Resolving Dimensions: A Comparison Between ERT Imaging and 3D Modelling of the Barge Crowie, South Australia
Three-dimensional (3D) modelling is becoming a ubiquitous technology for the interpretation of cultural heritage objects. However most 3D models are based on geomatic data such as surveying, laser scanning or photogrammetry and therefore rely on the subject of the study being visible. This chapter presents the case study of Crowie, a submerged and partially buried barge wrecked near the town of Morgan in South Australia. Crowie was reconstructed using two alternative approaches; one based on a combination of historic photographs and computer graphics and the second based on geophysical data from electrical resistivity tomography (ERT). ERT has been rarely used for maritime archaeology despite providing 3D representation under challenging survey conditions, such as in shallow and turbid water. ERT was particularly successful on Crowie for mapping the external metal cladding, which was recognisable based on very low resistivity values. An alternative 3D model was created using historic photographs and dimensions for Crowie in combination with information from acoustic geophysical surveys. The excellent correspondence between these models demonstrates the efficacy of ERT in shallow maritime archaeology contexts.
KeywordsElectrical resistivity tomography Geophysics Historic shipwreck Riverine archaeology
Roberts et al. (2017) undertook the first study of this vessel which was primarily concerned with locating and describing the submerged, but unburied, remains of Crowie via multibeam and sidescan imaging and exploring its Aboriginal significance. Subsequent research has sought to improve our knowledge regarding the dimensions and condition of the buried portion of the vessel via electrical resistivity tomography (ERT) and to validate the accuracy of these data by comparing the results to 3D model created by acoustic geophysical methods and historic photographs. ERT can image submerged and buried shipwreck remains in situ without disturbing the site or undertaking expensive recovery projects. This provides exciting new opportunities to create digital content as part of the increasing trend towards virtual museums in underwater archaeology (i.e., Haydar et al. 2011; Liarokapis et al. 2017; Varinlioğlu 2011). This chapter summarizes the geophysical results relevant to the creation of a 3D model. Further details about the geophysical survey are available in Simyrdanis et al. (2018).
11.2 Crowie’s History, Context, Significance and Construction
11.2.1 History and Context
Crowie operated during the latter half of a booming trade era on the Murray and Darling Rivers, which began in the mid-late nineteenth century. The origins of the river trade were closely tied to the spread of pastoralism from Sydney to South Australia and the associated expansion of the wool industry (Kenderdine 1993). Prior to the establishment of river trade routes, wool produced on these pastoral properties had to be carried along barely formed tracks by bullock and dray which was relatively slow and expensive (Younger 1976). The river trade provided a more efficient means of transporting wool and provisioning of stations until the establishment of railways in the area.
The size of Crowie initially raised some concern, with one critic writing ‘the general opinion is inclined to question the serviceability of a barge so large’ (Anon 1911b). Crowie proved, however, able to successfully transport record-breaking cargo loads including 7200 bags of wheat in 1912 (Anon 1912a, b, c), 7500 bags of wheat in 1913 (Anon 1913b) and 2700 bales of wool in 1918 (Anon 1918). The largest ever consignment of flour (580 tons) shipped on the river was also carried by Crowie (Anon 1920). Other known cargo carried by Crowie included dried fruit (Anon 1912c, 4), red gum piles (Αnon. 1925), stringybark piles (Αnon 1927), chaff (Αnon 1919), telegraph poles (Anon 1924), agricultural implements (Αnon 1913b), cement (Αnon 1922b), and steel plates (Αnon 1939).
Crowie was also critically important during the freshwater famines on the Murray (Anon 1915, 1928). These events resulted from salt water incursions that occurred when sea water entered the river system via the Murray mouth, turning fresh water brackish. Crowie was deployed (as the largest barge available) to pump fresh water into its hull and transport it to towns in need. Crowie was able to move approximately 600 tons each trip (Anon 1915).
The exact date of Crowie’s sinking is unknown. Historical records show Crowie appearing for sale on 11 April 1946, but by 1950 it had sunk (Anon 1950; Roberts et al. 2017). According to the Australian Heritage Database, as well as subsequent investigations by Roberts et al. (2017), Crowie is located approximately 100 m upstream from Morgan Wharf, and 10 m out from the western bank of the Murray River. The reasons for the sinking of Crowie are unknown. It is likely, however, Crowie was simply abandoned and, in the absence of any maintenance, eventually sank at its mooring.
