Sensor Resolution

Sensor Resolution

Outline for 4/14/2003
• Digital imagery - follow-on from last lecture
• Spatial Resolution
• Spectral Resolution
• Temporal
• Radiometric
• Instrument sensitivity

Digital Number
at-sensor
radiance
imaging optics
detectors
electronics
DN
DN is proportional to at-sensor radiance

Resolution and Instrument
Response Functions
• Sensor has finite precision
• Input signals vary in time and space
• Sensor has “response function” (spatial,
spectral)
input
signal
output
signal
convolution
w/response
function

Spatial Resolution
• “A measure of the smallest angular or linear
separation between two objects that can be
resolved by the sensor”. (Jensen, 2000)
• Resolving power is the ability to perceive two
adjacent objects as being distinct
– size
– distance
– shape
– color
– contrast characteristics
– sensor characteristics

• Instantaneous field of view (IFOV) is the
angular field of view of the sensor,
independent of height
• IFOV is a relative measure because it is an
angle, not a length
b

GIFOV
• Ground-projected instantaneous field of view
(GIFOV) depends on satellite height (H)
Ê
GIFOV = 2H tanÁ
IFOV
Ë 2
ˆ
˜
¯

IKONOS image of Gunnison River Basin, CO
1 kilometer
1 meter resolution 250 meter resolution

Spectral Resolution
• The width and number of spectral intervals in
the electromagnetic spectrum to which a
remote sensing instrument is sensitive
• Allows characterization based on geophysical
parameters (chemistry, mineralogy,etc.)

Spectral Resolution
• Determined by:
– the number of spectral bands
– spectral response function of each band
– full-width at half-maximum (FWHM)

AVIRIS image of Moffat Field, CA
224 channels from 0.4 - 2.5 mm
10 nm bandwidth

• Surface components with very distinct
spectral differences can be resolved using
broad wavelength ranges

Subtle differences require finer spectral resolution
vegetation spectral signatures from Jasper Ridge

Radiometric Resolution
• Number of digital levels that a sensor can use
to express variability of brightness within the
data
• Determines the information content of the
image
• The more levels, the more detail can be
expressed

Radiometric Resolution
• Determined by the number of bits of
within which the digital information is
encoded
2 2 = 4 levels
2 8 = 256 levels
2 12 = 4096 levels

2 bit radiometric resolution
8 bit radiometric resolution

Dynamic
Range
Saturation
Dark
Current
Signal
Image Brightness
Actual
Sensor
Response
Scene Brightness
Ideal
Response

Temporal Resolution
• The frequency of data acquisition over
an area
• Depend on:
– the orbital parameters of the satellite
– latitude of the target
– swath width of the sensor
– pointing ability of the sensor

• Multi-temporal imagery is important for
– infrequent observational opportunities (e.g.,
when clouds often obscure the surface)
– short-lived phenomenon (floods, oil spills,
etc.)
– rapid-response (fires, hurricanes)
– detecting changing properties of a feature to
distinguish it from otherwise similar features

Breakup of the Larsen B Ice Shelf
Courtesy of Ted Scambos, NSIDC
MODIS
imagery from
January 31, 2002-
March 6, 2002

Signal Strength
• Depends on
– Energy flux from the surface
– Altitude of the sensor
– Spectral bandwidth of the detector
– IFOV
– Dwell time

Signal-to-Noise Ratio (SNR)
Sensor responds to a both target brightness
(signal) and electronic errors from various
sensor components (noise)
SNR = signal to noise ratio
signal
noise
signal = the actual energy reaching the detector
noise = random error in the measurement (all
systematic noise has been removed)
†
To be effective, sensor must have high SNR

Noise =
n
Â
i=1
( ) 2
DN i
- m DN
n -1

Mean DN = 201
Noise = 1.345
SNR = 201/1.345 = 149
50%
200
201
199
203
202
201
200

Noise Equivalent Radiance or
Reflectance
• A measure of the lowest signal that can be
detected just before the signal falls below the
level of the noise
NEDL or NEDr = the standard deviation
of the Mean (of a set of measurements)
that produces a SNR of 1