image/svg+xml113 VIII/1/2017 INTERDISCIPLINARIA ARCHAEOLOGICA NATURAL SCIENCES IN ARCHAEOLOGY homepage: http://www.iansa.eu Some Examples of Good Practice in LiDAR Prospection in Preventive Archaeology Milan Horňák a* , Ján Zachar a a VIA MAGNA, s. r. o. Nábrežná 2, 03861 Vrútky, Slovakia 1. Introduction Unlike more generally in Europe, where LiDAR has been applied in many archaeological projects over recent years ( e.g. Bofnger, Hesse 2011; Challis et al. 2011; Devereux et al. 2008; Doneus, Briese 2006; 2011; Doneus et al. 2008; Hesse 2010; Gojda, John 2013; Opitz, Cowley 2013; Štular et al. 2012; Trier, Pilo 2002 etc. ), the potential of airborne laser scanning has been much neglected within Slovakian archaeology over the same period. Apart from some very rare articles on this topic (Ruttkay 2015; Holubec et al. 2016), no complex systematic studies, or even local particular archaeological projects, have been carried out (M. Ruttkay’s study contains just brief visual description of LiDAR data on particular hillforts in Nitra region. No information on ground points fltering algorithm and DEM creation parameters is provided. Furthermore, besides basic analytical hillshading, no further visualisation methods are applied. Graphic vector interpretation is also missing. The study of M. Holubec et al . deals with LiDAR documentation of the Iron Age hillfort Molpír in southwest Slovakia. It focuses mainly upon the possibilities of morphometric analysis by the detection of small anthropomorphic features. For this purpose algorithms aimed at visual augmentation of concave and convex surface shapes were tested). This is also partly due to the fact that in Slovakia, unlike some European countries, no public LiDAR data are available – either in point-cloud format or as DEM products. Although in many European countries LiDAR data are also not publicly available, in most cases they are at least partly accessible commercially. Furthermore, a signifcant part of the territory has not been covered with LiDAR survey at all. One of the aims of this article is to present particular case studies of LiDAR application on various types of archaeological sites in the Turiec region, Slovakia (Figure 1), with the intention to examine the potential of LiDAR in archaeological cultural heritage protection and encourage further development of LiDAR studies. 2. Methods The LiDAR data acquisition of individual test areas were performed at the end of March 2016. For the scanner, a Leica ALS70-CM mounted on the light airplane Cessna 402 Volume VIII ● Issue 2/2017 ● Pages 113–124 *Corresponding author. E-mail: hornak.milan@gmail.com ARTICLE INFO Article history: Received: 28 th February 2017Accepted: 11 th September 2017DOI: http://dx.doi.org/ 10.24916/iansa.2017.2.1 Key words: LiDARhillshadetopographic openness sky view factor hillfort classifcation preventive archaeology ABSTRACT The prime objective of this article is to demonstrate the possibilities of LiDAR mapping in the feld of preventive archaeology. The article focuses upon detailed descriptions of case studies that present particular examples of LiDAR application possibilities, as well as its limitations. The fnal remarks sum up an appropriate procedure for LiDAR prospection when applied to preventive archaeology and cultural heritage.
image/svg+xmlIANSA 2017 ● VIII/2 ● 113–124Milan Horňák, Ján Zachar: Some Examples of Good Practice in LiDAR Prospection in Preventive Archaeology 114 with respect to the landscape’s specifc features was crucial, as it determined the amount of detected ground points and subsequently the global quality of the fnal digital elevation model (DEM) represented by a digital terrain model (DTM) 2 . As all of the inspected sites are situated in a mountainous region with a highly closed tree canopy, the adopted parameters had to respect this determination. Out of the „scene“ options (fat, relief, steep slope) that the software ofered, the „steep slope“ alternative performed the best as all tested sites represent hilly environments with slopes up to 60 degrees in steepness. Moreover, the software ofered advanced parameters that enable a further precision 2 In this article we use DEM as a general expression, whereas DTM (digital terrain model) refers to the terrain model generated purely out of ground points in contrast to DSM (digital surface model) representing a model of the whole surface created out of all points.Table 1. Data of classifcation/ fltration procedure. SiteDocumented areaNr. of all pointsNr. of ground pointsAll points densityGround points density Podhradie-Vrchmúr0.04 km²5,778,1191,190,931 (21%)180/m²38/m²Skl. Podzámok-Katova Skala8.9 km²474,210,983145,160,874 (36%)118/m²34/m²Jasenové- Vyšehrad15 km²671,143,747253,083,224 (37%) 59/m²25/m² Figure 1. Location of the case study sites. 1: Podhradie-Vrchmúr, 2: Sklabinský Podzámok – hillfort “Katova Skala”, 3: Jasenové/Nitrianske Pravno – hillfort “Vyšehrad” was used (Field of View /FOV/: 36ᵒ, Scan Rate Setting used (SR): max 56 Hz, Maximum Laser Pulse Rate: 328400 Hz, Horizontal accuracy: 0.06 m, Vertical accuracy: 0.08 m).The open-source software CloudCompare with the Cloth Simulation Filter (CSF) plugin 1 was applied for the fltering (classifcation) of unclassifed data. The principle of the algorithm is that the original point cloud is turned upside down, and then a virtual „cloth“ is draped upon the inverted surface from above. By analyzing the interactions between the nodes of the cloth and the corresponding LiDAR points, the fnal shape of the cloth can be determined and used as a baseline to classify the original points into ground and non-ground parts (for a better notion of the algorithm see: Zhang et al. 2016). The choice of the optimal parameters 1 http://www.cloudcompare.org/