3DS MAX Project

I know it's a long time coming but here is my final project for the 3D Recording and Interpretation class.

The Triclinium of Julia Felix: A Virtual Reconstruction

Introduction

The potential for 3D modelling and visualisation for achieving research and didactic goals in an archaeological framework is astounding. Increasingly, the technology is becoming more accessible and commonplace for its use in archaeology (Kanter 2000; Porcelli et al. 2013).

I have fictionally been approached to produce reconstruction images of the Triclinium of the Praedia of Julia Felix for a production company undertaking an hour-long documentary series about the Praedia. This will entail producing a 3D model of the room as it might have been before Pompeii’s devastation in 79 AD in an appropriate 3D program. The end goal for the production team is to create a short animation of the room to inform the audience about the emotion and aesthetics of this room as it might have been in the past. The idea is to put the viewer within the context of the past. Computer-generated animations have become commonplace in popular media as a means of presenting ancient cultures and relevant archaeology.

Background

The world-famous city of Pompeii has provided archaeologists and historians with invaluable information on the lives and times of those living in the city. Within its walls, the Praedia of Julia Felix provided a unique look at a private house converted into a public space. It was a massive and unique complex of baths, shops, gardens and dining rooms on the Via dell’Abbondanza north of the amphitheatre on the western side of Pompeii (Figure 1).

Figure 1. Map of Pompeii with important and notable buildings and sites designated. (Source)

After a severe earthquake wracked the city in 62 AD, the complex was seriously damaged. Work was undertaken almost immediately to repair and renovate the buildings to provide public spaces and housing for those effected by the quake, to the benefit of its owner, Julia Felix, an affluent property owner who inherited her wealth from her family and astute business operations (Dobbins 2007; George 1986; Parslow 2007).

At a prominent position within the Praedia (Figure 2), a barrel-vaulted summer triclinium and nymphaeum with a water-stair fountain allowed patrons to dine and recline while gazing out onto the well-adorned garden. The water would have pooled around the marble-faced couches and created a beautiful effect within the room (George 1986).

Figure 2. Plan of the Praedia of Julia Felix. The triclinium is room F.

(Source)

Aims & Objectives

The aim of this reconstruction is to recreate the visual perception of the room illuminated with natural lighting and the emotions evoked through the personal experience of being within the room as it might have been prior to its devastation in 79 AD. More specifically, I would like to recreate the effect of the water pooling at the outer edge of the triclinium and the caustics generated by the natural light which kept the room illuminated during the summer months.

This will require a detailed geometric model, meticulous surface materials and textures, realistic spectral representations within the room and several renderings of the model with physically correct lighting. As my audience will primarily be those who may only possess a (suspected) cursory knowledge of Pompeii, Roman dining customs, triclinia or nymphea, I intend to construct my model as accurately as possible.

However, some compromises must be made and these will be described to dissuade the false assumption of ultimate veracity that often accompanies 3D reconstructions, as they tend to convey a strong suggestion of reality no matter the quality of data on which they are based (Kanter 2000). Ultimately, an animation will be story-boarded from rough sketches and render from which the production company can work.

Metadata

Appropriate metadata is essential for any project for its maintenance and dissemination. Accordingly, project-level and file-level metadata have been attached at the end of this report as Appendix B. All 3D files have been saved both as a 3D Studio Max Design File (.max) and Wavefront Object File (.obj), a standard open file format which is not software dependent.

3D Modelling in Archaeology

3D data is an increasingly important visualisation and analytical tool within the field of archaeology. Virtual archaeology sprang from “a melting pot of computer science and archaeological aspiration” (Earl 2009). Although its considerable advancement over the decades has facilitated analysis and research goals, it is not without constraints and underlying interpretive problems. These will be outlined in the following section.

There are many benefits to creating 3D models of archaeological data.  It allows archaeologists to explore a particular research question or predict the behaviour or perspective of an object or feature which has been damaged. The ability to transform archaeological data collected in the past into novel interpretive and portable formats of elaborated data (as I have done with this project) is an invaluable tool for retrospective research. Above all, perhaps, is its innate ability to facilitate interaction between the data and its human users by producing an interactive virtual tool for analysis and interpretation (Hermon 2008; Papadopoulos & Earl 2009).