Roberts et al. (2017) demonstrated that river vessels such as Crowie can contribute to the telling of more complex narratives relating to Indigenous riverscapes and cross-cultural entanglements. Their collaborative research, which incorporated historical data, oral histories and geophysical surveys, reminded us that the river trade took place within a riverscape that was and continues to be the ‘country’ of Aboriginal people (Roberts et al.2017, 143). Such riverscapes were and are ‘animated’ spiritual worlds that intersect with people, the environment and material culture (such as river vessels) (after Bradley 1997, 177; Kearney 2009, 171–172). The river boat industry was also entangled with Aboriginal lives in other ways, often overlooked in contemporary histories, through the naming of vessels and the employment of Aboriginal people (Roberts et al.2017). The naming of Crowie is a case in point as it is derived from the Ngarrindjeri (the Aboriginal language belonging ‘to the people of the Lower Murray, Lakes and Coorong region of South Australia’ (Gale and Sparrow 2010, 387)) word krawi which means ‘big’ and was hence appropriated for the barge (Anon 1911a; Nathan and Fang 2014, 51; Roberts et al.2017, 136).
The construction of a number of barges, including Crowie, were undertaken in the Goolwa shipyards. The construction technique for Crowie cannot be confirmed through geophysical data, however the following description of typical bottom-based construction paraphrased from Roberts et al. (2017, 141), likely applied to Crowie. ‘After the keel was laid, wooden bottom planking was assembled, followed by the insertion of angle-iron floors. Iron futtocks were then through-bolted onto the floors to erect the vessel’s framework. The frame was planked up with wooden planking strakes below the waterline and with iron plating above the waterline—both fastened with rivets. A heavy timber keelson was then fastened on top of the floors with keel bolts. Crowie also had an iron-plate stern deck, as well as iron gussets and a barn-door rudder’ (Roberts et al.2017, 141). The bottom-based construction technique used to build Crowie meant that the largest area possible was left free in the barge for storage.
11.3 Geophysical Modelling
Previous research did not examine the portion of the vessel buried in sediment. Thus, whilst the length and beam measurements of Crowie were confirmed through multibeam and sidescan data, the depth of the extant vessel remained unknown, as well as the degree of preservation of the portion of the vessel buried in the riverbed. This project aimed to produce a complete 3D model of the wreck using geophysical data.
11.3.1 Electrical Resistivity Tomography (ERT)
ERT is a geophysical method used for archaeological prospection where a current is injected into the ground and the resulting electrical potential is measured at a variety of locations along a survey line. ERT can resolve buried archaeological and geological features with characteristic electrical signatures (‘anomalies’) that are easily distinguishable from the surrounding environment (Clark 1990). In archaeological investigations, electrical resistivity survey has most commonly been used for mapping of tumuli (burial mounds) (Tsourlos et al. 2014) and imaging buried archaeological features (Papadopoulos et al. 2011).
The application of ERT in submarine archaeology has been relatively uncommon to date. Ranieri et al. (2009, 11) used 3D geoelectrical data to map buried and submerged archaeological features including the ancient settlements at Nora (South Coast of Sardinia), which included Phoenician, Punic and Roman remains and the Roman town of Pollentia (NE of the Isle of Majorca). A comprehensive feasibility study was also undertaken by Simyrdanis et al. (2015, 2016) who investigated the efficacy of ERT for reconstructing submerged archaeological material in shallow seawater environments. That research was undertaken at the Minoan archaeological site of Agioi Theodoroi in Crete, which contains a number of stone walls that were submerged due to recent tectonic activity. Passaro et al. (2009) and Passaro (2010) applied ERT to the investigation of a shipwreck at the Agropoli town of Salerno in Italy. The success of thesestudies indicates that ERT is an appropriate method for imaging conductive (metallic) objects and resistive (wooden) bodies in aquatic environments. This project represents the first time, however, that ERT has been used to map an entire shipwreck in 3D.
11.3.2 Data Acquisition and Modelling
11.3.3 Data Processing and Results
11.4 Visual Model
An alternative approach to creating a 3D model of a sunken vessel is by combining historic photos, measurements and descriptions from the literature to create a virtual reconstruction. This approach provides an important comparison to other forms of 3D modelling, such as photogrammetry or laser scanning, the results of which can be used to answer archaeological questions and to provide an effective tool for public engagement (i.e., Kormann et al. 2017; Plets et al. 2009).
In the case of Crowie, a visual 3D model was constructed, using the Blender 3D software suite, on the basis of photographs, published descriptions of the vessel’s measurements and the dimensions recorded by the multibeam and sidescan sonar. Initially, a virtual box was created using the barge’s maximum dimensions that acted as the outer limits of the 3D model. A virtual tube shape with the approximate form of the barge was then added. The dimensions of the vitual box and tube were informed by the measurements summarised in Roberts et al. (2017). Some detailed features, such as the name of the barge, internal division blocks and steering wheel base structure, were subsequently included based on historic photographs.
