Full text: Remote sensing for resources development and environmental management (Volume 1)

3-3- Cloud detection techniques 
One of the major problems in satellite retrievals 
of Earth-surface parameters is the correct 
identification and removal of cloud contaminated 
Currently available techniques (Saunders, 1985) are 
only partially automatic in nature and include an 
essential interactive stage, leaving the decision 
on cloud clearance to an experienced operator. 
However, to cope with the ever increasing stream of 
remotely sensed environmental data, we decided to 
embark on a fully automated cloud identification 
Algorithms for temperature retrievals require 
pixels to be flagged cloud contaminated even with 
cloud covers as low as 1$, the error in the derived 
brightness temperature having increased to the 0.2 
K level and higher already. 
During the course of our developments we found that 
the usual cloud detection techniques can be used in 
an automatic scheme if semi-transparent clouds can 
be identified by a new procedure. In this context 
we developped the "channel 4 - channel 5" - 
The brightness temperature difference between 
channels 4 and 5 can be used to detect semi 
transparent cloud-layers, especially thin cirrus. 
This type of cloud, though frequently occuring, is 
hard to identify with other cloud detection 
techniques, because the radiance of thin cirrus in 
both visible and infra-red channels is very low. 
The small difference in effective emissivity 
between channels 4 and 5 can cause brightness 
temperature difference (T^ - T b c) between the two 
channels as high as 6 K for semi-transparent cloud 
layers with an effective emissivity of 60$ (Inoue, 
Thresholds, linearly related to T b ^ for T b c are 
"empirically" determined. These have been obtained 
by analyzing a large number of AVHRR-images of 
different areas, seasons and times of the day. By 
selecting obviously cloudfree and obviously cloudy 
pixels and plotting the reswults in a 2-D histogram 
(T b c versus T b ^ - T b 5) thresholds for land and 
sea’nave been determined (see fig. 1): 
-> T b , 5 
Figure 1: 2-D histograph showing 
principle of "ch4 - ch5" - 
sea:cloudfree if T b ^ - T b 5 < 0.065 * T b 17.255 
land:cloudfree if T b ^ - T b 5 < 0.094 * T b 5 -25.11 
(brightness temperatures in’degrees kelvin) 
Land/sea discrimination is based on a linear 
combination of the channel 1 and channel 2 albedos. 
3.4. Navigation/geometric correction 
Navigation of satellite images involves assigning a 
latitude and longtitude to any point in the 
satellite image. For accurate navigation results, 
the exact position of the satellite must be known 
at any time, simple trigonometry then giving the 
latitude and longitude for every pixel (in 
The NOAA-information Service publishes every other 
day orbital elements of the operational NOAA- 
satellites. These elements can be used together 
with the recording date of a scanline to determine 
the coordinates of the sub-satellite-point in this 
line and after that the positions of the pixels on 
the scanline. In this way a navigational grid can 
be generated with which an image can be resampled 
in any desired map-projection. 
The brighness temperature in the three (or two) 
thermal-IR channels of the AVHRR are being used to 
derive true Earth-surface temperatures. The 
different characteristics of sea and land surface 
require different approaches. 
4.1. Sea surface temperature (SST) 
4.1.1. Multi channel technique 
Many uncertainties hamper the measurements of the 
Earth-surface temperature from space. Nevertheless 
for a sea-surface some of these can be eliminated. 
In the thermal IR wavelengths the emissivity of sea 
water is high and relatively constant, radiometric 
efficiency is particularly high on account of the 
nature of the Planck function at temperatures near 
300 K and verification with in-situ measurements is 
possible. In these circumstances by far the largest 
source of measurement error remains in the 
estimation of the atmospheric correction. The 
wavelengths of the AVHRR thermal infra-red channels 
have been chosen in such a way that atmospheric 
effects are different for each channel. The 
transmittance in these so called "window" is 
dependent not only on the water vapour 
concentration but also on its vertical 
The SST can be obtained from a linear combination 
of the brightness temperatures: 
SST = a ♦ .? a. T,., where N is the number of 
. .0 i=l 1 Ai 
channels used. 
The coefficients a Q , a i are determined, empirically 
or theoretically, to give the optimum performance 
in a given set of atmospheric conditions believed 
to joinly represent those in a particular area, or 
period, or for the whole globe. The correct 
determination of the coefficients is critical for 
the accurate measurements of SST from satellites. 
A good set of coefficients for the North East 
Atlantic Ocean and North Sea was determined by a 
group of the Rutherford Appleton Laboratory in the 
UK. (Llewellyn-Jones, 1984). The coefficents are 
scan-angle dependent. During daytime the "split"- 
window (channels 4 and 5) technique must be used, 
because the reflection of solar energy in channel 3 
is too high. During nighttime a "triple" window 
technique gives more accurate results provided 
channel 3 is not too noisy. 
4.1.2. Verification 
In October 1985 the Oceanographic Research 
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