TRANSFORMATION METHODS AND ALS-DATA

ARCHAEOLOGY

TRANSFORMATION METHODS AND ALS-DATA VISUALIZATION IN THE STUDIES OF HISTORICAL CHARCOAL PILES Rafał Zapłata2 Krzysztof Bakuła1 Wojciech Ostrowski1 1

Warsaw University of Technology, Faculty of Geodesy and Cartography, Poland

Cardinal Stefan Wyszyński University in Warsaw, Faculty of History and Social Sciences, Poland 2

ABSTRACT Land covered with vegetation, in particular woodland, is poorly recognised but contains a significant number of archaeological features and sites, including a number of objects associated with the production of charcoal in the past, such as charcoal piles or kilns. An example of such objects, analysed in this text, are remains of charcoal piles, which are today visible on the surface in the rudimentary form of grooves and ridges of earth of a few or a dozen centimetres each. Charcoal piles are objects that existed in the past, providing raw material for energy production for the needs of, for example, the development of industry. Identification of these objects in woodlands based on traditional surface prospection is virtually impossible or impossible. This situation is changed by the use of ALS, and above all by the implementation of specific methods of processing geodata, the potential of which is perfectly suited for the identification of very poorly preserved objects, such as charcoal piles. The main purpose of this article is to present methods for assessing quality of the point cloud (based on density) and, most importantly, to review available solutions that allow for diverse visualizations of archaeological objects – historical charcoal piles. Keywords: airborne laser scanning (ALS), archaeological interpretation, charcoal piles, historical – industrial archaeology 1. INTRODUCTION Airborne Laser Scanning in archaeological prospection has become very popular in the last few years and led to the discovery of numerous heritage objects. The new, nondestructive method of surveying is connected not only with gathering raw data but also with the implementation of various tools to transform and visualise data; those methods have a crucial role in the interpretation and analysis of geodata. The most widely used method of data processing (DEM) is hillshading, yet, as literature and the experience of researchers reveal, significantly better results are achieved with the use of several other morphological filters (such as LRM or PCI). Their use enables to discover and register archaeological heritage, including charcoal piles, at the stage of in-house studies. The aim of the project was to recognise the area in the vicinity of Seredzice (Mazowieckie Province, Poland) and to verify the suitability of various geoinformatic tools in the 417

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detection of heritage objects. The carried out investigations allowed to compare different methods of processing and visualising ALS data. Research was based on numerical terrain models acquired from the point cloud generated during airborne laser scanning conducted in spring 2012 by MGGP Aero Sp. z. o. o. with the use of a Riegl scanner, type LMS-Q680i. A full-wave form analysis was carried out for an area of 60 km² in the vicinity of Iłża, Seredzice and Pakosław in the Mazowieckie Province (Fig. 1). The acquired data was characterised by a medium point density – 6 points per square meter for the whole cloud. The declared vertical accuracy was mZ ≤ 0.15 m. The first step in our research was to evaluate the quality of data (especially the density of measurements at ground level). Secondly, diverse methods were used to process geodata for the needs of archaeological research, including the detection of heritage charcoal piles. 2. VULTURAL HERITAGE – CHARCOAL PILES Non-destructive prospection carried out within a project entitled “Use of Laser Scanning and Remote Sensing in the Protection, Analysis and Inventory of the Cultural Heritage. Development of Non-invasive, Digital Methods of Documentation and Recognition of Architectural and Archaeological Heritage Resources” led to the discovery of over 1000 features, which could be, on the basis of in-house studies and field surveys (2012-2013), recognised as remains of charcoal piles – features used in the past to produce charcoal. Remains of charcoal piles were recorded in the vicinity of Seredzice and Iłża in the Mazowieckie Province, on a forested area of approximately 21 km² belonging to forest inspectorate Marcule (Fig. 1) [1]. This group of heritage features has to be connected with the industry of this area, developed within the Staropolski Okręg Przemysłowy (Old Polish Industry Region) and within the somewhat younger Centralny Okręg Przemysłowy (Central Industrial Region). The vast demand for energy raw material – charcoal – from ancient times to modernity, especially during the development of industry in the 18th and 19th centuries, was the main reason for the development of such features in the investigated areas. Those kinds of features have been recognised on the basis of archaeological works [2] and analyses of primary sources [3] in, among other places, Europe and Poland, including the Świętokrzyskie Province and parts of the Mazowieckie Province. However, the exact localisation and number (even estimated) of places connected with charcoal production has not been determined because of the character of those features, their state of preservation and the lack of appropriate research methods. A solution to the above mentioned difficulties was provided by the implementation of Airborne Laser Scanning, which brought new quality to the studies of cultural and industrial heritage. ALS became a method that, with the support of geoinformatic tools, allows to detect and provisionally recognise charcoal piles. Within the project, along the recognition of features, attention was devoted to the need of an analysis and evaluation of measurements and generated derivative products (DEM) in order to improve analysis results and to develop methodology for future research of this type. Another important element within the development of research methods was the implementation of various tools to transform and visualise geodata. This allowed to go beyond the usually implemented method – hillshading and, in result, to recognise new features. 418