Once the visual model was created, it was transferred to the 3D visualizing and processing software Meshlab for verification. Indeed, a specific algorithm implemented in Meshlab (Corsini et al. 2009) allows for detailed comparison of digital model to photographs. The visual inspection of this alignment provided important clues on the morphology of the barge and helped improved the accuracy of the final model.
The Crowie case study illustrates the relative advantages and disadvantages of two different 3D modelling methodologies for documenting archaeological materials which cannot be measured using conventional approaches. Clearly these methods cannot provide the same degree of spatial accuracy as is possible from survey techniques such as laser scanning or photogrammetry but are well suited to particular survey conditions, such as where the target is buried or in turbid or shallow water.
ERT was successful in the case of Crowie at imaging the parts of the wreck with a high degree of resistivity contrast from the surrounding materials (as shown in Figs. 11.8 and 11.11). In this case, the metal parts of the wreck (which have extremely low resistivity) were well resolved but the wooden features were much more ambiguous. An important advantage of ERT is that ferrous and non-ferrous metals do not have markedly different resistivity values and so ERT is unlike magnetometry in being able to image aluminium and other non-ferrous metals. ERT is also very suitable for shallow water contexts where sub-bottom profiling is problematic due to the abundance of ‘ringing’ from the sea floor reflector. A disadvantage of ERT is that it provides data with much lower resolution (0.5 m horizontal in this case) than would be possible from other methods. This resolution is governed by the minimum electrode spacing which is usually 0.5 m or 1 m, although it could be reduced for small survey areas. Another disadvantage of this method is that it requires a fixed survey grid and needs to be collected in static fashion, meaning it is much slower than other comparable methods.
The 3D digital model is visually appealing and easily recognisable as a cargo barge despite the image being stylized. While the image appears detailed, it is based on relatively sparse information and so the representation of the vessel’s features is interpretive rather than accurate. In the context of public outreach, these (necessary) inaccuracies are trivial, however they may be more important for detailed research on shipbuilding. Due to the data sources, the image captures the form of the contemporary vessel when it is intact and not buried. In contrast, the 3D geophysical model based on the ERT data accurately represents the wreck in its current condition and provides a model that is much lower resolution, less visually appealing and more difficult to understand. The ERT survey also requires intensive fieldwork and specialized equipment. Nonetheless, it provides a quantitative image that is very useful for understanding the current condition of the vessel, particularly the sub-surface portion which is inaccessible to other, more conventionally applied, geophysical techniques.
The submerged and partially buried barge Crowie was used as a case study to test the applicability for a 3D reconstruction of shipwreck using both geophysical survey and historical research. The model created from ERT data provided an image of the current condition of the buried portion of the wreck while the model created from historic research combined with sidescan sonar and multibeam data provided a visually appealing 3D model with an excellent spatial correspondence with the ERT model. The final products, while different, are an evocative representation of a vessel that previously played an important role in the Murray River trade and which has been used to illustrate Aboriginal significance of riverscapes in the region. This study demonstrates that both geophysical and historical data can serve an important role in providing quantitative geometric information to constrain 3D models, particularly in low visibility conditions or when the target is buried. This project has also established that ERT is an effective geophysical method for maritime archaeology contexts, particularly in relation to shallow and turbid water environments.
The overall project, including fieldwork activities, was funded by the 2017 Australia Awards-Endeavour Research Scholarships and Fellowships provided by the Australian Government and granted to Kleanthis Simyrdanis between July and December 2017. Ian Moffat is the recipient of an Australian Research Council Discovery Early Career Award (project number #DE160100703) funded by the Australian Government and a Commonweath Rutherford Fellowship funded by the Commonwealth Scholarships Commision. That you to Homerton College which hosted Ian Moffat as a Research Associate during the writing of this manuscript. Flinders University provided equipment and financial assistance needed for geophysical data acquisition. Thank you to Lisa and Barry from Morgan Waterfront Marina and ZZ Resistivity for their support of this research. Special thanks to Nikos Papadopoulos for his assistance during the fieldwork and data interpretation as well as to Lee Rippon, John Naumann, Celeste Jordan, Belinda Duke and Anika Johnstone who contributed to the field work for the project. We also acknowledge the River Murray and Mallee Aboriginal Corporation and the prior work of Roberts et al. (2017) which formed the basis for this methodological study.
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