However, the creation of 3D models in archaeology remains necessarily constrained by certain facts within the practice. Firstly, that archaeological datasets are seldom, if ever, complete and a certain amount of conjecture or, more favourably, imagination is inevitably introduced into every 3D model produced for archaeological purposes (Barceló 2002; 2010; Earl 2009; Kanter 2000). Even the most complete dataset will never present a sufficient reconstruction of the past (Papadopoulos & Sakellarakis 2010). (This position, of course, excludes laser scanned data of extant sites or objects which is often accurate within the sub-millimetre range.) It is for this reason that it is essential that descriptions of the primary data are included, in addition to any interpretive leap that might be made to build a model (Eiteljorg 2000; Kanter 2000).

Perhaps more theoretically, it has been argued that 3D data favour the visual aspect of any site or object, at the cost of the other senses (Eiteljorg 2000; Gillings & Wheatley 2001, Hamilakis 2013). Luckily, we do not live in a world dictated purely by what we see, but rather one that is affected by all the interactions of our senses in fluctuating combinations. 3D visualisation inherently ignores all other senses.

These constraints and others, such as the goals of a particular model and its intended audience, affect the way in which we model archaeological data in a 3D environment. The levels of realism portrayed in virtual environments must always be considered and described.

3D Studio Max as the Tool

Virtual reality is particularly dependent on the software and hardware used in its creation (Papadopoulos & Earl 2009). For the completion of my model, I have chosen to utilise Autodesk’s 3D Studio Max 2014 as the primary program for construction. By using geometric primitives, and subsequently adding materials, textures and lighting, a 3D model is thus produced. It allows considerable flexibility in model creation and excellent rendering capabilities with even the most basic package renderer.

Model Creation

The general workflow for the creation of the resulting model can loosely be represented by Figure 3, although no excavation data was used. The key point to mention here is the minor degree of imagination is essential is reconstruction because an archaeological dataset is seldom complete.

Figure 3. Schematic Diagram of 3D modelling stages. This figure shows the typical stages of 3D modelling and its basic components. (Courtesy of Hermon 2008)

Data Sources

My primary data source was Michelle George’s dissertation on the nymphaeum from 1985 at McMaster University. This work included three meticulously detailed section drawings of the room from which I derived the measurements for the geometry of my model. Of course, data uncertainty is always an issue in any archaeological study.

Unfortunately, I had to make a considerable compromise in modelling my geometry in consideration of time constrains. I modelled half of the required geometry with the intention of mirroring the structure, thus creating a complete model. Unquestionably, this has introduced errors into my resulting data as nearly nothing in human construction is impeccably symmetrical, especially a building that is over 2000 years old. This unearths another inherent problem with modelling a reconstruction of a room. Although careful attention was made to model accurately, by ‘turbosmoothing’ my model, I have created a perfectly and uniformly smoothed model. It may look good, but I have knowingly introduced a certain amount of error.

I based the materials and general feeling/evocation of the room on my own personal experience (Figure 4) of visiting the site and photographs from the internet.

Figure 4. A picture of me in the room taken in 2011.

Numerous books, tutorials and descriptions of models found on the internet were essential for the creation of this model (Bekerman 2011; Brinck 2005; DiClementi 2007; DM Multimedia 2008; Master Zap 2013; Nagakura 2011; Pabico 2011; ScratchPixel 2012).

Geometry/Meshes

A highly-detailed geometry is the first step in the 3D reconstruction process. An effort was made to create a reconstruction with as few errors as possible. Quadrangular topology was favoured for modelling as this tends to be more stable than triangular counterparts.

Once a very basic model was obtained, the geometry was made more complex with the intention of adding a turbosmooth modifier on the interior. This was accomplished with swiftloops to achieve a subtle curvature to the model, as nearly nothing in reality is made up perfect ninety degree angles. This added a subtle yet significant degree of realism to the model (Figure 5).