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Fig. 1. A visualisation made of the basis of hillshading and a cross-section – a charcoal pile. (left) Area of ALS prospection. The darker area in the south is the area of the discovery of heritage charcoal piles. (right)

Charcoal piles are regular, oval features, approximately 12.5 meter in diameter and characterised, among other traits, by pieces of charcoal visible on the surface, darkrusset humus, circular grooves approximately 0.5-1 meter deep and 0.5-1 meter wide (Fig. 1). The detection was carried out during the first stage of research on the base of DEM generated with the use of hillshading. In result of this process over 1000 features were recognised. However, the implementation of other visualisation tools on test areas allowed to conclude that the number of features is much higher [4] [5] and that the data requires further analyses with the use of other processing and visualisation tools. 3. ALS – ASSESING DATA QUALITY Data acquired during Airborne Laser Scanning can be divided into two categories: data gathered for the needs of non-destructive archaeological prospection and data gathered for other purposes, not connected with research (an example is the Polish ISOK data base - IT System of the Country's Protection Against Extreme Hazards). A crucial part of work with both kind of data is the assessment of the quality of measurements, especially of the point cloud – the spatial density of the investigated area (features) especially of the ground level and the assessment of point classification within the point cloud, i.e. the association of particular points with specific groups (for example soil, low vegetation, buildings). The observed quality of research conducted within numerous projects and the hitherto acquired experience of our team members provided ideas for this article, which is to be another point in the discussion of the quality of ALS data, this time focusing on charcoal piles. One of the basic elements [6] influencing the quality of data gathered trough ALS and thus having impact on their usability for archaeological research is the density of point cloud. It has to be noted that during the prospection of features (such as charcoal piles) that have their distinct forms of structure relief, important is not only the density of the whole point cloud but the density of points at ground level. Figure two indicates the difference in the density of point cloud and the density of points on ground level on the investigated area.

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Fig. 2. Difference in point cloud density (left) and in density of points on ground level (right).

Fig. 3. An area covered by high vegetation (left) and an area of low density of points at the ground level (right).

While assessing this kind of data it is especially important to pay attention to areas in which the density of points is higher because of the accumulation of measurements (repeated flight passes). While analysing the overall density of points it is also worth stressing that the density of points grows (because of the presence of high vegetation, tree crowns etc.) on forested areas (comparing to agriculture areas), but that this growth does not result in a higher density of points on the ground level. On the contrary, a lower density can be usually expected in woodlands. Therefore, before starting archaeological analyses, it is advisable to assess the density of points and create a plan (layer) that shows areas with a significantly lower density of points (compared to the desired density), the investigation of which can lead to wrong conclusions. Figure 3 shows an area with high vegetation and areas with a low density of points, thus illustrating the lack of a clear relationship between the occurrence of high vegetation and the density of ground level points in woodlands. However, not only the presence of vegetation influences the density of points, so does the kind of vegetation, its growth stage (conifers such as young larch trees, a young dense forest etc.), as well as the local occurrence of wetlands, which can be related with the season in which measurements are taken. A different problem, which will be only briefly mentioned here, is the classification of point clouds, which is important for the generation of digital elevation models, for the processing of geodata and, finally, for the recognition of archaeological features. Generally, there are two methods of carrying out classification: automatic and manual. 420

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The best methods for archaeological research is manual. Alternatively, the automatic method with a re-assessment carried out by an operator can be implemented; results have to be verified during traditional field surveys. This method is most suited for the research of heritage charcoal piles. 4. TRANSFORMATION AND VISUALISATION OF ALS-DATA The method most commonly used to process and visualise digital elevation models is hillshading, which has several significant advantages: easiness of data processing, intuitiveness and easiness of interpretation [7]. However, both published accounts and experience from previously carried out research indicate that the use of TPI, LRM or SVF processing enables additional verification and better visualisation of the ground surface and therefore also a more detailed detection of archaeological features, including charcoal piles. Hillshading, is a specific type of DTM processing. Its visualisation shows places (surfaces) remaining in shadow. This shadow is created during illumination simulation of the DTM surface by parallel rays from a source which is defined by azimuth and altitude (Fig. 4). One of the inconveniences of this method is the insufficient visibility of linear objects (like historical roads) paralleled to the rays of light. It can be resolved by generating more simulations with different azimuths of light source and creating RGB composition from three of these simulations. This type of visualisation is called hillshading from multiple directions. A second method that involves multiple hillshading is Principal Component Analysis (PCA) proposed by Devereux et al. [8].

