UNIVERSITY OF CALIFORNIA, SAN DIEGO
3 1822 04429 7182
ATMOSPHERIC VISIBILITY
TECHNICAL NOTE NO. 203
SEPT 1986
Offsite
(Annex-Jo
rnals)
974.5
. 145
no. 203
AUTOMATED VISIBILITY & CLOUD COVER
MEASUREMENTS WITH A SOLID-STATE
IMAGING SYSTEM
R.W. Johnson
W.S. Hering
UNIVERSITY
OF
CALIFORNIA
SAN DIEGO
The material contained in this note is to be considered
proprietary in nature and is not authorized for distribution
without the prior written consent of the Visibility Laboratory
and Air Force Geophysics Laboratory
TERSI
Contract Monitor, Dr. H.A. Brown
Atmospheric Sciences Division
LIGHT
RNIA
21868
Prepared for
Air Force Geophysics Laboratory, Air Force Systems Command
United States Air Force, Hanscom AFB, Massachusetts 01731
SCRIPPS
INSTITUTION
OF
OCEANOGRAPHY
VISIBILITY LABORATORY La Jolla, California 92093

UNIVERSITY OF CALIFORNIA, SAN DIEGO
III
11
1111
IT 11
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III
3 1822 04429 7182
TECHNICAL NOTE NO. 203
AUTOMATED VISIBILITY & CLOUD COVER MEASUREMENTS
WITH A SOLID-STATE IMAGING SYSTEM
This Technical Note contains the extended summary and vu-graph representations that were submitted
for the Preprint Volume associated with the Sixth Symposium on Meteorological Observations and
Instrumentation scheduled for 12-16 January 1987, in New Orleans, LA.
The paper has been accepted for oral presentation during the afternoon session on Tues., 13 January
1987.
COPY_5_OF_10_COPIES
AUTOMATED VISIBILITY AND CLOUD COVER MEASUREMENTS
WITH A SOLID-STATE IMAGING SYSTEM
Richard W. Johnson and Wayne S. Hering
Visibility Laboratory
University of California, San Diego
Scripps Institution of Oceanography
La Jolla, CA 92093
1. INTRODUCTION
corrections applied. The sensor responses tend to be highly linear and
discrete pixel corrections once applied tend to be valid for extended
time periods.
The development and testing of a family of compact, solid-state
imaging systems for the automatic measurement of atmospheric optical
and meteorological properties is underway at the Visibility Laboratory.
In its most basic form, each of these devices consists of a computer
controlled solid-state video system that provides calibrated multi-
spectral imagery suitable for the automatic extraction of local image
transmission and cloud cover information. Imbedded within the control
computer are prototype and proprietary extraction algorithms necessary
to provide these numerical products. In addition to radiometrically
calibrated imagery, advanced algorithm development is currently
underway to provide near real-time products of the data acquisition,
processing, and display system in the form of continuously updated
digital presentations of selected operational quantities. The quantities
most desired for describing the optical state-of-the-atmosphere in which
this sensor system operates are of course task dependent, but current
algorithm development is slanted toward cloud detection, cloud-free arc
determinations, sector visibilities and total cloud cover. The multi-
spectral imagery is equally applicable in more generalized search, detect
and identify scenarios.
Whereas many useful algorithms for the determination of
atmospheric properties can be devised to require only the input of the
relative values of radiant flux fields, it is generally true that far more
redundant and reliable methodologies are available when absolute values
of radiance are available. Thus, to enable an optimum selection of
techniques for analytic applications, the camera systems described in
this note are all calibrated against standards of radiant intensity
traceable to N.B.S. using standard radiometric procedures in association
with optical calibration facilities established by the Visibility
Laboratory. In practice, each measurement system is subjected to a
systematic series of calibration procedures consisting of:
a) Radiometric linearity - radiative flux vs byte value output.
b) Absolute radiative response--absolute spectral flux input vs byte
value output.
