Meta Research Bulletin (ISSN 1086-6590, USA)
December 15, 1999
Vol. 8, No. 4, pp.49-54.
FOR RUIN-LIKE FORMATIONS ON THE MOON
Institute of Radio Astronomy, 4 Krasnoznamennaya, Kharkov, 310002,
The Moon is an indicator of possible alien visits to the Earth during past
~4 billion years. New computer algorithms are proposed and tested for the
archaeological reconnaissance of our satellite. About 20,000 Clementine
lunar orbital lunar images have been processed, and a few ruin-like
formations were found. According to a fractal analysis, some of these finds
are different from the lunar surface on which they reside, and formally
resemble terrestrial archaeological objects. At the least, the catalogued
formations should be interesting as geological anomalies.
As it is argued
[1,2] the Moon could be used as an indicator of extraterrestrial
intelligence visits to the Solar System. Therefore, it is necessary to
ascertain the indicator's condition REGARDLESS OF THE RESULT. Unfortunately,
such studies are outside of the professional activity of selenologists
(because of their orientation only to natural formations and processes)
as well as archaeologists (because archaeology adheres to a pre-Copernican
geocentric position). That is why the first archaeological reconnaissance
of the Moon is realized only as a private project, SAAM: Search for Alien
Artefacts on the Moon.
The SAAM Project
is developed since 1992. The justifications of lunar SETI, the wording
of specific principles of lunar archaeology and the search for promising
areas on the Moon were the first stage of the project (1992-95).
Already obtained results of lunar exploration (e.g. ) show that
the search for alien artefacts on the Moon is a promising SETI-strategy,
especially in the context of lunar colonization plans. The aim of
the second SAAM stage is the search for promising
targets of lunar archaeological reconnaissance. The most probable to detect
would be very ancient (age ~1-4 Gyr) analogies of proposed modern
lunar bases. Such long-term buildings should be under the lunar
surface for protection from ionizing radiation and meteorites.
Such super-ancient constructions could be eroded and detected as systems
of low ridges and depressions, covered by regolith and craters.
It is more reasonable
to use for SAAM the archaeological method (e.g. preliminary assumption
of artifact existence) than the planetological "presumption of naturality".
According to Dr. B.V.Andrianov (the Russian authority in aerial archaeology):
"The main demasking sign of objects, whose origin on the terrain is due
to human activity, is their geometric regular configuration (at rare exclusions)"
. Terrestrial buildings, as a rule, have
rectangular outlines. Hence, it is reasonable to search
on the lunar images for unusual patterns of rectangular
shape. The status of such finds can not be higher than that artifact
candidates. The true nature of the finds cannot be ascertained by the remote
sensing only. According to archaeological practice, direct exploration
(e.g. excavations) is an obligatory element of the search. Hence,
the finds of the SAAM Project cannot be discoveries; but SAAM is a precursor
for inevitable archaeological reconnaissance of the Moon.
The lunar Clementine
EDR Image Archive on CDs  was used for SAAM. The following tests
were proposed and used for the analysis of high-resolution camera (HIRES)
data of the Clementine spacecraft.
2.1 PRELIMINARY FRACTAL TEST
As a rule, natural
landscapes consist of self-similar details on various dimension scales.
For example, lunar craters are similar at diameter of 0.1m to 104 m. By
contrast, artificial constructions have some typical dimensions caused
by size of their constructors. Hence, the artifacts might be recognized
as details of unusually frequent size. The search for such dimension anomalies
is an essence of the fractal method proposed by M.J.Carlotto and M.C.Stein
. Unfortunately that test is too slow for the express analysis of ~80,000
HIRES images because of so many calculations. That is why the simpler and
faster algorithm is proposed here.
