**PRELIMINARY SEARCH
FOR RUIN-LIKE FORMATIONS ON THE MOON**
**Alexey V.Arkhipov**

rai@ira.kharkov.ua
**Institute of Radio Astronomy, 4 Krasnoznamennaya, Kharkov, 310002,
Ukraine**

**ABSTRACT**

**1. INTRODUCTION**

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. [1]) 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.

**2. METHODOLOGY**

The lunar Clementine EDR Image Archive on CDs [4] 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**

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 residuals:

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.

The analysis
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
of 0.95.

**2.2 RECTANGULAR TEST**

**2.3 SAAM IMAGE**

**2.4 GEOLOGICAL TEST**

The lineament 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**

There are three types of the finds:

(a) Quasi-rectangular lattices of leneaments;

(b) Quasi-simmetrical, quasirectangular patterns of depressions;

(c) narrow and shallow depressions with smoothed bottom of quasi-simmetrical and quasi-rectangular outlines;

**Figure 1**

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:
LHD6749R.318).

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. [10]). Some depressions of (b)-type could be interpreted in mining terms too.

**Figure 2**

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 [5] 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.

Unfortunately,
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.

**Figure 3**

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
squares).

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) [11]; the Cerro Vidal trinchera , the Cerro Juanaquena trinchera and Pueblo She' in Galisteo Basin (New Mexico, aerial photographs [12]). 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.

**Figure 4**

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.

**4. CONCLUSIONS**

Formally, there 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.

**ACKNOWLEDGEMENTS**

**REFERENCES**

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.

4. DoD/NASA, "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, 47-48 (1990).

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 /

URL: http://www.nmia.com/~jaybird/AANewsletter/RoneyOnTrincheras.html and She_in_shadow.html

Longitude Latitude Type
Dimensions
Image
Description

(deg.)
(deg.)
(km)

________ _______ ____
_________ _____________
____________________

28.04
-76.45 a
5.3 x 5.6 LHD0132B.290
separate group of

rectangular walls and

qadrangular hills

28.31
79.11 c
1.2 x 1.5 LHD5502Q.290
curious pattern of linear

and broken band

depressions of ~100m-

width and ~8m-depth

(Fig.2)

31.06
78.84 c
0.3 x 1.3 LHD5256Q.293
rectangular zigzag band

of flat depression of

~20m-depth

151.21 -76.24
b
0.8 x 0.8 LHD0470B.112
rectangular claster of

depressions

246.08 81.88
a
2.2 x 2.2 LHD7638R.343
rectangular walls of

100m-width and the

box-like hill of

300x300m

301.11 85.59
a-b 0.8
x 0.8 LHD6749R.318
complicated

rectangular structure

on the top of a hill (Fig. 1)

**(This web page produced for Alexey Arkhipov by Francis Ridge of
The Lunascan Project)**

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