Relative radiance shifts -- systematic changes in flux/byte
relationships as a function of f-stop and neutral density changes.
d) Geometric mapping - pixel element vs object space geometry as
diagnosed with Hemispheric Dome facility.
2. INSTRUMENTATION
4. CLOUD SPECIFICATION AND ANALYSIS
The system design is modular so that components may be added or
exchanged and the configuration modified to satisfy specific
operational requirements. The system block diagram shown in Fig. 1b
serves to illustrate features common to systems now being tested and
refined and is not necessarily intended as an as-built representation.
Both the video and digital data are routed through the system
simultaneously and independently. The parallelism is an operator
convenience, not a necessity. Most of the operational characteristics
illustrated in Fig. 1 are included in each of the currently evolving
hardware configurations.
A variety of techniques for objective cloud/clear-sky discrimination
with the solid-state imagery system are being investigated. Single
image (monochromatic) analysis with simple brightness contrast and/or
edge depiction techniques often provides excellent results. The cloud
radiances are in general larger than the background clear-sky radiances,
especially in the red portion of the visible spectrum. Although the
qualitative brightness contrast is readily apparent in most images,
obvious difficulties are involved in the development of objective
depiction criteria using single wavelength image analysis. As
summarized in the list of caveats in Fig. 2, the cloud and clear-sky
radiances vary over broad limits, requiring complex analytic
adjustments to the appropriate cloud/clear-sky threshold radiance
values. Furthermore, dense and/or shadowed cloud radiances are
comparable and sometimes become less than the corresponding
background sky radiances.
The schematic drawing of the multi-spectral imager shown in Fig.
la illustrates two important features of the camera system that
contribute to its general utility.
First, the Filter Changer Assembly is shown to contain two
independently controlled filter locations on the optical axis. In
actuality, this assembly contains two filter wheels, each holding four
separate filters in addition to the five lens optical relay. Each wheel
can position any one of its four filters into the optical path under
either manual or computer control. In one existing research
configuration, the forward wheel contains four glass absorption neutral
density filters, while the rear wheel contains four spectrally different
interference filters. Thus, both spectral band and flux level can be
controlled either manually or by pre-determined computer program.
On the other hand, experimental results clearly demonstrate the
effectiveness of color contrast, as derived from multi-spectral imagery,
for objective sky-cover analysis. Dedicated systems with the dual filter
wheel option can easily be configured to acquire, sequentially, narrow-
passband blue and red imagery with variable neutral density control.
Objective cloud depiction algorithms based upon the ratio of the all-
sky blue and red radiance fields provide good specification accuracy
over a broad range of sky and visibility conditions. The blue/red
spectral radiance ratios are characteristically near 1 for the white or
grey cloud elements in contrast with significantly larger values for the
background clear sky.
Second, the multi-lens Turret Assembly (shown pictorially, not as
built), provides an efficient method of modifying the overall optical
path to meet task specific requirements. In the prototype systems
currently in use, the two lens assemblies require manual substitution
into a fixed adapter. The remotely controlled Turret Assembly is still
under development, as are the remote control of the Iris and Occultor
sub-assemblies. However, it is important to note that the system lends
itself well to task specific changes in Turret design.
1
Illustrated in Fig. 3 is a typical set of cloud depiction imagery.
Shown for comparison, are the observed brightness field acquired with
the red passband filter, and the red/blue radiance ratio field.
Preliminary results indicate that the cloud analysis based upon the
radiance ratio imagery might be extended effectively beyond a simple
yes-no representation. For example, studies are underway to explore
the correspondence between the measured radiance ratios and the
opacity of thin, semi-transparent cloud elements.
3. SYSTEM CALIBRATION AND PERFORMANCE
These dedicated video systems offer the combined capabilities of
solid-state imaging technology and fast and efficient micro-computer
processing. Measurement accuracy is achieved through excellent
control over both spatial resolution and relative brightness accuracy.
