) Space borne
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Landsat 1,2,314
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Landsat 4,515
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Landsat 716
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IRS 1 C IRS 1 D
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Space-LISS-III18
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space- WiFS19
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Landsat Satellite
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IKONOS Satellite
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Orbits
• The path followed by a satellite is referred to as its orbit.
Geostationary Orbit
Near-Polar Orbits
Equa. W-E satellite orbiting Earth
Mainly used for communication and
meteorological applications – GOES,
METEOSAT, INSAT etc.
Satellite Orbital plane is near polar and the
altitude is such that the satellite passes
each place at same local sun-time.
Cover entire globe – LANDSAT, SPOT,
NOAA, IRS etc.
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Low-Earth orbits
~700-800 km
Sun-synchronous, near-polar, near-circular
Satellite orbit is fixed in space: Earth rotates beneath it
Orbit inclined at 98.7
Cross the equator (N-S) at ~10.30am local time
~90 minutes per orbit
Geostationary orbits
35,770 km, 0° inclination
Period of orbit = 24 hours
Global coverage requires several
geostationary satellite in orbits at
different latitudes
Good for repetitive observations, poor for
spatially detailed data
Large distortions at high latitudes
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Swath
• As a satellite revolves around the Earth, the sensor "sees" a certain
portion of the Earth's surface. The area imaged on the surface,
• Imaging swaths for space borne sensors generally vary between tens
and hundreds of kilometers wide.
Swath Swath Area
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SPECTRAL RANGE
Sensors for mapping – usual spectral range:
BLUE ~ 0.45 – 0.52µm - not in any case, problems with atmospheric scattering
GREEN ~ 0.52 – 0.60µm – used
RED ~ 0.63 – 0.69µm – used
Near Infrared (NIR) ~ 0.76 – 0.90- (1.2)µm – used
Mid infrared ~ 1.55 – 1.70 µm – often used by more new sensors, usually larger pixel size, advantage for classification
Thermal infrared – not for mapping, only for classification, lower resolution
Wide field sensors usually only red and NIR – determination of vegetation index
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SENSOR PERFORMANCE PARAMETERS
SPATIAL- THE PHYSICAL DIMENSION ON EARTH IS RECORDED :
SPATIAL RESOLUTION
SPECTRAL- RELATING OF WAVELENGTH CHARACTERISTICS OF
EMR MEASURED NUMBER OF BANDS, BANDWIDTH:
SPECTRAL RESOLUTION
RADIOMETRIC- ACCURACY AND MINIMUM CHANGE POSSIBLE IN
RADIANCE MEASUREMENT :
RADIOMETRIC RESOLUTION
TEMPORAL- FREQUENCY OF OBSERVATION :
TEMPORAL RESOLUTION
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TEMPORAL RESOLUTION
The concept of revisit period that refers to the length of time it takes for a satellite to complete one entire orbit cycle. The revisit period of a sensor is usually several days depending upon satellite to satellite
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Required resolution for mapping (pixel size)
rule of thumb: pixel size of 0.05 – 0.1 mm at publishing scale1: 10 000 0.5 – 1 m1: 25 000 1.2 – 2.5 m photographic resolution1: 50 000 2.5 – 5 m - pixel size: 2 pixel ~ 1 lp1:100 000 5 -- 10 m1:200 000 10 -- 20 m
Detectability of objects pixel sizeurban buildings 2 mfoot paths 2 mminor road network 5 mfine hydrology 5 mmajor road network 10 mbuilding blocks 10 m
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CLASSIFICATION OF REMOTE SENSORS
REMOTE SENSORS ARE INSTRUMENTS THAT MEASURE THE
PROPERTIES OF THE REFLECTED/ EMITTED EMR
Photographic camera,
Opto-mechanical
Scanner(MSS),
Push-broom Scanner
(IRS-LISS)
Scanning
microwave
radiometer (MSMR)
LIDAR Scatter meter,
SAR
Remote Sensors
Passive Active
Optical IR (OIR) Microwaves Optical IR (OIR) Microwaves
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SPECIFICATIONS OF PAYLOADS FOR IRS SATELLITE SERIES
CHARACTERISTICS LISS-I LISS-II LISS-III PAN WiFS
RESOLUTION (m) 72.5 36.25 23.5 5.8 188
SWATH (km) 148 74 141 71 810
SPECTRAL BANDS
.45 - .51
.52 - .59
.62 - .68
.77 - .86
Same as
LISS-I
.52 - .59
.62 - .68
.77 - .86
1.55 – 1.70
.50 - .75 .62 - .68
.77 - .86
STEERABILITY NIL NIL NIL ± 26 NIL
REVISIT (DAYS) 22 22 24 5 5
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Remote SensingVisual Image Interpretation
Spatial characteristics are:
shape size shadow pattern texture
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Deductive Approach
1. Photo / Image
Elements
• Shape
• Size
• Tone / Colour
• Texture
• Pattern
• Shadow
• Association
2. Terrain / Geotechnical Elements
• Landform
• Drainage Pattern, Density & Anomaly
• Vegetation & land Use
• Erosional Pattern
• Soil
Convergence of Evidence
Existing Geological Information & Ground Checks
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EXISTING GEOLOGICAL MAPS & LITERATURE
PREPARATION OF FINAL LITHOLOGICAL MAP OVERLAY
FIELD VERIFICATION
PREPARATION OF PRE-FIELD LITHOLOGICAL MAP OVERLAY
COORELATION OF IMAGE CHARACTERISTICS & ROCK TYPES
STUDY OF IMAGE & TERRAIN ELEMENTS
VISUAL INTERPRETATION
SATELLITE IMAGERYContd..