For this purpose,
the probability distribution (M) of distances ( r ) between minima of
brightness along the lines of an image is constructed. In fact, M(r) is
the distribution of the image detail's size. At long scales, this function
could be approximated by the fractal power law: M(r) ~ rn. As constructions
have some typical size, the artifacts should increase the squared residuals
of linear regression: log M(r)= n log r + C; where C is a constant. According
to empirical results, M(r) of the HIRES images could be approximated by
the power law at rò5 pixels. That is why the regression is
calculated in the interval of 5 ó ri ó 30 pixels (50m ó
ri ó 900m) or up to 26 points.
In each of twelve
test squares of 96x96 pixels of the image, the computer calculates the
best n and C by least squares technique and the average of the squared
nmax sk2 = (gk /nmax) S [ log M(ri) - n log ri - C]2, i=1
where: k is the number of test square; gk is the apparatus factor or
average (s*/sk)2 from a lot of HIRES images (s* is sk in the center of
image at gk=1); nmax is the number of used scales up to M(ri)=0. Then the
average dispersion <s> is estimated from these regional squared residuals.
of 733 HIRES images (0.75mm-filter; the polar zones up to 75o-latitudes;
112-115 orbits) shows that s distribution is the classical
Gaussian function. According to the Student's criterion for 12 estimations,
if the inequality (sk -<s>) > 1.796 ( S(sk -<s>)2/11)1/2 is true
in any test square, this area could be considered as anomalous with a probability
2.2 RECTANGULAR TEST
test reveals the rectangular patterns of lineaments on the image of
lunar surface. For each pixel of the image, the probe point at the
distance of 6 pixels and position angle j is selected. Let N be the total
number of such pairs, and n is the number of pixel pairs, where bright
accounts are equal. The function W(j)=n/N characterizes the anisotropy
of the image. For the correction of the camera aberration, W(j) was divided
by its average quantity, which is calculated for many images at same j.
The computer finds maxima of the smoothed W(j) and the corresponding
jm angles. Obviously jm describes the orientations of lineament
groups. If there is (90oñ10o)-differences between jm , the image
is classified as interesting.
2.3 SAAM IMAGE
For the false alarm
selection, the SAAM-transformation of the image was used for revealing
indiscernible details of the lunar surface. This algorithm is very simple:
The image is smoothed by the sliding window in a kind of circle with radius
R, then the result of this procedure is subtracted from the initial image.
Thus the pixels, which are brighter than the smoothed level, are considered
as "white", and others are considered "black". This clipping permits us
to see details of extremely low contrast as well as the high contrast features.
Moreover, the large details (>R) of the image appear damped, and they do
not interfere with small-sized objects.
2.4 GEOLOGICAL TEST
J. Fiebag  supposed
that the parallelism of the formation with lineaments of its surroundings
is the criterion for naturality of the object. Although the human activity
correlates with geological lineaments (e.g. rivers), the conservative Fiebag
test was applied to the lunar finds.
orientation of surroundings was estimated by the described rectangular
test technique for the corresponding large-scale image from the ultraviolet-visible
(UVVIS) camera. The UVVIS image cover 196 times the HIRES images' area
with the same 0.75mm-filter. Only W(j)-peaks with statistical significance
of >0.9 were taken into account. If one of the two directions
of the rectangular formation on a HIRES-image coincides (±10o)
with any significant UVVIS direction, the object is not considered as interesting.
This test rejects about 60% of finds.
3. RESULTS OF THE SEARCH
The polar zones
of ñ75o to ñ90o latitudes are most suitable for the SAAM
because of oblique lighting. For the preliminary archaeological search
of those zones, 20 CDs were selected randomly from the Clementine
EDR Image Archive . About 20,000 files or ~25% of the polar HIRES data
were analyzed. Only 32 images were selected as interesting after geological
There are three
types of the finds:
lattices of leneaments;
quasirectangular patterns of depressions;
(c) narrow and
shallow depressions with smoothed bottom of quasi-simmetrical and quasi-rectangular
Arrowed rectangular 800x800m pattern on the hill is an example of lunar
ruin-like formations (long.=301.11 deg.; lat.=85.59 deg.; Clementine image:
An example of picturesque ruin-like formations on a hill is shown
in Fig. 1. The traditional explanations in terms of crossing of impact
fault systems seem inadequate for such compact and closed formations. The
Moon did not have conditions (a thin crust above melted mantle) for
Venus-like tessera terrains. So the origin of these anomalies is problematical.
