3D SURVEYING AND MODELING OF ARCHAEOLOGICAL SITES - SOME CRITICAL ISSUES -

Abstract. The goal of the reported project is to test and evaluate 3D surveying and modelling methods to document the remaining ancient byzantine city walls of the archaeological site of Aquileia in Friuli Venezia Giulia, Italy. The objectives are threefold: (1) to use 3D data to create maps, facades and sections that provide information useful for archaeological purposes such as the investigation of architectural construction techniques or construction phases, (2) to evaluate and compare photogrammetric and laser scanner data in order to identify the advantages and disadvantages of the two 3D surveying techniques for archaeological applications and needs and (3) to draw broader conclusions about the applicability of photogrammetry and laser scanning for documenting and analysing ancient walls within a particular set of environmental circumstances. The paper presents the employed 3D surveying techniques, the obtained 3D results and 2D products and some critical comments

POINTS CLASSIFICATION BY A SEQUENTIAL HIGHER - ORDER MOMENTS STATISTICAL ANALYSIS OF LIDAR DATA

The paper deals with a new sequential procedure to perform unsupervised LIDAR points classification by iteratively studying skewness and kurtosis for elevation and intensity point distribution values. After a preliminary local shape analysis of elevation and intensity point distributions, carried out from the original discrete frequencies by a non parametric estimation of the density functions, the procedure starts by choosing the category of data (elevation or intensity) to analyse at first: the choice falls on the category better showing by a testing procedure a bi or a multi clustering distribution. The first point cluster is identified by studying the distribution skewness and kurtosis variations, after removing at each step the largest data values. The selected cluster is furthermore analysed by studying higher order moments behaviour of the complementary data category. This makes possible to find out potential sub clusters of the original selected one, permitting, in this way, a more effective point classification. Successive clusters are identified by applying the same iterative procedure to the still unclassified LIDAR points. For complex point distribution shapes or for the classification of large areas, a progressive analysis method, based on the partition of the entire data set into regular subsets, is proposed. Some real numerical experiments confirm the capability of the method proposed. The classification total errors in the experiments range from a minimum value of 1,2% to a maximum value of 8,9%

Characterization and BMP Tests of Liquid Substrates for High-rate Anaerobic Digestion

This work was focused on the physicochemical characterization and biochemical methane potential (BMP) tests of some liquid organic substrates, to verify if they were suitable for undergoing a process of high-velocity anaerobic digestion. The selected substrates were: first and second cheese whey, organic fraction of municipal solid waste (OFMSW) leachate, condensate water and slaughterhouse liquid waste. Firstly, a physicochemical characterization was performed, using traditional and macromolecular parameters; then, batch anaerobic tests were carried out, and some continuous tests were planned. The results revealed that all the analyzed substrates have a potential to be anaerobically treated. Valuable information about treatment rate for a high-velocity anaerobic digestion process was obtained. Start-up of a lab-scale UASB reactor, treating diluted cheese whey, was successfully achieved with good COD removal efficiency. These preliminary results are expected to be further investigated in a successive phase, where continuous tests will be conducted on condensate water and OFMSW leachate. This work is licensed under a Creative Commons Attribution 4.0 International License

LiDAR data filtering and classification by skewness and kurtosis iterative analysis of multiple point cloud data categories

A new procedure supporting filtering and classification of LiDAR data based on both elevation and intensity analysis is introduced and validated. After a preliminary analysis to avoid the trivial classification of homogeneous datasets, a non-parametric estimation of the probability density function is computed for both elevation and intensity data values. Some statistical tests are used for selecting the category of data (elevation or intensity) that better satisfies a bi- or a multi-modal distribution. The iterative analysis of skewness and kurtosis is then applied to this category to obtain a first classification. At each step, the point with the highest value of elevation (or intensity) is removed. The classification is then refined by studying both statistical moments of the complementary data category, in order to look for potential sub-clusters. Remaining clusters are identified by applying the same iterative procedure to the still unclassified LiDAR points. For more complex point distribution shapes or for the classification of large scenes, a progressive analysis is proposed, which is based on the partitioning of the entire dataset into more sub-sets. Each of them is then independently classified by using the core procedure. Some numerical experiments on real LiDAR data confirmed the potentiality of the filtering/classification method

Performance Investigation and Repeatability Assessment of a Mobile Robotic System for 3D Mapping

In this paper, we present a quantitative performance investigation and repeatability assessment of a mobile robotic system for 3D mapping. With the aim of a more efficient and automatic data acquisition process with respect to well-established manual topographic operations, a 3D laser scanner coupled with an inertial measurement unit is installed on a mobile platform and used to perform a high-resolution mapping of the surrounding environment. Point clouds obtained with the use of a mobile robot are compared with those acquired with the device carried manually as well as with a terrestrial laser scanner survey that serves as a ground truth. Experimental results show that both mapping modes provide similar accuracy and repeatability, whereas the robotic system compares favorably with respect to the handheld modality in terms of noise level and point distribution. The outcomes demonstrate the feasibility of the mobile robotic platform as a promising technology for automatic and accurate 3D mapping

Advanced 3D modeling versus Building Information Modeling: the case study of Palazzo Ettoreo in Sacile (Italy)

This paper presents an experience of 3D modeling starting from laser scanning data and following two alternative approaches: the first one, called \u201cAdvanced 3D modeling\u201d, based on an original meshing algorithm, while the second make use of Revit BIM software. The case study in Palace Ettoreo in Sacile (Pordenone, Italy), constructed in Renaissance Venetian style in the 16th century: it has a trapezoid plan and is developed on three floors, with the ground one endowing a portico on two fa\ue7ades. The palace has been surveyed by two terrestrial laser scanners: a Riegl Z420i for 5 external scans and a FARO Photon 120 for 53 internal scans; also a topographic surveying of 270 targets have been carried out. The final TLS cloud has 1,4 billions of points. The Advanced 3D modeling has produced a \u201csmart\u201d mesh, allowing also to model the elements with deformations (out of plumb, bulges and troughs). Moreover, this model drastically reduce the stored data: the whole palace is modeled by 111.496 polygons only. The modeling with Revit follows the classical flowchart where the principal architectonical elements are gradually composed: this HBIM process has required a strong manual work in exploiting the available parametric objects and/or in the definition of new objects. Comparing the two models with respect the points cloud, both have evidenced advantages and limitations: therefore, the best solution is a process involving their combination. At the beginning, the Advanced 3D modeling is performed onto the points cloud, so well exploiting the segmentation tools and the smart meshing of the surfaces preserving any geometrical irregularity. Such obtained model allows metrical and morphological evaluation on the various structural and architectonical elements. Afterwards, this very light model becomes the entry data for the modeling in BIM environment, where also the shape of irregular elements are so imported

Critical factors and guidelines for 3D surveying and modelling in Cultural Heritage

The 3D digitization of sites or objects, normally referred to “realitybased 3D surveying and modelling”, is based on 3D optical instruments able to deliver accurate, detailed and realistic 3D results. Nowadays many non-experts are facing the 3D world and its technologies (hardware and software) due to their easiness of use but a not correct use leads to wrong results and conclusions. The goal of the article is to critically report the 3D digitization pipeline with some Cultural Heritage examples. Based on our experiences, some guidelines are drawn as best practices for non-experts and to clearly point out the right approach for every goal and project