The solid-state sensor array has exact pixel element placement. Thus,
any individual element imperfections can be recognized and specific
Remaining problem areas that are associated with the independent
use of the blue-red ratio algorithm for cloud discrimination center
primarily on paths of sight near the horizon, especially the upsun
direction near sunrise and sunset, where the blue-red spectral ratio of
the background clear-sky typically becomes less than one in hazy
atmospheres. The problem also extends to the solar aureole region at
higher solar elevation angles in dense haze conditions where little
color contrast exists between the white aureole region and the existing
clouds. The information content of the multi-spectral image pattems is
being investigated in an effort to develop helpful supplementary
techniques to extend the limits of cloud detection in these areas.
It should be emphasized that the solid-state imaging system
provides highly accurate and continuously updated measurements of the
apparent contrast of all identifiable objects in the scene. Initial
experience has verified the importance of using a wide selection of
suitable targets in the array, as suggested by the illustrative scene
shown in Fig. 4b. Whenever practicable, the actual selection of
visibility targets should be adjusted for each scene in accordance with
observed conditions. In the absence of ideal dark targets viewed
against the background horizon sky, priority should be shifted as
necessary to objects at distances close to the limit of detection, where
the most consistent and representative calculations of visual range can
be made.
5. DETERMINATION OF DAYTIME VISIBILITY
The process of daytime visibility determination either
instrumentally or by a human observer ultimately involves the
resolution of the distance from pre-selected targets that the apparent
contrast, Cr , reduces to some minimum (threshold) value needed for
detection. The threshold contrast is dependent on a number of factors
including the visual acuity of the observer as well as the angular
subtense of the target, its shape and its location with respect to
background features. The goal is to develop a completely automated
system to provide objective quantitative estimates that are consistent
regardless of time and location. The degree of modeling required to
provide, for example, the visual range along specific pre-selected
horizontal or slant paths is dependent upon the accuracy needed to
satisfy the individual user requirements.
For fixed base installations one has the important advantage of
refining the basic algorithms for visibility determination on the basis
of measurements and local experience acquired through continuous
operational use of the system. Early experience indicates that
consistent and reliable estimates of visual range can be obtained from
target/background ensembles as well as with isolated targets. The
important consideration is that the objects in a selected area ensemble
be located at approximately the same range and as close in range as
practicable to the limit of visibility.
6. SUMMARY
The stepwise derivation of the fundamental equations for contrast
transmittance as given by Duntley, et al. (1957) is shown
schematically in Fig. 4a, along with the definition of the individual
terms in the expressions. For purposes of discussion here, let us
simply state the corresponding diagnostic equation for the calculation
of visual range, V, as follows,
The primary characteristics of several compact, solid state imaging
systems for the automatic measurement of atmosphere optical and
meteorological properties have been presented and discussed. The
modular design of the systems allows for both manual and/or computer
control of both spectral band and flux level selections as required by
the measurement task. In addition, absolute radiometric calibration of
the sensor array enables a variety of reliable methodologies for the
assessment of atmosphere properties to be employed with objective
confidence.
In {s (*)/[1 . (1-3) ]}
{$() / [.- (1 -»]}
1
Experimental results have clearly demonstrated the effectiveness of
color contrast, as derived from multi-spectral imagery, for objective
sky cover analysis over a broad range of sky and visibility conditions.
The solid-state imaging system provides highly accurate and
continuously updated measurements of the apparent contrast of all
identifiable objects within its field of view. Early experience indicates
that consistant and reliable estimates of visual range can be obtained
from these target-background ensembles as well as with isolated
targets.
where ε = is the threshold contrast for detection and S = L / Lo is the
so called "sky-ground ratio" (Duntley, 1948), and Lois point source
function (equilibrium radiance) of the directional path radiance L,. The
source function, Lg, may be estimated from the clear-sky horizon
radiance for a path of sight having the same scattering angle with
respect to the sun as the target line of sight.
