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14: Sky-view factor is defined as the proportion of visible sky (Ω) above a certain observation point as seen from a two-dimensional representation (A). The algorithm computes the horizon angle γ in n (presented are eight) directions to the specified radius R (B) 

14: Sky-view factor is defined as the proportion of visible sky (Ω) above a certain observation point as seen from a two-dimensional representation (A). The algorithm computes the horizon angle γ in n (presented are eight) directions to the specified radius R (B) 

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Archaeological interpretation of lidar derived relief models is strongly dependent on the specific characteristics of different data visualization techniques, especially when not combined with extensive field surveying. Archaeologists dealing with such interpretations are mainly confined to analytical hillshading, the most frequently used technique...

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... archaeological features as well (Challis et al. 2011), but require additional calculations and the results are more generalized. The SVF computation is based on diffuse illumination. An imaginary light source illuminates the relief from the celestial hemisphere, which is centred at the point being illuminated. Additionally it assumes that: In such a case, the relief illumination is correlated to a portion of the visible sky that is limited by the relief horizon (either terrain or surface, depending on the application) corresponds to the relief illumination; a ridge is more illuminated than the bottom of a steep valley because both are illuminated from the bright sky and more sky can be seen from the ridge than from the valley. The most convenient measure for expressing the portion of the visible sky is the solid angle, Ω (Figure 8.14), which is proportional to the surface area, S , of the projection of the object onto the sphere centred at the observation point, divided by the square of the sphere’s radius R: Ω = k • S/R 2 . In order to normalize the SVF between 0 and 1 the proportionality constant k is set to the value of 1/2 π (Marks et al. 1979). Values close to 1 indicate that almost the entire hemisphere is visible, which is the case in exposed features (planes and peaks), while values close to 0 are present in deep sinks and lower parts of deep valleys where almost no sky is visible. The light that falls from the sky onto a certain part of the surface is reduced by the obstacles that form the horizon. These obstacles can be described in all directions by the vertical elevation angle above the horizontal plane. A good SVF approximation can therefore be performed with the estimate of this angle in several directions. After the vertical elevation angle is determined in the chosen number of directions n , the SVF is determined as a sum of all portions of the sky within each direction: ∑ (1 – sin γ i )/n , where γ i is the vertical angle of the horizon in the direction i . The computation of the horizon in multiple directions is time consuming so simplified methods have been developed (Duffie and Beckman 1991; Tian et al. 2001), that ...

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... These included Analytical Hillshades (simple relief shading) by one light source (cf. Kokalj et al., 2013), primarily using the SAGA tool "Combined Shading", which creates the impression of diffuse light scattering in combination with the slope. The height of the light source above the horizon was set between 15° and 35° and the result was displayed in a grey scale with a linear histogram stretch (Fig. 6A). ...
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The interdisciplinary project "Between Land and Sea" combines geological, geomorphological and paleo-environmental approaches to identify archaeological remains of the Chekka region (Lebanon). In order to record the topography of this area, the first ever scientific airborne LiDAR data acquisition in Lebanon was conducted in autumn 2018. This work describes not only the acquisition and processing of the LiDAR data, but also the attempt to derive possible archaeological sites from the generated elevation model based on methods for spatial analysis. Using an "inverted mound" (iMound) algorithm, areas of possible settlement structures could be identified, which were classified regarding their probability of a possible ancient site using a deductive predictive model. A preliminary validation of some of the detected favoured areas using high-resolution aerial images has shown that the methods applied can provide hints to previously undiscovered sites. It was possible to identify probable ancient wall remains at several detected locations. In addition, least-cost path analyses were performed to reconstruct possible trade and transport routes from the Lebanon Mountains to the Mediterranean coast. The combination of the results of the iMound detection and classification as well as the calculated path system could point to the strategic location of the modern village of Kfar Hazir as a kind of traffic junction. Moreover, reconstructed main transport routes provide indications of heavily frequented roads and may form the basis for further investigations. To validate the results, upcoming field surveys will be realized on site.
... of the DEM, together with other geomorphometric variables can increase the quantity of information that can be recognized [27][28][29][30][31][32][33][34][35]. When the features that need to be identified are rather small, cover wide areas and are in big number, automatic or semi-automatic methods for their identification and delineation can improve the creation of inventories [36][37][38][39][40]. ...