Figure 5a. A comparison of the model without turbosmoothing applied.

Figure 5b. A comparison of the model with turbosmoothing applied.

The final polygon count for the model is 46,684.

Materials

As the materials were one of the most important aspects of my work to achieve my aim, I primarily focused on them in the creation of my model. I used Arch & Design shaders for all my materials.

I intentionally used BRDF by Index of Refraction instead of manually setting facing and perpendicular reflectivity to ensure a realistic reflection falloff was obtained. The decision was made to map the materials visible to the cameras using image-based texturing instead of procedural texturing (Ebert et al. 2003). This allowed for a more accurate representation of the materials as they might have looked.

In adding materials to the walls, the decision was made not to recreate the frescos which might have been on the walls. The entire Praedia was effectively looted upon its discovery in 1755 and it is unknown which frescos ornamented the walls (Parslow 2007). In addition, the condition of most frescos today, having been removed from their walls several hundreds of years ago and hung in museums, are severely degraded. Cracking, fading and warping are all effects which would be irreparable, even if I were to hazard a guess as to which frescos were present in the room. Instead, a red painted plaster material was chosen to represent the walls, which is known to have adorned the walls, albeit not exclusively. This was a severe compromise, although one for which I could not find a solution.

As the room was primarily used in the summer months, it is unlikely that anything other than natural light illuminated the room. Thus the built-in photometric 3DS Max daylight system was set up. As the system cannot calculate the position of the sun before 1583 AD, it was arranged at the pre-set time of 15:00 on the summer solstice (June 21) in the year 2014 AD. Sky portals were also aligned with the two openings in the room, the main entrance and a skylight above the water-stair fountain on the opposite wall. This directed the photons created by the daylight system through these openings.

Rendering

The rendering process was comprised of extensive trial and error. Through several tests, I was able to render out an acceptably realistic image of my model and its materials, textures and lighting, including caustics.

Mental Ray

Mental Ray was the rendering engine selected for the rendering of this model. This is the package renderer that is included with the 3DS Max software and it yielded excellent results for its relative ease of use and speed (O’Connor 2010).

Caustics

Caustics, the way light rays are reflected or refracted by a curved surface or object, such as water, was enabled in my rendering. Caustics add a great deal of realism to my scene. However, it took additional setup, a high number of caustic photons (1,500,000) and very long render times to produce a satisfactory solution.

Anti-Aliasing

As there are several types of filters for anti-aliasing, I’ve chosen to use the Mitchell filter as this is often the most accurate (according to Grant Cox). This seems to have produced the crispest version of my render yet.

Post-Production

The renders produced were still somewhat flat and the shadows not as defined as I would have liked (Figure 6). Thus, the decision was made to create an ambient occlusion pass within 3DS Max and incorporate it into the original render using Photoshop's multiply feature (Figure 7).

Figure 6. The final render output from 3DS Max. As one can observe, the shadows in places such as the shrines and the water-stair fountain are falling flat and do not look realistic.

Figure 7. Ambient Occlusion Pass rendered using Mental Ray in 3DS Max.

Results

The virtual reconstruction of the triclinium of Julia Felix offers valuable information about the visual perception and aesthetics of the room as it might have been in the past (Figures 8, 9, 10 & 11). For its purpose, I believe my reconstruction met my goals, at least superficially. However, the model and its subsequent renders are too pristine and crisp. There is no accumulated stains, dust, scratches and objects or mildew in the water or the water-stair fountain from everyday use. Nor is there background noise from dust or haze in the model. Admittedly, due to time constraints, I was unable to render the model with these effects. The final renders would have taken on a more believable realism from them real-world effects.

Figure 8. The final render looking into the room from the entrance.

Figure 9. A final render looking into the room from the inside, as if standing near the edge of the couch.

Figure 10. A final render of the room looking toward the water-stair fountain. 

Figure 11. A final render of the room as if sitting on the right couch of the triclinium.

