An Examination of Lunar Maria Ages Based on Cratering ... › exploration › education ›...

An Examination of Lunar Maria Ages Based on Cratering Densities

Image Source: Lunar Orbiter Photographic Atlas

Chenango Forks High School Research TeamSharon Hartzell, Jackson Haskell, Ben Daniels, Sarah Maximowicz, Sarah Andrus

Background

• Approximately 16% of the lunar surface is covered by cooled basaltic lava flows, known as maria.

• Localized areas of the lunar crust have undergone resurfacing throughout history.

• The dating of these maria provides insight into the geologic history of the lunar environment.


Problem

• Many samples returned from the Apollo and Luna missions have been absolutely dated using radiogenic techniques.

• Not all samples returned from the moon have been radiogenically dated.

• Most lunar maria are still unvisited.

Image Source: Consolidated Lunar Atlas

Problem

• Furthermore, returned samples represent only a small portion of the visited maria.

• These facts make it difficult for a comprehensive history of these maria to be developed.

• The lack of complete data from visited maria in combination with the absence of data from unvisited maria has compelled lunar researchers to rely on remote techniques for relative dating.


ProblemThe remote dating of lunar maria has been conducted by

lunar researchers in the following ways:

• Comparing total crater frequencies, using the assumption that more heavily cratered maria are older (Example: Boyce and Johnson, 1977)

• Comparing the distribution of crater diameter within maria, assuming that most larger craters are older (Examples: Hiesinger et al, 2010; Hiesinger et al, 2000)

• Comparing the relative weathering of craters within maria, using craters as kind of ‘fossil indicators’ (Example: Boyce, Dial & Soderblom, 1974)

Problem

Research into lunar maria ages may be divided into two major methods:

Method 1: Studies applying dating techniques to a small portion of a given mare and extrapolating their results to the surrounding area (Example: Hiesinger et al, 2000)

Method 2: Studies focusing on “continuous mapping,” (Boyce and Johnson, 1977). That is, they examine the entirety of a mare, obtaining a comprehensive understanding of that area, including differently aged basalt flows within maria. (Examples: Boyce and Johnson, 1977, 1978)

Problem

Both methods have limitations.

• Method 1 enables researchers to investigate a greater number of maria. However, data for small areas is usually extrapolated to the surrounding mare material, which may or may not share the same age characteristics.

• Method 2 is a more complete and comprehensive investigation of mare age. However, given the complexity of examining individual flows within maria, it is usually limited to one or a few maria. (Example: Boyce and Johnson, 1977)

Approach

• The overriding goal of our research was to develop and utilize a system for analyzing ages of all lunar maria.

• Since neither Method 1 nor Method 2 fulfilled the goals of our research, we synthesized our own approach.


Approach

• We analyzed all areas of all maria in three distinct investigations.

– Investigation 1: Total crater count to determine cratering density, and comparison of densities to absolute age

– Investigation 2: Analysis of crater weathering in relation to age

– Investigation 3: Analysis of crater size in relation to age

Investigation 1Image Sources

• To conduct crater counts for each mare, we first investigated sources of images.

• We used the Lunar and Planetary Institute’s online archive of the Consolidated Lunar Atlas to obtain images of much of the lunar nearside.– These images were of a relatively consistent scale and resolution. We rejected those images that were distorted due to the curvature of the moon.

– This allowed us to have a consistent margin of error in discerning craters from the surrounding material.


Investigation 1Image Sources

• For far‐side and borderline maria, the Consolidated Lunar Atlas was insufficient.

• We used images from the Lunar Orbiter Photographic Atlas.

• These images were a potential source of error in gross crater counting. – While crater measurements could be

converted to the scale of the Consolidated Lunar Atlas, differences in scale and resolution may have impacted gross crater counting.


Investigation 1Crater Counting Method

• Our crater counting method involved counting every visible crater within the boundaries of a given mare.

• We were able to discern each mare from the surrounding highlands by the smoother texture and lower albedo of mare basalt.