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Archaeological topography identification from high-resolution DEMs is a current method that is used with high success in archaeological prospecting of wide areas. I present a methodology trough which burial mounds (tumuli) from LiDAR DEMS can be identified. This methodology uses geomorphometric and statistical methods to identify with high accuracy burial mound candidates. Peaks, defined as local elevation maxima are found as a first step. In the second step, local convexity watershed segments and their seeds are compared with positions of local peaks and the peaks that correspond or have in vicinity local convexity segments seeds are selected. The local convexity segments that correspond to these selected peaks are further feed to a Random Forest algorithm together with shape descriptors and descriptive statistics of geomorphometric variables in order to build a model for the classification. Multiple approaches to tune and selected the proper training dataset, settings and variables were tested. The validation of the model was performed on the full dataset where the training was performed and on an external dataset in order to test the usability of the method for other areas in a similar geomorphological and archaeological setting. The validation was performed against manually mapped and field checked burial mounds from two neighbor study areas of 100 km2 each. The results show that by training the Random Forest on a dataset composed of between 75% to 100% of the segments corresponding to burial mounds and ten times more non-burial mounds segments selected using latin hypercube sampling, 93% of the burial mound segments from the external dataset are identified. There are 42 false positive cases that need to be checked, and there are two burial mound segments missed. The method shows great promise to be used for burial mound detection on wider areas by delineating a certain number of tumuli mounds for model training.
... Logical and arithmetical operations, classification, visibility analysis, overlaying procedures, and moving window operations can be used to enhance the edges of features or otherwise improve their recognition. Multiple studies compare the various visualization techniques (see e.g., References [13][14][15][16][17]), including the visualization guidelines by Kokalj and Hesse [18]. Some techniques are simple to compute, e.g., analytical hillshading and slope gradient, while others are more complex, e.g., sky-view factor [13], local relief model [19], red relief image map [20], multidirectional visibility index [21], or multiscale integral invariants [22]. ...
... Kokalj and Hesse [18] (pp. [16][17][18][19][20][21][22][23][24][25][26][27] give guidelines for various visualization methods and terrain types. Similarly, the threshold values for opacity are arbitrary and depend on the terrain type, structures we want to highlight, and the overall desired effect. ...
... The Good representation of color is important because it provides a new visual dimension. Using color hue to display quantitative data is discouraged, because it can be misleading or difficult to discern (see e.g., Reference [16]). Using color lightness (luminance) is more appropriate to display such data [3,74]. ...
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Visualization products computed from a raster elevation model still form the basis of most archaeological and geomorphological enquiries of lidar data. We believe there is a need to improve the existing visualizations and create meaningful image combinations that preserve positive characteristics of individual techniques. In this paper, we list the criteria a good visualization should meet, present five different blend modes (normal, screen, multiply, overlay, luminosity), which combine various images into one, discuss their characteristics, and examine how they can be used to improve the visibility (recognition) of small topographical features. Blending different relief visualization techniques allows for a simultaneous display of distinct topographical features in a single (enhanced) image. We provide a “recipe” and a tool for a mix of visualization techniques and blend modes, including all the settings, to compute a visualization for archaeological topography that meets all of the criteria of a good visualization.
... Una vez realizada la clasificación, se utilizaron diferentes procesos de visualización que permitieron acentuar los rasgos débiles o micro, así como también identificar patrones estructurales arquitectónicos. Para ello utilizamos el software libre Relief Visualization Toolbox (Kokalj et al., , 2013. Algunos de los procesos más eficientes fueron el factor de visión del cielo (Sky View Factor) y los componentes principales de múltiples sombreados (PCA of multiple Hillshades) (Figura 5). ...