Conclusion

The potential for archaeological analysis of sites and objects using 3D virtual modelling is exhilarating. The purposes of this project were to recreate the room as it might have been with the water pooling around the triclinium to understand the general ambience and visual evocation of the room using caustics from the water. In this regard, I think I have succeeded in doing so.

Luckily, we live in a world where technology is constantly changing, advancing and ameliorating the way we see archaeology. The prospects for future research are unknown, yet tremendously optimistic.

Bibliography

Barceló, J.A. 2002. Virtual Archaeology and Artificial Intelligence. In Nicolucci, F. (ed) Virtual Archaeology. BAR International Series S1075, pp. 21-28. Oxford: Archaeopress.

Barceló, J.A. 2010. Visual Analysis in Archaeology: An Artificial Intelligence Approach. In Elewa, A.M.T (ed) Morphometrics for Nonmorphometricians. Lecture Notes in Earth Sciences 124. Berlin: Springer-Verlag.

Dobbins, J.J. & Foss, P.W. 2007. The World of Pompeii. New York: Routledge.

Earl, Graeme. 2009. Physical and Photo-realism: The Herculaneum Amazon. In Archeologica 2.0, Seville Spain, 16-19 Jun 2009.

Ebert, D, Musgrave, F.K, Peachey, D, Perlin, K. & Worley, S. 2003. Texturing and Modeling: A Procedural Approach. San Francisco: Elsevier Science.

George, M. 1986. The Triclinium-Grotto of Julia Felix: The Grotto in Roman Domestic Architecture. Digital Commons @ McMaster University.

Gillings, M. & Wheatley, D. 2001. Seeing is Not Believing: Unresolved Issues in Archaeological Visibility Analysis. In Slapšack, Bozidar (ed) On the Good Use of Geographical Information Systems in Archaeological Landscape Studies: Proceedings of the COST G2 Working Group 2 round table, pp. 25-36. Office for Official Publications of the European Communities: Luxembourg.

Hamilakis, Y. 2013. Archaeology and the Senses: Human Experience, Memory, and Affect. Cambridge: Cambridge University Press.

Hermon, S. 2008. Reasoning in 3D: A Critical Appraisal of the Role of 3D Modelling and Virtual Reconstructions in Archaeology. In Frischer, B. & Dakouri-Hild, A. (eds) Beyond Illustration: 2D and 3D Digital Technologies as Tools for Discovery in Archaeology. Archaeopress.

Kanter, J. 2000. Realism vs. Reality: Creating Virtual Reconstructions of Prehistoric Architecture. In Barceló, J.A, Forte, M. & Sanders D.H. (eds) Virtual Reality in Archaeology. Bar International Series 843, pp. 47-52. Oxford: Archaeopress.

O’Connor, J.A. 2010. Mastering Mental Ray: Rendering Techniques for 3D and CAD Professionals. Hoboken: Sybex.

Papadopoulos, C. & Earl, G. 2009. Structural and Lighting Models for the Minoan Cemetery at Phourni, Crete. In Debattista, K, Perlingieri, C, Pitzalis, D. & Spina, S. (eds) Proceedings of the 10th VAST International Symposium on Virtual Reality, Archaeology and Cultural Heritage.

Papadopoulos, C. & Sakellarakis, Y. 2010. Virtual Windows to the Past: Reconstructing the ‘Ceramics Workshop’ at Zominthos, Crete. In Contreras, F. & Melero, J. (eds) Proceeding of the 38th CAA Conference.

Parslow, C. 2007. Entertainment at Pompeii. In Dobbins, J.J. & Foss, P.W. (eds) The World of Pompeii. New York: Routledge.

Porcelli, V, Villa, F.C, Senabre, J.B, Torres, V.E. & Chapapría, J.E. 2013. Integration of 3D Laser Scanning and Virtual Reconstructions as Research and Educational Tools for Representing the Past: The Case Study of Roman Baths of Edeta. In Earl, G, Sly, T, Chrysanthi, A, Murrieta-Flores, P, Papadopoulos, C, Romanowska, I. & Wheatley, D. (eds) Archaeology in the Digital Era. Amsterdam: Amsterdam University Press.