• We obtained a gross crater count for each of the twenty‐three lunar maria.


Investigation 1Calculations

• We divided the total number of craters from each mare by the area of that mare.– Most mare areas were obtained from J.L. Whitford‐Stark, 1982.

For maria without explicitly stated areas, we used a grid to estimate.

• This technique yielded the crater density for each mare.

• By graphing the densities in ascending order, we were able to establish a relative mare chronology, from youngest to oldest.

• By comparing our relative data to absolute dates, we were able to create a chronology in the context of geologic time.

Investigation 1Analysis

• To gain more insight into the relationship between our chronology and the lunar timeline, we related our rates to known radiogenic data for the following maria:

Oceanus Procellarum Mare Imbrium Mare CrisiumMare Serenitatis Mare Tranquillitatis Mare Fecunditatis

Mare Nectaris

• We gathered known radiogenic data collected during the Apollo and Luna missions from NASA’s Lunar Sample Compendium.

• We graphed our crater rates against all known dates for these seven maria, and obtained the following graph:

Mare Nectaris

Oceanus ProcellarumMare Crisium


• The trend line for this graph was intriguing. However, the graph had several limitations.– The samples represented were taken from a very small portion of each

mare, which may or may not be representative of all areas. – The listing of all data points distorted our graph because the small areas

were overrepresented.

• To eliminate the distortion, we averaged the data and constructed a graph with one representative point for each mare.

– Since Mare Fecunditatis was a notable outlier, and was not sampled very extensively by the unmanned Russian Luna mission, we present the graph both with and without Mare Fecunditatis.

Mare Nectaris

Mare Fecunditatis

Mare Serenitatis

Mare Tranquillitatis

Mare Crisium

Mare Imbrium

Oceanus Procellarum

Mare Nectaris

Mare Serenitatis

Mare TranquillitatisMare Crisium

Mare Imbrium

Oceanus Procellarum

Investigation 1Calculations

• This graph was the basis of our relative age determination

• The equation from the graph was rearranged so that:y = 4x10‐11 e4.738x became

x=ln(y/4x10‐11)/4.738

where the y value is the density of non‐radiogenically dated mare.

• Using density as y, we found age as x. We exchanged x and y values, and graphed the relative age of each mare in ascending order.

Analysis

• Show MAP of maria, ranked

Oldest YoungestSource of Image: Google Moon

Investigation 1Results

• In establishing a chronology and mapping the maria, we discovered that younger maria were more dominant on the near side, while the far side had mostly older maria.

• The calculation of tentative mare ages was also helpful in comparing our results to those gained through different methods.

• For most maria, the calculated position in the lunar chronology was reflected in results of other crater‐counting investigations, with a few exceptions.

• Our results from these maria may reflect the flaws in our investigation, or they may indicate that certain maria are worthy of further investigation:

Investigation 1Conclusion

• Our first investigation culminated in a relative chronology of the lunar maria.

• Though establishing correct dates was beyond the scope of this investigation, our results are valuable as a possible mare chronology.

• This method had a major limitation: Maria are like old cars which have had many parts replaced. Since they are composites of various ages, it is difficult to date a mare as a whole unit.

• The next step for this investigation would be to use the same technique as an extensive study of individual flows.

Investigation 2Approach

• Our second investigation examined the relationship between relative crater weathering and age.

• This investigation was largely qualitative; we looked for patterns within individual maria that might provide insight into mare history.

• We also sought to correlate crater age distributions within maria to our results from Investigation 1.


Investigation 2Methods

• This investigation was conducted at the same time as Investigation 1, and followed the same process of image analysis.

• All craters greater than .5 mm in diameter, or ~2.5 km based on the scale of the image used, were rated on a 1‐5 relative age scale

• The scale, described on the following slide, incorporated aspects of crater visibility and morphology to distinguish relative ages.


• 1 The crater features are very distinct, as are the rays. It has rough and jagged ejecta patterns .

• 2 The crater features are still very distinct and the rays are still visible. The ejecta is craggy and textured.