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Resumen: El objetivo de este artículo es presentar las potencialidades que posee el uso de la tecnología LIDAR (Light Detection and Ranging) para el estudio de sitios arqueológicos. Para ello daremos a conocer los recientes trabajos realizados en El Shincal de Quimivil e interfluvio de la sierra de Zapata, departamento de Belén, provincia de Catamarca. Se trata de los primeros trabajos con esta tecnología implementados en un sitio arqueológico de la República Argentina. La tecnología LIDAR se basa en la emisión y registro de luz láser reflejada que permite la identificación de distintos niveles de información que el haz encuentra en su camino. Esta propiedad hace posible detectar construcciones a priori ocultas por la capa vegetal. La aplicación de esta metodología en diferentes lugares del mundo ha significado el descubrimiento de estructuras y sitios arqueológicos en los últimos años. Los resultados de este estudio determinaron la presencia de nuevas estructuras arqueológicas no reconocidas hasta el momento y la generación de un Modelo Digital de Terreno (MDT) con una alta resolución espacial. ///////////////////////////////// Abstract: The aim of this article is to assess the potential that LIDAR (Light Detection and Ranging) has for the study of archaeological sites. In doing so, we present our recent research on the site of El Shincal de Quimivil and watershed of the Zapata mountain range, Department of Belén, Province of Catamarca. This is the first research that employs this technology at an archaeological site in the Argentine Republic. LIDAR technology is based on the emission and registration of reflected laser light which thereby allows the identification of different levels of data that the beam finds across its path. This property makes it possible to detect a priori constructions hidden by layers of vegetation. The use of this methodology in different parts of the world has led to the discovery of previously hidden structures and archaeological sites in recent years. The results of our study revealed the presence of new, previously unregistered, archaeological structures at the site, and the generation of a high-resolution Digital Terrain Model (DTM).
... Una vez realizada la clasificación, se utilizaron diferentes procesos de visualización que permitieron acentuar los rasgos débiles o micro, así como también identificar patrones estructurales arquitectónicos. Para ello utilizamos el software libre Relief Visualization Toolbox (Kokalj et al., , 2013. Algunos de los procesos más eficientes fueron el factor de visión del cielo (Sky View Factor) y los componentes principales de múltiples sombreados (PCA of multiple Hillshades) (Figura 5). ...
Article
Full-text available
The aim of this article is to assess the potential that LIDAR (Light Detection and Ranging) has for the study of archaeological sites. In doing so, we present our recent research on the site of El Shincal de Quimivil and watershed of the Zapata mountain range, Department of Belén, Province of Catamarca. This is the first research that employs this technology at an archaeological site in the Argentine Republic. LIDAR technology is based on the emission and registration of reflected laser light which thereby allows the identification of different levels of data that the beam finds across its path. This property makes it possible to detect a priori constructions hidden by layers of vegetation. The use of this methodology in different parts of the world has led to the discovery of previously hidden structures and archaeological sites in recent years. The results of our study revealed the presence of new, previously unregistered, archaeological structures at the site, and the generation of a high-resolution Digital Terrain Model (DTM).
... Simple local-relief model SLRM Neighborhood: rectangle; Neighborhood settings: height 5/width 5 Sky-view factor SVF Search radius: 10 pixels (5 m) Number of search directions: 16 Openness: positive, negative OP_P, OP_N Search radius: 10 pixels (5 m) Number of search directions: 16 does not provide a direct representation of topographic change while it is reported to accentuate data artifacts more than other techniques ( Bennett et al., 2012;Doneus, 2013). More technical details of each visualization method are presented elsewhere ( Devereux et al., 2008;Doneus, 2013;Hesse, 2010;Kokalj et al., 2011;Kokalj, Zaksek, & Oštir, 2013;, and the specific parameters we used are presented in detail in Table II. For analytical hill-shading, the 16 azimuth directions were abbreviated as shown in The most objective and efficient feature extraction from relief visualization models is performed by employing automatic or semiautomatic image analysis algorithms that are considered a very useful tool for environmental remote sensing ( Tarolli, 2014). ...
Article
This paper presents the method used to efficiently identify and map previously unknown subsurface remains in a steep, forested, and mostly unexplored area, within the archaeological site of Porolissum, Romania. The remains are part of the defensive system of the ancient Roman Empire frontiers (Roman limes). The complementary use of high-resolution airborne laser scanning derived digital terrain model and visualization techniques enabled the detection of 79 new, subsurface archaeological structures, most of which were confirmed by ground inspection to be key elements of the limes. The best performing methods, achieving detection of the maximum visible extent for over 75% of all features were in descending order: principal component analysis, simple local-relief model, sky-view factor, and positive openness. Analytical hill-shading, slope, negative openness, and hill-shading had a larger proportion of partial detections. The position of these ancient remains supports the hypothesis that this area was extensively deforested, for strategic purposes, during the Roman period. Employing one of the latest remote sensing techniques, we have identified the location of previously unknown, buried ancient structures of the Roman limes in Dacia Province, an essential step for compiling a database necessary for enlisting this Roman limes sector on the World Heritage List.
