introduction to remote sensing and geographical information system

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1 Prof. Samir P Parmar Associate Professor, Dharmasinh Desai University, Nadiad, Gujarat, India Mail: [email protected]

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Page 1: Introduction to remote sensing  and geographical information system

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Prof. Samir P Parmar

Associate Professor, Dharmasinh Desai University, Nadiad, Gujarat, India

Mail: [email protected]

Page 2: Introduction to remote sensing  and geographical information system

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

Page 3: Introduction to remote sensing  and geographical information system

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 !