• 3 The crater features, while still visible, no longer have visible rays. Ejecta is only lightly textured.

•

• 4 The outer ring of uplift and ejecta is still visible but is devoid of distinguishing features .

5 The crater features are extremely faded and only barely visible. There is a smooth transition between ejecta and surrounding mare.Anything that appears to actually be beneath the mare is automatically scored as a 5.

youngest

(Source of Images: LPI Consolidated Lunar Atlas)


• After data was collected, we graphed all age data from all maria together to view the distribution of crater age throughout the entire lunar surface.


• If a constant rate of weathering is assumed, the dominance of 3, 4 and 5 craters could indicate that the cratering rate has slowed over time.


• Initially, we planned to use the total number of craters per category to make points on a line graph. We hoped to compare the slope of that graph to those of the individual maria and in that way come up with a relative chronology.

• This, however, was unsuccessful, because of complications stemming from the qualitative nature of the 1‐5 scale system.

• Further analysis of the data, though, did reveal several other interesting trends

Young and Middle‐aged Maria: Examples

• In the younger and middle‐aged maria, according to our chronology, many crater age distributions peaked at 3. Ages were generally more evenly distributed.

Older Maria: Examples

• For older maria, according to our chronology, 4 and 5 craters were dominant.

Far Side and Borderline Maria: Examples

Mare Australe (borderline) and Mare Moscoviense (far side), exemplified the age distribution of older maria.

Far-side and borderline maria, which were typically older, according to our chronology, also exhibited age distributions typical of older maria.

Oldest Youngest

Investigation 2Conclusions

• At first, the presence of 4 and 5 craters on maria we had deemed younger seemed anomalous. However, this can be accounted for by considering– A) Human error in mistaking crater age– B) The presence of older, non‐resurfaced basalts– C) The presence of pre‐mare craters, flooded with basalt but still

visible

• The even distribution of crater age on younger and middle‐aged basalts could indicate that they have been resurfaced more times, resulting in an obliteration of older craters.

• Older maria had, as expected, age distributions with more 4 and 5 craters. These distributions were shared by several far‐side and borderline maria.

Investigation 3Approach and methods

• The third investigation examined the possible correlation of crater size to mare age.

• The data for this investigation were recorded at the same time as Investigations 1 and 2, using the same method of image analysis.

• Instead of simply recording a gross number of craters, we recorded crater diameters as well, measured with calipers.

• When measuring the printed images with our calipers we made sure that we measured the diameter at its widest point so that distortion from the moon’s curvature was negligible.

Investigation 3Results

• When data from all the maria was gathered, crater diameter was graphed against age category for each mare.

• The age versus size graphs showed no reliable correlation.

• There were patterns evident on graphs for individual mare, but patterns differed widely.

• As stated in the introduction, size and age have been correlated by other researchers; however, our data did not reflect this correlation.

Source of Image: Lunar Orbiter Photo Gallery

Overall Conclusions

• We began with a lofty goal that yielded mixed results.

• In Investigation 1, we were able to create a chronology of mare relative ages by relating crater densities to known radiogenic data.

• This chronology is valuable as a qualitative tool.

• It also helped to relate our dates to those of other researchers, which pointed to several mare warranting further investigation.

• Investigation 2 provided an insight into the impact history of different maria.

• In conjunction with Investigation 1, it revealed several patterns of crater weathering related to age.

• It also helped support the Investigation 1 conclusion that far‐side and borderline are older.

Future Directions

• In future studies, the total mapping of individual flows within maria may provide a more complex and comprehensive history of the lunar environment.

• By refining our relative‐age ranking system to include a wider range of categories, we may discover more subtle age distribution patterns.

The investigation of mare ages is a multifaceted challenge which, as we have discovered, can be approached in many different ways. As these methods are refined, our picture of the lunar surface can only grow clearer.