... at the beginning of our field research, in 2009, we created a digital terrain model (dtm) through precise total station height measurements tied to national reference points ( fig. 4) in order to document the state of preservation of the mound, which has been liable to destruction owing to both anthropological (ploughing, soil extraction) and natural (erosion, bioturbation) factors. From 2015 we have used a dtm ( fig. 3) that was interpolated from a point cloud (in the form of las-format files) 3 and visualized using the relief visualization toolbox (Kokalj et al. 2013). We used the multi-hillshade, hillshade, slope and sky view Factor visualization techniques. ...
... a whole series of books and articles have recently been published where lidar derivatives are used in the context of heritage in the woodlands (e.g. hesse 2010;Kokalj et al. 2013;mlekuž 2013a, 2013bŠtular et al. 2012;irlinger, suhr 2017). along these lines, the same is valid about recent research tendencies in Polish archaeology (e.g. ...
... A whole series of books and articles have recently been published where LiDAR derivatives are used in the context of heritage in the woodlands (e.g. Hesse 2010; Kokalj et al. 2013;Mlekuž 2013aMlekuž , 2013bŠtular et al. 2012;Irlinger, Suhr 2017). Along these lines, the same is valid about recent research tendencies in Polish archaeology (e.g. ...
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This paper discusses recent advancements in the context of modern conflict archaeology in the woodlands. One aspect of this development of archaeological research is a broad use and application of airborne laser scanning (ALS). Material remains of a forced labour camp and munitions depot in the forests around Gutowiec (Poland) known as Guttowitz 35 are used as a case study. After approaching prisoners' memories concerning the site, the results of ALS combined with the outcomes of fieldwalking at the site are presented. This article tries to back up the following thesis: due to applications of non-invasive methods (e.g. ALS, fieldwalking), archaeology is able to offer a deeper understanding and contextualization of such sites as Guttowiec 35: a fresh insight into the materiality of conflict landscapes from the recent past in the woodlands.
... Image processing can be achieved with photographic processing software to ensure that the full range of possible shades is reproduced to represent all the information that is produced by the visualisation software. This histogram stretch process is essential for comparing visualisation results (Kokalj, Zakšek & Oštir 2013). ...
... There is evidence of data acquisition that was not ideal for archaeological purposes in the Middle Hope Lidar dataset from EA. There is evidence of 'fish scales' in the DTM which suggest that the raster was created directly from the point cloud rather than from an intermediate triangulated irregular network (Kokalj, Zakšek & Oštir 2013). Also, there is an effect referred to as 'charcoal burning' in both DEMs, which is evidence of poor alignment of Lidar scan lines (ibid). ...
... The Hill Shade model, also known as relief shading, is one of the initial methods used for visualisation of Lidar and produces very natural and intuitive results of DEMs (Kokalj, Zakšek & Oštir 2013). This method is naturally easy to interpret due to the assumption that a single light source is used to illuminate the DEM. ...
... The ground points for the area of our interest were reflected with the average spacing of 0.57 m. A 0.5 m. digital terrain model (DTM) was interpolated, which was later visualized using different algorithms 8 . ...
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In our paper we would like to present a remote sensing perspective on damage assessment of a hill-fort from central Poland, which is a listed site. The lime stone from this hill is known for its quality and has been excavated from at least medieval time. Due to poorly performed walking prospections the extent of the site has been faultily drawn and the whole extent of the site has been detected. Although most of it is being protected by and natural-archaeological reserve, some part are still being quarried. The goal of our study was to assess the damage done to the landscape of the Chełmo Mount. In our research we will investigate two types of data: very high resolution satellite imagery and LiDAR data (and its derivatives). Supervised classification and thematic change detection applied on archival satellite imagery enabled us to evaluate the progression of quarry in time. The DTM derived from LiDAR data, brought us the possibility to mark the potential outline of the site and the area to be protected as well as a 3D insight in to the damage done to the landscape itself.