Amount of Information Extracted α Amount of Experience
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Sensors in photographic Image Interpretation
Black and white panchromatic
Black and white infrared
Colour
Colour infrared/ false colour
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VISUAL INTERPRETATION
Shape
Texture
Size
Pattern
Tone
Shadow
Location /
Association
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false colour imageColour image37
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FUSED
IMAGE
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Goa, Maharashtra, India
Forest Area
Run way
Sedimentation in river
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Sensor : IRS1C WiFS
Wet Land
Haze & Moisture present in Vegetation
Sedimentation in river
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Sunder bans , West Bengal India
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Remote Sensing - Visual Image Interpretation
Full colour Panchromatic
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Remote Sensing - Visual Image Interpretation
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Remote Sensing - Visual Image Interpretation
SHADOW
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Remote Sensing - Visual Image Interpretation
PATTERN44
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Spatial Resolution45
Less Number of pixels/ unit area = Unclear Picture
More Number of pixels/ unit area = Clear Picture
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10 m resolution 30 m resolution 80 m resolution
A "High Resolution" image refers to one with a small resolution size. Fine
details can be seen in a high resolution image. On the other hand, a "Low
Resolution" image is one with a large resolution size, i.e. only coarse
features can be observed in the image.
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Characteristics of remotely sensed data
Different remote sensing systems acquire different types of data
which are often categorised according to four different types of `resolution`
1. Spatial resolution: the ability to distinguish between adjacent objects on the ground.
30-m pixels5-m pixels
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Temporal resolution: How often are the data collected?
Temporal and spatial resolution generally inversely related
Characteristics of remotely sensed data
AVHRR - 1 km pixels - 12 hour repeat SPOT - 10m pixels - 26 day repeat
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Digital Terrain Modeling (DTM)
Digital Elevation Model
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Aerial photograph showing a strike-slip fault. 50
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Location: Near Rongtong Pass, North of Kaja, Spiti Valley
IRS LISS-III Image
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River Topography Change
1 2
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Volcanic cone and crater
Volcanic Crater53
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Oil Spills56
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57Tornado/ Storms
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Temperature sensor image
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Quick Bird 0.5 m resolution image
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Landsat-76-Aug-199915m resolution
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b/w, true color and false color (infrared) ImagesDifferent features are differentiated automatically
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Infra red image for lava flow
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Pyramids of Egypt
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Digital Elevation Model Using GIS
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Beijing
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Vatican City
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IKONOS, 0.8 m Resolution, Vancouver, Canada, October 29, 2002
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75Quick Bird 60 cm resolutionRiyadh, Saudi Arabia30 Dec-2005
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0.5 m Resolution Image
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Washington DC0.15m Resolution
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1m DEM, IKONOS Data, 0.8 m Resolution, Sahara Desert
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IKONOS YOKOHAMA
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Natural Hazards
Land slides
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Quarry site and conveyer system along with sand heaves
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85Individual Plots and Street s Digitized
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Individual Plots and Street s Digitized
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Buffer for a Road
Buffer= effective, influence zone
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DEM of a City, Digitized buildings in 3D
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DEM of a City, Digitized buildings in 3D
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DEM of a City, Digitized buildings in 3D
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DEM of a City, Digitized buildings in 3D
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DEM of a Flood in City
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DEM of a Flood in City
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DEM of a Flood in City with real time monitoring
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97 DEM model of IIRS, Dehradun, Uttarakhand India
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101 GIS Supporting equipment's
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GARMIN, GPS Instrument
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Precision in GPS
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GIS Links:GIS Cafe.com (http://www.giscafe.com/) GIS Internet Directories (Related topics) (http://www.compinfo-
center.com/tpgis-t.htm) GIS Internet Directories (Special topics)
(http://www.ncsu.edu/midlink/gis/links.htm) Guide to GIS Resources on the Internet (Berkely Digital Library)GIS Case Studies
Map Projections /Datums/ Coordinate syetms
1. http://www.colorado.edu/geography/gcraft/notes/mapproj/mapproj_f.html2. http://en.wikipedia.org/wiki/Map_projection
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GIS RESOURCES
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More Linkshttp://www.geospatialtoday.com/http://www.innovativegis.com/basis/http://www.gisdevelopment.net/http://spatialnews.geocomm.com/http://www.mycoordinates.org/http://www.gpsworld.com/gpsworld/http://www.geoplace.com/ME2/Default.asp(Almost all are freely available)
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GIS RESOURCES
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Remote Sensing Links:
Publications, References, Books, Journals & many
more links
AAG-RSSG Web Resources Sensor Systems and Data
Products
CEOSDIS - Committee on Earth Observation Satellites
Disaster Management Support Group
Remote Sensing Educational Guide
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RS RESOURCES
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ILWIS S/W (http://www.itc.nl/ilwis/downloads/default.asp)
GRASS (http://grass.itc.it/download/index.php)
ARCVIEWARC GISGEOMETICAGEOSTUDIOERDAS GRAM ++ (IIT Bombay)TNT MIPS (http://www.microimages.com/products/tntmips.htm)
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GIS SOFTWARES
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Special Thanks to Faculty members and Management who provided meexcellent expert level training in NNRMS course in 2007, IIRS, Dehradun,Uttaranchal, INDIA
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Thank You !