As a rule, lunar base projects would be expected to show the rectangular
patterns of subsurface constructions [7-9]. Formally, such complexes could
be classified as (a) and (b) patterns. The (c)-type bands in Fig.
2 are a puzzle. Theirs depth from shadows (~10 m) is about the average
thickness of the regolith layer on the Moon. Theirs flat bottoms and geometry
remind one of modern projects for lunar regolith mining (e.g. ). Some
depressions of (b)-type could be interpreted in mining terms too.
The curious shallow depressions of ~8m-depth and ~100m-width
can be seen in the box after filtration of the image's fine structure,
and again in the schematic at the top left (long.=28.31 deg.; lat.=79.11;
Clementine image: LHD5502Q.290).
Of course, this visual impression should be tested by some objective
procedure. The modified fractal Carlotto-Stein method was used for
this purpose. First, the range of HIRES image brightness was increased
linearly up to 256 gradations. Then convert the image into an intensity
surface in a 3-D rectangular frame of coordinates (x and y are the pixel
coordinates; z is its brightness). The Carlotto-Stein method  can be
thought of as enclosing the image intensity surface in volume elements.
These volume elements are cubes with a side of 2r; where r is the
scale in terms of pixel coordinates or its brightness. Let Vr be the average
minimal volume of such elements enclosing an image intensity surface
at some point. Then the surface area is Ar = Vr/2r. As a function of scale,
Ar characterizes the size distribution of image details. The fractal
linear relation between log Ar and log r is a good approximation for natural
landscapes. However, the self-similar fractals do not approximate artificial
objects as a rule. That is why M.J. Carlotto and M.C. Stein used the average
of the squared residuals e of the linear regression log Ar=blog r + g
as a measure of artificiality.
e depends on the number of pixels in an image. Therefore, it is difficult
to compare different images. Moreover, the shadows increase e and generate
false alarms. These problems could be resolved by the non-linear regression:
log Ar = a (log r)2 +blog r + g,
where the factor
a is independent of the image size. The shadows lead to a >0, but
artificial objects have a <0.
The diagram of fractal properties of analyzed images: the random set
of HIRES files (crosses), HIRES images of ruin-like formations (black squares),
and aerospace photographs of terrestrial archaeological objects (opened
This effect is shown in Fig. 3. There factors a and b are calculated
for the random set of HIRES images (crosses) and aerospace photographs
of terrestrial archaeological objects (white squares). The fragments of
images of the following archaeological sites were used in our analysis:
Giza tombs in Egypt (KVR-1000 satellite) and El-Lejjun Roman legionary
fortress, Jordan, (CORONA satellite) ; the Cerro Vidal trinchera ,
the Cerro Juanaquena trinchera and Pueblo She' in Galisteo Basin (New Mexico,
aerial photographs ). The parameter a values for lunar ruin-like formations
(black squares) is distributed between the geological background (crosses)
and archaeological objects (opened squares). Some formations have a as
low as the known archaeological sites.
The shadow effect for the parameter a of geological background (crosses)
and ruin-like formations (black squares) on the Moon. The regression relating
a of the random image set and zenith angle of the sun (Zsol) is shown as
the dashed line. The adopted criterion for target selection (regression
- 3sa) is shown as the solid line.
The weak effect of low sunlight could be seen in Fig. 4. At any
zenith angle of the Sun (Zsol), the ruin-like formations have systematically
lower a than the random set of HIRES images does. The average linear regression
relating a of the random set and Zsol is shown as a dashed line. The standard
deviation of the crosses from this regression is sa =0.0113. A minimal
deviation of 3sa (solid line) is adopted as a formal criterion for
the final selection. The selected objects on the Moon listed in Table I
all have reasonable levels of archaeological interest.
It is shown that
computerized archaeological reconnaissance of the Moon is practicable.