Visibillity and GIS

Here is the final report from Archaeological Applications of GIS from the University of Southampton

 Intervisibility of Megaliths and Pile-Dwellings along the edge of Lake Neuchâtel in Switzerland

Introduction

Beginning with the chance discovery of the Ober-Meilen prehistoric lacustrine village on the Lake of Zurich in 1854 by a curious school teacher, pile-dwelling sites around lakes and bogs have yielded incalculable knowledge on prehistoric cultures living in the foothills of the Alps. Dendrochronological analyses of well-preserved timbers from numerous sites, along with a wealth of plant and animal remains, suggest a beginning for the Alpine foreland Neolithic around 4300 BC spanning until the seventh century BC (Menotti 2004). Spread across six countries and listed as World Heritage Sites by UNESCO since 2011, the pile-dwellings are hailed as “among the most important examples of archaeological heritage in Europe” (Hafner and Schlichtherle 2008).

As studying nearly one thousand sites throughout the Alpine foreland is beyond the scope of this brief research, Lake Neuchâtel in Switzerland (Figure 1) was selected for study to simplify the necessary computations, as well as to present a straightforward example of using GIS to answer specific archaeological questions. The GIS provides the tools to systematically analyse vision in prehistory, although methods may be the same as manual methods decades ago (Wheatley and Gillings 2000). It should be noted that the scope of this research could easily - read tediously - be adjusted to include all known sites in the surrounding countryside.

Figure 1.  Map of Switzerland with study area. (Copyright: ©2013 Esri, DeLorme, NAVTEQ)

Undoubtedly, the pile-dwellings have been part of a persistent and respected research tradition for over a century and a half. However, standing solemnly nearby, megalithic monuments are consistently overlooked in the context of the cultural landscape. Although archaeological evidence in associated strata around the megaliths is sparse, they were certainly a part of the landscape throughout the 4000 years of documented Neolithic settlement around the lake, notwithstanding the possibility of their construction during this period. The principle aim of this study is to describe and analyse intervisibility between pile-dwelling and megalithic sites to assess whether the megaliths might have played a significant role in the cultural landscape of the Alpine foreland Neolithic. As Wheatley and Gillings point out, “the suggestion is that it is through viewshed analysis that the GIS makes its most unique and valuable contribution to landscape study” (2000). It has thus been chosen to determine the importance of these mysterious megaliths in context with the pile-dwellings. The Kolmogorov-Smirnov one-sample goodness-of-fit test is used to assess the significance of the relationship.

The procedure of georeferencing source maps and digitizing a workable dataset is documented, and the technical and analytical choices made in the interpretation are described. ESRI's ArcMap and ArcCatalog 10.1 were used throughout the data process.

The Context

Lake Neuchâtel is the largest lake in Switzerland at 38 km long and 8 km at its widest point. It was formed through the uplift of the Alps and subsequent glaciations and lies primarily in the modern canton of Neuchâtel, but also shares its border with the cantons of Vaud, Fribourg and Bern. The elevation of its surface is 422 m above sea-level. Visibility from the lake is very high and the assumption that these Neolithic cultures used the lake as a means for transportation and subsistence is not farfetched.

Pile-dwelling sites were settlements built on stilts, or piles, on dry land near the water’s edge. Due to seasonal flooding of the lake, the houses were raised upon piles in such a way that the intermittent overflow did not cause inconvenience. Some of the piles around the lake have been observed to have been taller than 5 m and as short as 0.4 m. There is little evidence to determine what the specific architecture of the dwellings was like, but most research suggests that they were probably single-story houses accessed by ladders or stairs (Leuzinger 2004). Settlements were situated every 2.5-5 kilometres on the shores of Lake Neuchâtel (Rouff 2004), although in this particular study, only the UNESCO qualified sites, of which there are thirteen, are being researched.

