45
L l =
´
(
)+
gain DN offset
Before proceeding with further processing, these gains and offsets should be
applied to your imagery, such that each pixel value represents the radiance measured by the sensor.
For UAV imagery mosaicked from many individual images, care is needed where
the camera has used different exposure parameters (i.e., ISO, aperture, shutter
speed). The pixels values correlating to the amount of radiance will differ and converting to radiance will not be possible once mosaicked. If correction is required for
UAV imagery, then the camera parameters need to be known and ideally should be
constant throughout the flight. Additionally, the camera needs to be calibrated to
relate the digital number (DN) value of the camera to radiance.
At Sensor Radiance
At sensor reflectance, also referred to as top of atmosphere (TOA) reflectance, is a
standard and easily calculated ratio of the incoming radiant energy (light) from the
sun (ESUN) and the corresponding radiance measured by the sensor. The radiance
measured at the sensor differs from the incoming signal due to the reflectance of the
Earth surface and the atmosphere (or part of the atmosphere) the signal has transmitted through. Although providing a standard measure and common range of values (0–1), the reflectance measurement includes the reflectance from the atmosphere
and the ground surface and therefore images taken at different times are not directly
comparable. At sensor reflectance is calculated as:
r
p
q
l
l
l
=
× ×
×
L d
ESUN cos s
2
where λ is the wavelength, ρ λ is the spectral (at sensor or top of atmosphere)
reflectance for wavelength λ, L λ is the spectral radiance (W m
−2
 sr
−1
 μm
−1
), d is the
Earth-Sun distance in astronomical units, ESUN λ is the mean solar exoatmospheric
irradiance in units of W m
−2
 μm
−1
and θ s is the solar zenith angle.
Surface Reflectance
Surface reflectance, also called ‘bottom of atmosphere reflectance’ is the ratio of
incoming radiance (i.e., from the sun) with the radiance that is measured by the sensor without the atmospheric effect and should be equivalent to the signal measured
if the sensor was at ground level or there was no atmosphere. To derive this
Pre-processing of Remotely Sensed Imagery
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