Remote Sensing

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Resolution

Landsat ETM+ image

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Types of Resolution

Spatial

Spectral

Radiometric

Temporal

Spatial Resolution

The dimension of a single pixel

The extent of the smallest object on the ground that can be distinguished in the imagery

Determined by the Instantaneous Field of View of satellite instruments (IFOV)

Determined by altitude and film characteristics for air photos.

Spatial Resolution

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IFOV

1 pixel

Raster grid size

finer

Coarser

4

Available Resolution

Satellites: ~ .61 m to > 1 km

Air photos ~ <0.6 m to large.

Satellite data resolution

MODIS: 250 - 1000 m

Landsat MSS: 80 m

Landsat TM5, 7: 28.5 m

IRS MS: 22.5 m

SPOT: 20 m

ASTER: 15m

IRS Pan: 5 m

Quickbird Pan: 0.6 m pan

Quickbird (Digital Globe, Inc.)

~ 2.4 m spatial resolution in multispectral bands.

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MODIS

500 m spatial resolution

Spatial Resolution Trade-offs

Data volume

Signal to Noise Ratio  Dwell Time

“Salt and Pepper”

Money

Spectral Resolution

How finely an instrument “divides up” the range of wavelengths in the electromagnetic spectrum

How many spectral “bands” an instrument records

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Spectral resolution

Related to the measured range of EMR

Wide range - coarse resolution

Narrow range - finer resolution

Case 1

Measure the EMR across a wide range

E.g., the visible portion of EMR

Assign a single DN for sum of all visible light energy hitting the sensor

Analogous to black and white (panchromatic) film

b lu e

g re e n

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0.4 0.70.60.5 UV Near-infrared

Case 1

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Case 2

Measure EMR across narrower ranges

E.g., Blue, green and red bands

Assign a DN for each of these wavelength ranges to create 3 bands

Case 2

b lu e

g re e n

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0.4 0.70.60.5 UV Near-infrared

Coarser (lower) Spectral Resolution

Finer (higher) Spectral Resolution

RGB

Red Green Blue

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0.2

0.3

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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

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High Spectral Resolution

Low Spectral Resolution

Wavelength (nm)

Wavelength (nm)

R e

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R e

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Spectral Resolution

Spectral Resolution Trade-Offs

Data Volume!

Signal to Noise Ratio

Processing complexity (time)

Money

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Radiometric Resolution

How finely does the satellite divide up the radiance it receives in each band?

Usually expressed as number of bits used to store the maximum radiance  8 bits = 28 = 256 levels (usually 0 to 255)

64 levels (6 bit)

4 levels (2 bit)

Radiometric resolution

1 bit ( 0 - 1)

8 bit ( 0 - 255 )

16 bit ( 0 - 65,535 )

32 bit ( 0 - 4,294,967,295 ) & more

0: No EMR or below some minimum

value (threshold)

255: Max EMR or above some threshhold

for 8 bit data type

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Radiometric resolution

8 bit data (256 values)  Everything will be scaled from 0 – 255

 Subtle details may not be represented

16 bit data (65,536 values)  Wide range of choices

 Required storage space will be twice that of 8 bit

Radiometric resolution

1 bit 2 ( coarse )

8 bit 256

16 bit 65536

32 bit 4 Billion

64 bit ( detailed )

Radiometric Radiation Trade Offs

Data volume

Signal to Noise Ratio

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Calculating Image Size

Computer hard drives store data in “boxes” called bytes (e.g., 1 Mb = 1 million bytes)

1 byte can hold 8 binary (base 2) digits (0s or 1s or some combination of 0s and 1s)

Each “bit” is a single binary digit

An 8-bit number is made of of 8 binary digits and fits into 1 byte.

A 9-bit number won’t fit in 1 byte and requires 2 bytes.

Converting Base 10 to Binary Base 10 Base 2 (Binary)

0 0

1 1

2 10

3 11

4 100

5 101

6 110

7 111

8 1000

255 11111111

256 100000000

257 100000001 (etc.)

Temporal resolution

Time lag between two subsequent data acquisitions for an area  Example:

Aerial photos in 1971, ’81, ’91 and 2001

The temporal resolution is 10 years

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Return Time (Temporal Resolution)

How frequently does a satellite view the same place?

Depends on:  Orbital characteristics

 Swath width

 Ability to point the recording instrument

Orbital Characteristics

• Geosynchronous

• Polar

• Sun synchronous

Geosynchronous Orbits

Satellite orbits the earth at a rate that allows it to match the earth’s rotation—so the satellite is always over the same place

Narrow range of altitudes—about 35,786 km above the equator.

Useful for communications, weather etc.

Example: GOES satellite (weather)  Geosynchronous orbiting earth satellite

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Polar/Sun Synchronous Orbits

Pass roughly over the north and south poles

Fly over the same place on earth at the same time of day (sun always in same position)

Examples: Landsat, AVHRR

Good for land remote sensing

Return time depends on Swath Width

Swath Width

Swath Width

Return Time Trade Offs

Spatial resolution

Viewing geometry effects (off nadir)

Clouds and other atmospheric problems

Lack of archival repeat coverage for pointable satellites