Source of Image: Lunar Orbiter Photo Gallery

Acknowledgements

We would like to acknowledge the following people for helping us take part in this research experience:

Dr. Justin Filiberto

Andrew Shaner

Dr. Stephanie Shipp

Dr. Angela Pagano, SUNY Cortland

Bill Sica, Chenango Forks Computer Services

Works CitedBoyce, J. M. & Jonnson, D. A. (1978). Ages of flow units in the far eastern maria and implications for basin‐filling

history. Lunar and Planetary Science Conference, 9th, Houston, Tex., March 13‐17, 1978, Proceedings. Volume 3. (A79‐39253 16‐91) New York, Pergamon Press, Inc., 1978, p. 3275‐3283.Web. Retrieved from http://articles.adsabs.harvard.edu//full/1978LPSC....9.3275B/0003275.000.html.

Boyce, J. M. & Johnson, D. A. (1977). Ages of flow units in Mare Crisium based on crater density. Lunar Science Conference, 8th, Houston, Tex., March 14‐18, 1977, Proceedings. Volume 3. (A78‐41551 18‐91) New York, Pergamon Press, Inc., 1977, p. 3495‐3502.Web. Retrieved from http://adsabs.harvard.edu/full/1977LPSC....8.3495B.

Boyce, J. M., Dial, A. L., & Soderblom, L. A. (1974). Ages of the lunar nearside light plains and maria. Lunar Science Conference, 5th, Houston, Tex., March 18‐22, 1974, Proceedings. Volume 1. (A75‐39540 19‐91) New York, Pergamon Press, Inc., 1974, p. 11‐23. Web. Retrieved from http://articles.adsabs.harvard.edu//full/1974LPSC....5...11B/0000013.000.html.

Google Moon. (2005). [Satellite imagery of the moon, provided by the Clementine Missions]. Retrieved from http://www.google.com/moon/

Hiesinger, H., J. W. Head III, U. Wolf, R. Jaumann, and G. Neukum (2010), Ages and stratigraphy of lunar mare basalts inMare Frigoris and other nearside maria based on crater size‐frequency distribution measurements, J. Geophys. Res., 115, E03003, doi:10.1029/2009JE003380.

Hiesinger, H., R. Jaumann, G. Neukum, and J. W. Head III (2000). Ages of mare basalts on the lunar nearside. J. Geophys. Rev., 105, 29,239 – 29,275. Web. Retrieved from http://www.planetary.brown.edu/pdfs/2061.pdf.

Works CitedLunar and Planetary Institute (2010). Lunar Orbiter Photo Gallery. Retrieved from

http://www.lpi.usra.edu/resources/lunarorbiter/

Lunar and Planetary Institute/Universities Space Research Association (2004). [Digital archive based on the Lunar Orbiter images contained in Bowker D.E. and Hughes J.K. (1971) Lunar Orbiter Photographic Atlas of the Moon, NASA SP‐206, NASA Scientific and Technical Information Office, Washington, DC.] Gillis, J.J. (Ed.) Digital Lunar Orbiter Photographic Atlas of the Moon). Retrieved from http://www.lpi.usra.edu/resources/lunar_orbiter/.

Lunar and Planetary Institute/Universities Space Research Association. (2003). [Digital archive based on the images contained in Gerard P. Kuiper, Ewen A. Whitaker, Robert G. Strom, John W. Fountain and Stephen M. Larson (1967) Consolidated Lunar Atlas, Lunar and Planetary Laboratory, University of Arizona.] Douglass, E. (Ed.) Consolidated Lunar Atlas. Retrieved from http://www.lpi.usra.edu/resources/cla/

National Aeronautics and Space Administration. Lunar Sample Compendium. Compiled by Charles Meyer for Astromaterials Research & Exploration Science (ARES). Retrieved from http://www.huduser.org/Datasets/IL/IL08/in_fy2008.pdf

Whitford‐Stark, J. L. (1982), A preliminary analysis of lunar extra‐mare basalts: Distribution, compositions, ages, volumes, and eruption styles, Moon Planets, 26, 323–338. Web. Retrieved from http://articles.adsabs.harvard.edu/full/1982M%26P....26..323W.

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