The age of the megalithic sites is largely hypothetical due to the lack of archaeological evidence. Therefore, it is not possible to establish precise chronological connections between the megalithic monuments and the pile-dwelling sites, a grim obstacle in my research. Discovering any information of any kind about the megaliths was a challenge in and of itself. However, this problem can cautiously be resolved by suggesting that most megaliths were erected in the Neolithic and were probably contemporaneous with or predated the pile-dwelling settlements. Within the scope of this research, several types of megaliths are being studied: menhirs, large tapered erected stones sometimes found in groups but primarily alone; stone rows or alignments, which include dozens of menhirs in alignment with each other; and dolmens, which are stone slabs assembled as burial chambers. Some of these stones are as tall as 4.5 m (Figure 2). The megaliths must have been important places within the landscape, marked as they were by such imposing heights. For purposes of the research, megalith type is not considered an important factor in intervisibility.

Figure 2.  An example of a Swiss megalith. The Menhir de Clendy of Yverdon-Les-Bains, part of a stone alignment, this is the tallest at 4.5 m.    (Source)

Methodology

Fortunately for the author, a Digital Elevation Model, the foundation for any visibility study, was already available for the study area, obtained from the NASA Shuttle Radar Topography Mission which has an estimate height error report of 5 m and is accurate to 3 arc seconds, which equates to 90 m on the ground. Of course, the quality of the DEM determines the accuracy of the findings. Although this was not the most accurate of DEMs, the author, with financial constraints, had to opt for data that was free of cost.

This particular DEM uses the World Geodetic System 1984 coordinate system, one of the main reference systems for cartography. However, the author deemed the European Datum 1950 Universal Transverse Mercator projected coordinate system to be better suited to the study area because the UNESCO data utilizes this system. Thus, the elevation data was exported within this datum and all subsequent analyses use ED 1950 UTM Zone 32 North.

Individually georeferenced pile-dwelling maps from a UNESCO nomination file were used to digitize the locations of each pile-dwelling site around the lake. There were inherent problems with the precision of this method because the measured grid around each of these maps was imprecise. This made itself evident in the digitizing process because the edges of the lake did not match the base map. The imprecise maps were individually adjusted to match with the base map which was accurately georeferenced. The viewpoint taken is static and situated in the relative center of the settlements or megaliths. The above factors have clear implications for accuracy and precision of the subsequent data.

The locations of the megaliths were obtained from coordinates from an online database at www.megalithic.co.uk. The coordinates were manually entered into ArcMap and display as central points to the location of the megalith(s). Lake Neuchâtel was also digitized to eventually obtain a cumulative viewshed of all the points within the lake. The end map, created for display, (Figure 3) contains contour lines, both types of sites and the lake itself.

Figure 3. Map of Lake Neuchâtel displaying megaliths and pile-dwellings with surrounding landscape contours made entirely from digitized data.

Now, the process of creating relevant viewsheds was possible. Ideally, the visibility of features should be considered according to factors of the nature, density and height of the vegetation, the weather and season (Wheatley and Gillings 2000). The DEM is a smooth surface and does not take into account the presence or absence of trees or any other vegetation. The area for which visibility was calculated was restricted to a buffer zone of 10 km around the edge of the lake. Because viewshed does not readily extend beyond a radius of about 5 km (Loots 1997), this is an overestimation of perception but, for the sake of the study, it ensures minimal edge effects within the area of study and that the viewshed is not subject to artificial truncation (Wheatley and Gillings 2000, Conolly and Lake 2006).

The modern heights of seven of the megaliths were recorded in the database. However, some of the megaliths have toppled in modern times or are so obscure that the database had no height data, in which case an average of the known megalith heights was calculated (2.7 m) and was used as the height data for the four unknown megalith heights. The heights of the pile-dwellings also had to be interpolated. According to Leuzinger (2004), the piles themselves range from 0.4 m to over 5 m tall. In order not to skew the data, the author elected again to assign the average height of the known piles (2.7 m) plus the average height of a person (1.7 m) as the offset in the viewshed (4.4 m), to simulate a person standing on the floor of a pile-dwelling. As for the heights of the pile-dwellings themselves, a conservative height of 6 m was selected to represent the maximum height of the pile-dwellings.