The proposed methods can be used for more extensive lunar survey and for
planetary SETI in general.
are the ruin-like formations on the Moon. Of course, the ruin-like objects
could be geological formations, but they could be archaeological objects
too. This second possibility is so important, that it should not be ignored
a priori. Thus, any hill is natural for geologist, but an archaeologist
has the right to suspect the hill as a tumulus or ancient settlement. Only
direct exploration of the Moon can decide between artificial or natural
origin of these unusual lunar formations. Obviously ruin-like formations
are interesting as geological anomalies, at the very least.
The author is very
grateful to Dr. Y.G. Shkuratov for access to the Clementine's CDs. I also
thank Dr. F.G. Graham, Dr. J. Fiebag, Dr. T. Van Flandern, Dr. L.N. Litvinenko
and Dr. J. Strange for discussions and support.
1. A.V. Arkhipov
and F.G. Graham, "Lunar SETI: A Justification", in The Search for Extraterrestrial
Intelligence (SETI) in the Optical Spectrum II, ed. S.A. Kingsley &
G.A. Lemarchand, SPIE Proceedings, Vol. 2704, SPIE, Washington, 150-154,
2. A.V. Arkhipov,
"Earth-Moon System as a Collector of Alien Artefacts", J. Brit. Interplanet.
Soc., 51, 181-184 (1998).
3. B.V. Andrianov,
Ancient irrigation systems of Aral Region. Nauka Publishing House, Moscow,
1969, p. 29.
"Mission to the Moon", Deep Space Program Science Experiment, Clementine
EDR Image Archive. Vol. 1-88. Planetary Data System & Naval Research
Laboratory, Pasadena, 1995 (CDs).
5. M.J. Carlotto,
M.C. Stein, "A Method for Searching for Artificial Objects on Planetary
Surfaces", J. Brit. Interplanet. Soc., 43, 209-216, (1990).
6. J. Fiebag,
Analyse tektonischer Richtungsmuster auf dem Mars. Kein Hinweise auf knstliche
Strukturen in der sdlichen Cydonia-Region // Astronautik, Heft 1, 9-13,
7. T.L. Stroup,
"Lunar Bases of the 20th Century: What Might Have Been", J. Brit. Interplanet.
Soc., 48, 3-10 (1995).
8. S. Matsumoto,
T. Yoshida, K. Takagi, R.J. Sirko, M.B. Renton, J.W. McKee, "Lunar Base
System Design", J. Brit. Interplanet. Soc., 48, 11-14 (1995).
9. W.Z. Sadeh
and M.E. Criswell, "Inflatable Structures for a Lunar Base", J. Brit. Interplanet.
Soc., 48, 33-38 (1995).
10. J. Sved, G.L.
Kulcinski, G.H. Miley, "A Commercial Lunar Helium 3 Fusion Power Infrastructure",
J. Brit. Interplanet. Soc., 48, 55-61 (1995).
11. M.J.F. Fowler,
Examples of Satellite Images in Archaeological Application // URL: http://ourworld.compuserve.com/homepages/mjff/examples.htm
12. J. Roney, Cerro de Trinchera
Archeological Sites // The Aerial Archaeology. Newsletter. Vol. 1,
No. 1, 1998 /
Table I. Selected Ruin-Like Formations of the Moon
Longitude Latitude Type
________ _______ ____
5.3 x 5.6 LHD0132B.290
separate group of
rectangular walls and
1.2 x 1.5 LHD5502Q.290
curious pattern of linear
and broken band
depressions of ~100m-
width and ~8m-depth
0.3 x 1.3 LHD5256Q.293
rectangular zigzag band
of flat depression of
0.8 x 0.8 LHD0470B.112
rectangular claster of
2.2 x 2.2 LHD7638R.343
rectangular walls of
100m-width and the
box-like hill of
x 0.8 LHD6749R.318
on the top of a hill (Fig. 1)
(This web page produced for Alexey Arkhipov by Francis Ridge of
The Lunascan Project)