Fig. 4. A model of terrain elevation based on hillshading with shaded reliefs of potential charcoal piles (left). A model generated with the use of principal component analysis (PCA); the same reliefs of potential piles visible in the centre (right).

PCA is one of the most complex visualisation techniques and requires the generation of the principal component form sixteen hillshade images. These input images are obtained by changing the azimuth of light source in order to cover the entire horizon. Three first results of Principal Component Analysis provide good results in case of manual interpretation but the third component is important because of the visibility of microtopography. However, this visualisation method also has drawbacks, which impact its popularity [9]. Major limitations are objects shifting [10] and the non-intuitive appearance of RGB compositions [11]. 421

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The quality of visualisation and analyses depends also on the spatial resolution of DEM; it is illustrated by Figure 5 which shows an elevation model and features generated using hillshading. A significant difference in the quality of elevation models is visible for spatial densities of 1 meter and 0.2 meter.

Fig 5. A DEM generated with the use of hillshading for two spatial densities 1 meter and 0.2 meter.

Topographic Position Index [Weiss. 2001] is an example of a more useful DTM processing method for detection of archaeological features, especially in case of charcoal piles detection [12]. It belongs to trend removal methods [11], which involve the generation of differential models between detailed DTM and its generalisation in order to expose local height difference, such as hills or grooves, which are characteristic for the remainder of charcoal piles. The simplest method for the generation of this model is the application of an averaging low-pass filter followed by the subtraction of processed DTM from the input (detailed) model [6]. A visualisation of processing with the outline of the charcoal piles is shown on Fig. 6.

Fig. 6. An example of processing and DEM visualisation with the use of: Topographic Position Index – TPI.

Local Relief Model is an example of a more complex trend removal processing and visualisation method. It was designed for archaeological research by Hesse [13]. Its 422

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primary aim is to expose local height difference, similar to TPI. However it uses a more sophisticated “purged” generalised model, instead of a simple average one. Results of LRM are strictly dependent on the radius in which the generalised model is calculated. This technique is considered as one of the best methods for the detection of objects like charcoal piles because of its availability of showing micro-topography in flat areas with the preservation of the real scale (unit) of the object [9]. 5. CONCLUDING REMARKS Summing up the results of hitherto conducted research, several issues connected with the investigation of heritage charcoal piles have to be emphasised in the context of methods of processing and visualising ALS data. Relatively common is the problem of an insufficient spatial density of measurements; additional measurement should be carried out on the whole area in order for the data to be used for archaeological research. This problem in connected not only with measurements taken especially for the purposes of archaeological investigations but also with measurements carried out for other purposes, such as the ISOK project [14]. This relates especially to areas covered with dense vegetation, young afforestation areas or areas with particular plants or trees, such a young larches with wide crowns build of vertical branches with thick bundles of needles. For the purpose of detecting, analysing and creating an inventory of heritage charcoal piles, it seems advisable to use the most detailed DEMs, created on the basis of high density ALS data. The objects in question – charcoal piles and piles are small (for example the circular grooves) and characterized by elevation changes of only a few centimetres and should therefore be detected during in-house studies conducted on the basis of several differentiated methods of processing and visualizing ALS data, such as hillshading, LRM or SVF. The previously conducted studies clearly prove that the use of only one method (for example hillshading) is insufficient for non-destructive detection of charcoal piles; the most effective method is LRM. Research leading to the detection of heritage charcoal piles and piles as well as works connected with testing methods of processing and analysis of geodata will be continued during the next years of the project’s implementation. This paper refers to research carried out within the scientific project “Use of Laser Scanning and Remote Sensing in the Protection, Analysis and Inventory of the Cultural Heritage. Development of Non-invasive, Digital Methods of Documentation and Recognition of Architectural and Archaeological Heritage Resources” conducted by the Cardinal Stefan Wyszyński University in Warsaw as part of the “National Program for the Advancement of Humanities” established by the Ministry of Science and Higher Education in Poland. Translated by Marta Dulinicz

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