The author utilized the work of Kvamme (1990) and Wheatley (1995) from which to base her model. To initiate the Kolmogorov-Smirnov one-sample goodness-of-fit test, a ‘population’ of all possible pile-dwelling locations was generated from the megalith viewshed by creating a 600 m buffer around the lake to ensure all known pile-dwelling locations were within the buffer zone (Figure 4). This is the statistical population, while the pile-dwelling sites are the statistical sample from that population, from which to conduct the goodness-of-fit test. Given these, the author has constructed a pair of hypotheses from which to test as follows:

• H₀ – The pile-dwelling sites are distributed regardless of the number of megaliths which are visible.
• H₁ – The pile-dwelling sites are NOT distributed regardless of the number of megaliths which are visible.
  
  

  

  Figure 4. Map of 10km buffer zone and viewshed map from the megaliths. The thin sliver around the lake is the 600m buffer zone from which the statistical population is derived.

A separate Kolmogorov-Smirnov test was also conducted to test the significance of the intervisibility between the megaliths and the viewpoints on the lake. A buffer of 2000 m around the lake was generated to include all known megaliths sites (Figure 5). In the same manner as before, this buffer is the population and the known megaliths sites are the sample. Given these, the author has constructed a pair of hypotheses from which to test as follows:

• H₀ – The megaliths are distributed regardless of the number of lake-points which are visible.
• H₁ – The megaliths are NOT distributed regardless of the number of lake-points which are visible.

Figure 5. Map of 10km buffer zone and viewshed map from the lake-points. The thin sliver around the lake is the 2000m buffer zone from which the statistical population is derived.

The Kolmogorov-Smirnov test undertaken for each case adopted a 0.05 confidence interval. Because the sample size was so small for each test, 13 for the pile-dwelling test and 11 for the megalith test, d is 0.361 and 0.391 respectively. Dmax was then obtained from the results. For each data theme used in the final research and the end maps, metadata was created in GeoDoc using the AGMAP 2.1 guidelines and saved as both PDFs and XML files.

Results

For the pile-dwelling test, it can be seen that Dmax (0.14) does not exceed d (0.361) and therefore the test does not allow for the rejection of H0 at the 0.05 confidence interval (Figure 6).

Figure 6. Right: Kolmogorov-Smirnov test for the pile-dwellings. The test compares the distribution of the population and the sites, or samples, with respect to the number of lines-on-sight to the megaliths. Dmax is highlighted. Left: Cumulative distribution, or percentages, of both population and sample cumulative viewshed values. 

Equally for the megalith test, it can be seen that Dmax (0.12) does not exceed d (0.391) and therefore the test does not allow for the rejection of H0 at the 0.05 confidence interval (Figure 7). Thus, neither the distribution of pile-dwellings not the distribution of megaliths are dictated by the location of megaliths or lake-points, respectively.

Figure 7. Right: Kolmogorov-Smirnov test for the megaliths. The test compares the distribution of the population and the sites, or samples, with respect to the number of lines-on-sight to the lake-points. Dmax is highlighted. Left: Cumulative distribution, or percentages, of both population and sample cumulative viewshed values. 

Conclusion

Although the results of this study are not exceedingly thrilling, the use of the Kolmogorov-Smirnov test did statistically proof the significance, or lack thereof, of the specific location of the sites in question. The method was relatively straightforward to implement and, with the right question, could potentially yield interesting and valuable results. This is not to say that the particular location of these sites within the landscape are not dictated by other factors, seemingly unknown at the time of study. Indeed, this result doesn’t necessarily mean that visibility was not at all a factor in location, it just means that the author cannot statistically claim that it was. With a larger sample, more conclusive results could be drawn.

Bibliography

Conolly, J. and Lake, M. 2006. Geographical Information Systems in Archaeology, 6th edn. (Cambridge: Cambridge University Press).

