These characteristics can be further specified by the:
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Transcript of These characteristics can be further specified by the:
The quality of image data is primarily determined by the characteristics of sensor-platform system.
The image characteristics are usually referred to as:
1. Spatial characteristics: Refer to the area measured
2. Spectral characteristics : Refer to the spectral, the wavelength that the sensor is sensitive to
3. Radiometric characteristics : Refer to the energy levels that are measured by the sensor
4. Temporal characteristics : Refer to the time of the acquisition
These characteristics can be further specified by the:
Extremes that are observed (coverage) and
The smallest unit that can be distinguished (resolution)
Spatial Coverage: It refers to the total area covered by one image. In case of multispectral scanners this is proportional to the total field of view (FOV) of the instrument, which determines the swath width on the ground.
Spatial Resolution: It refers to the smallest unit-area measured. This indicates the minimum details of objects that can be distinguished.
Spectral Coverage: Total wavelength range observed by the sensor
Spectral resolution: Relates to the width of the spectral wavelength bands that the sensor is sensitive to.
Dynamic range: The minimum and maximum energy levels that can be measured by the sensor.
Radiometric resolution: The smallest differences in levels of energy that can be distinguished by the sensor.
Temporal Coverage: Span of time over which images are recorded and stored in image archives.
Revisit Time: minimum time between two successive image acquisition over the same location on earth. This is sometimes also referred to as Temporal resolution
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Types of ResolutionTypes of Resolution
• SpatialSpatial
• SpectralSpectral
• RadiometricRadiometric
• TemporalTemporal
Spatial ResolutionSpatial Resolution
• The dimension of a single pixelThe dimension of a single pixel
• The extent of the smallest object on the The extent of the smallest object on the ground that can be distinguished in the ground that can be distinguished in the imageryimagery
• Determined by the Instantaneous Field of Determined by the Instantaneous Field of View of satellite instruments (IFOV)View of satellite instruments (IFOV)
• Determined by altitude and film Determined by altitude and film characteristics for air photos.characteristics for air photos.
Spatial ResolutionSpatial Resolution
IFOVIFOV
1 pixel
Raster grid sizeRaster grid size
finer
Coarser
Available ResolutionAvailable Resolution
• Satellites: ~ .61 m to > 1 kmSatellites: ~ .61 m to > 1 km
• Air photos ~ <0.6 m to large.Air photos ~ <0.6 m to large.
Satellite Satellite DData ata RResolutionesolution• MODIS: 250 - 1000 mMODIS: 250 - 1000 m
• Landsat MSS: 80 mLandsat MSS: 80 m
• Landsat TM5, 7: 28.5 mLandsat TM5, 7: 28.5 m
• IRS MS: 22.5 mIRS MS: 22.5 m
• SPOT: 20 m SPOT: 20 m
• ASTER: 15mASTER: 15m
• IRS Pan: 5 mIRS Pan: 5 m
• Quickbird Pan: 0.6 m panQuickbird Pan: 0.6 m pan
Quickbird (Digital Globe, Inc.)
~ 2.4 m spatial resolution in multispectral bands.
MODIS
500 m spatial resolution
Spectral ResolutionSpectral Resolution
• How finely an instrument “divides up” the How finely an instrument “divides up” the range of wavelengths in the range of wavelengths in the electromagnetic spectrumelectromagnetic spectrum
• How many spectral “bands” an instrument How many spectral “bands” an instrument recordsrecords
Spectral Spectral RResolutionesolution
• Related to the Related to the measuredmeasured range of EMR range of EMR
• Wide range - coarse resolutionWide range - coarse resolution
• Narrow range - finer resolutionNarrow range - finer resolution
Case 1Case 1• Measure the EMR across a Measure the EMR across a widewide range range
• E.g.E.g., the visible portion of EMR, the visible portion of EMR
• Assign a single DN for sum of all visible Assign a single DN for sum of all visible light energy hitting the sensorlight energy hitting the sensor
• Analogous to black and white Analogous to black and white (panchromatic) film(panchromatic) film
blu
e
gre
en
red
0.4 0.70.60.5UV Near-infrared
Case 1Case 1
Case 2Case 2
Measure EMR across Measure EMR across narrowernarrower ranges ranges
E.g.E.g., Blue, green and red bands, Blue, green and red bands
Assign a DN for Assign a DN for eacheach of these of these wavelength ranges to create 3 bandswavelength ranges to create 3 bands
Case 2Case 2
blu
e
gre
en
red
0.4 0.70.60.5UV Near-infrared
Coarser (lower) Spectral Coarser (lower) Spectral ResolutionResolution
Finer (higher) Spectral Finer (higher) Spectral ResolutionResolution
RGB
Red Green Blue
400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 25000.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500
0.0
0.2
0.4
0.6
0.8
High Spectral Resolution
Low Spectral Resolution
Wavelength (nm)
Wavelength (nm)
Ref
lect
ance
Ref
lect
ance
Spectral ResolutionSpectral Resolution
Radiometric ResolutionRadiometric Resolution
• How finely does the satellite divide up the How finely does the satellite divide up the radiance it receives in each band?radiance it receives in each band?