For the ideal case where a black target (C. =-1) is viewed against
the clear horizon sky (S=1), Eq. (1) reduces to the simple form
From our experience to date, it is clear that a small relatively
automatic system for the assessment of these key atmospheric
properties is now readily available to the experimental and modelling
communities. Figure 6 illustrates our conception of an automatic
system designed to accumulate the imagery required to address these and
related optical phenomena. The application of this prototype system
to the task of multi-purpose local area measurements should be the
harbinger of a new standard of consistent and reliable weather related
observations.
V = r In € / In C = ln € 1ā
Eq. (2) is often referred to as Kochmieder's Law and is used extensively
to calculate visual range from measurements of attenuation coefficient,
7. ACKNOWLEDGEMENTS
This research was funded by the Air Force Geophysics Laboratory
under Contract F19628-84-K-0047.
8. REFERENCES
The general solution to Eq. (1) is shown in Fig. 5 for the case
where the threshold contrast is .05 and the inherent contrast is -1.
Note in particular the changes in calculated visual range associated with
departures of sky-ground ratio from the clear horizon-sky background
value of 1. In general, S varies from about 0.2 for very bright
backgrounds to 5 or more for low surface reflectance and upsun paths of
sight. The error bars shown for the S=1 result, indicate the relative
errors in the calculated visual range due to a +20 percent uncertainty in
the estimated inherent contrast. Note that the errors in calculated
visual range due to errors in estimated inherent contrast increase
markedly with increasing apparent contrast of the designated target. In
other words, reliable calculations of visual range are especially difficult
using the apparent radiance contrast of close range targets in good
visibility conditions.
Duntley, S.Q. (1948), "The Reduction of Apparent Contrast by the
Atmosphere", J. Opt. Soc. Am. 38, 179-191.
Duntley, S.Q., A.R. Boileau, and R.W. Preisendorfer (1957), "Image
Transmission by the Troposphere 1, J. Opl Soc. Am. 47, 499-506.

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b. Image acquisition & analysis system block diagram
Fig. 1. Multi-spectral whole sky imager.

SINGLE WAVELENGTH DISCRIMINATORS: CAVEATS
1. RADIANCE THRESHOLD TECHNIQUES
a. Sky & Cloud Radiances Vary over Large Excursions
b. Threshold Radiances Require Continual Analytic Updates
c. Dark or Shadowed Clouds mimic Background Sky Radiances
2. EDGE GRADIENT TECHNIQUES
a. Cloud Imbedded in Cloud Background Yields Redundant Boundaries
b. Fails as Scene Approaches Uniform Overcast
Fig. 2.
(a.) High Contrast Image using red spectral filter
(650nm)
(b.) Composite radiance ratio image from red/blue
spectral bands (450 nm & 650 nm)
Fig. 3. Typical cloud depiction imagery.

SOLAR
SPECTRAL
IRRADIANCE
ATMOSPHERIC OPTICAL EFFECTS
DIRECT & DIFFUSE
SURFACE IRRADIANCE
SCATTERED SKYLIGHT
(PATH RADIANCE)
SOLAR
VIEW
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GEOMETRICS
BACKGROUND
REFLECTANCE
OBJECT
REFLECTANCE
Lp = LoTR + L*
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INHERENT
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INHERENT
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ATMOSPHERIC
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OBJECT
RADIANCE
APPARENT
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INHERENT
CONTRAST
APPARENT
CONTRAST
Co= (ho-blo)/OLO
CONTRAST
TRANSMITTANCE
CF = (-61)/OL
T = c/c = (bLo/bLT,
Fig. 4. Conceptual Procedure for the determination of contrast transmittance.

20.0
ADJUSTED TO THRESHOLD CONTRAST = .05
INHERENT CONTRAST = 1.0
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RATIO
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22
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↑ és Áį į į į 05 To
APPARENT CONTRAST (Log Log Scale)
Fig. 5. Visual range versus apparent contrast relationships.

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