Hafner, A. and Schlichtherle, H. 2008. Neolithic and Bronze Age lakeside settlements in the Alpine region: threatened archaeological heritage under water and possible protection measures – examples from Switzerland and Southern Germany. In Heritage at Risk: ICOMOS world report 2006/2007 on monuments and sites in danger, edited by Petzet, M. and Ziesemer, J. (Altenburg, Germany: E. Reinhold-Verlag). pp 175-180.

Kvamme, K.L. 1990. One-sample tests in regional archaeological analysis: new possibilities through computer technology. American Antiquity, 55 (2), edited by Raymond, W.W. (Washington, D.C.: Society for American Archaeology). pp 367-381.

Leuzinger, U. 2004. Experimental and applied archaeology in lake-dwelling research. In Living on the lake in prehistoric Europe: 150 years of lake-dwelling research. (Abingdon: Routledge). pp 237-250.

Loots, L., Nackaerts, K. and Waelkens, M. 1999. Fuzzy viewshed analysis of the Hellenistic city defence system at Sagalassos, Turkey. In Archaeology in the age of the internet:  computer applications and quantitative methods in archaeology 1997, edited by Dingwall, L., Exon, S., Gaffney, V., Laflin, S. and van Leusen, M., BAR International Series 750. (Oxford: Archaeopress). pp 82 [CD ROM].

Menotti, F. 2004 (ed). Introduction: the lake-dwelling phenomenon and wetland archaeology. In Living on the lake in prehistoric Europe: 150 years of lake-dwelling research. (Abingdon: Routledge). pp 1-6.

Ruoff, U. 2014. Lake-dwelling studies in Switzerland since ‘Meilen 1854’. In Living on the lake in prehistoric Europe: 150 years of lake-dwelling research. (Abingdon: Routledge). pp 9-21.

Wheatley, D. 1995. Cumulative viewshed analysis: a GIS-based method for investigating intervisibility, and its archaeological application. In Archaeology and geographic information systems: a European perspective, edited by Lock, G. and Stancic, Z. (London: Taylor & Francis). pp 171-185.

Wheatley, D. and Gillings, M. 2000. Vision, perception and GIS: developing enriched approaches to the study of archaeological visibility. In Beyond the map: archaeology and spatial technologies, edited by Lock, G.R., NATO Science Series A: Life Sciences. (Amsterdam: IOS Press). pp 1-27.

AutoCAD Project Problems

I'm in the process of researching for a project in my 3D recording and interpretation class. The assignment will test my ability to choose appropriate Computer Aided Design (CAD) methods to address an archaeological question, to critique their applications and thoroughly document my outcomes.

Because I'm primarily interested in Prehistoric stuff, I'm finding it extremely difficult to find a subject that is suitable for this project. The CAD technology seems to be too rigid for such a subject because most prehistoric remains and features are so organic in shape (and mostly in ruins).

So I've decided to steer away from such ancient remains and model a medieval castle. Herein lies the problem. Finding accurate plans and measurements for medieval castles is nearly impossible. After days of researching, I have yet to find something I can model! So I had this idea to start a blog about my problems (and, hopefully, successes). I'd like to think that this might help someone searching for the same answers.

Here's some cool things that I've found.


A 3D model of Le Château de Pierrefonds
This is the work of Andrea Polato (who has a beautiful website by the way). His work on the castle is exquisite, unfortunately I don't know where he got his source material! According to the website, this project took one and a half years to complete and it shows in the level of detail. With his reconstruction, Andrea was able to visually phase the restoration of the castle, first by producing a ruin model, then a middle restoration and finally a complete restoration model based on the work of Eugene Viollet-le-Duc. Simply beautiful.

Caldonazzo Castle - From Ruins to Archaeological 3D Reconstruction
This model was created using Structure-from-Motion which creates a point cloud in a virtual environment from a series of photographs. The results are an accurate 3D model of this beautiful castle using free and open software.


This is my mom and brother in the early '90s near my favorite castle in the world: Chillon Castle in Switzerland. I would really love to model this castle in AutoCAD. Blueprints and floor plans exist but I'm having trouble finding accurate dimensions of the height of the building.

More stuff coming soon...