• Usually expressed as number of bits used Usually expressed as number of bits used to store the maximum radianceto store the maximum radiance– 8 bits = 28 bits = 288 = 256 levels (usually 0 to 255) = 256 levels (usually 0 to 255)
64 levels (6 bit)
4 levels (2 bit)
Radiometric resolutionRadiometric resolution
• 1 bit ( 0 - 1)1 bit ( 0 - 1)
• 8 bit ( 0 - 255 )8 bit ( 0 - 255 )
• 16 bit ( 0 - 65,535 )16 bit ( 0 - 65,535 )
• 32 bit ( 0 - 4,294,967,295 ) & more32 bit ( 0 - 4,294,967,295 ) & more
0: 0: No EMR or below some minimumNo EMR or below some minimum
value (threshold)value (threshold)
255:255: Max EMR or above some thresholdMax EMR or above some threshold
for 8 bit data typefor 8 bit data type
Radiometric Radiometric rresolutionesolution
• 8 bit data 8 bit data (256 values)(256 values)
– Everything will be scaled from 0 – 255Everything will be scaled from 0 – 255– Subtle details may not be representedSubtle details may not be represented
• 16 bit data 16 bit data (65,536 values)(65,536 values)
– Wide range of choicesWide range of choices– Required storage space will be twice that of 8 Required storage space will be twice that of 8
bit bit
Radiometric Radiometric RResolutionesolution
• 1 bit1 bit 22 ( coarse )( coarse )• 8 bit8 bit 256256
• 16 bit16 bit 6553665536
• 32 bit32 bit 4 Billion4 Billion
• 64 bit64 bit ( detailed )( detailed )
Calculation of Image Size in BytesCalculation of Image Size in Bytes
• No. of rows X No. of columns X No. of bands X No. of bits per pixel
• Example:
• 4-band X 3000 rows X 3000 columns X 1 byte = 36 Mb
• Meteosat-8 generates:
3700 X 3700 X 12 bands X 1.25 bites X 96 images per day = 20 Gb/day
Temporal Temporal RResolutionesolution
• Time lag between two subsequent data Time lag between two subsequent data acquisitions for an areaacquisitions for an area– Example:Example:
• Aerial photos in 1971, ’81, ’91 and 2001Aerial photos in 1971, ’81, ’91 and 2001• The temporal resolution is 10 yearsThe temporal resolution is 10 years
Return Time Return Time (Temporal Resolution)(Temporal Resolution)
• How frequently does a satellite view the How frequently does a satellite view the same place?same place?
• Depends on:Depends on:– Orbital characteristicsOrbital characteristics– Swath widthSwath width– Ability to point the recording instrumentAbility to point the recording instrument
June 2002
Jul 2002
Aug 2002
April 2002
When would you be likely to make a good agriculture map?
Nov 11, 1998 Dec 08, 1998 Jan 01, 1999 Feb 18, 1999 Mar 14, 1999
NDVI PROFILE
Mustard
Wheat
NDVI NDVI
NDVI = f(LAI)
Yield = f(NDVI)YIELD
CROP GROWTH AND YIELD MODELING
LAI
TEMPORAL DATA FOR MONITORING CROP DYNAMICS
WHEAT
MUSTARD
IRS – LISS-I 76 meters IRS – LISS-II 36 meters IRS – LISS-III 23 meters IRS – WIFS 188 meters
IRS – PAN 5 metersIRS – OCM 360 meters TES – PAN 1 meter
IMPROVEMENTS IN SPATIAL AND SPECTRAL RESOLUTIONS OF IRS SENSORS
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