Campagna di Roma olim Latium:A historical landscape archaeology of Tyrrhenian southern Lazio from late Antiquity to incastellamento

This thesis aims at a spatial analysis of human activity within the landscape of Tyrrhenian southern Lazio between the late Roman and high medieval period (3rd to 14th century AD), using a multidisciplinary dataset. The research is a review study, based on data from primary and secondary sources that are (re)analysed in a regional geographic context. With these data as a background, the landscape is approached from two angles:● The contemporary perspective. Using contemporary archaeological and historical data (3rd to 14th century), a diachronic mapping is made of human activity within the landscape. This mapping is based on finding contemporary sites of human activity and analysing these sites in a spatial context, in a GIS. ● The retrospective perspective. Using historical cartography, data from the historical topographical literature, ethnographic studies and toponymic research, a retrospective analysis is made of the medieval to sub-recent landscape (12th to 20th century), in order to increase our understanding of the longue durée functioning of the landscape. Within the main objective the study aims at two things:1. To diachronically map activity within the landscape, such as settlement, production, trade, ownership, animosities, religion and infrastructure, and the actors involved. 2. To test the used method. It is tried to establish to what extent a multidisciplinary review study can provide new ideas about the chronology of the processes that took place, and on the social reality behind these processes. The thesis concludes with a set of recommendations, intended to facilitate future study

Creation and Spatial Analysis of 3D City Modeling based on GIS Data

The 3D city model is one of the crucial topics that are still under analysis by many engineers and programmers because of the great advancements in data acquisition technologies and 3D computer graphics programming. It is one of the best visualization methods for representing reality. This paper presents different techniques for the creation and spatial analysis of 3D city modeling based on Geographical Information System (GIS) technology using free data sources. To achieve that goal, the Mansoura University campus, located in Mansoura city, Egypt, was chosen as a case study. The minimum data requirements to generate a 3D city model are the terrain, 2D spatial features such as buildings, landscape area and street networks. Moreover, building height is an important attribute in the 3D extrusion process. The main challenge during the creation process is the dearth of accurate free datasets, and the time-consuming editing. Therefore, different data sources are used in this study to evaluate their accuracy and find suitable applications which can use the generated 3D model. Meanwhile, an accurate data source obtained using the traditional survey methods is used for the validation purpose. First, the terrain was obtained from a digital elevation model (DEM) and compared with grid leveling measurements. Second, 2D data were obtained from: the manual digitization from (30 cm) high-resolution imagery, and deep learning structure algorithms to detect the 2D features automatically using an object instance segmentation model and compared the results with the total station survey observations. Different techniques are used to investigate and evaluate the accuracy of these data sources. The procedural modeling technique is applied to generate the 3D city model. TensorFlow & Keras frameworks (Python APIs) were used in this paper; moreover, global mapper, ArcGIS Pro, QGIS and CityEngine software were used. The precision metrics from the trained deep learning model were 0.78 for buildings, 0.62 for streets and 0.89 for landscape areas. Despite, the manual digitizing results are better than the results from deep learning, but the extracted features accuracy is accepted and can be used in the creation process in the cases not require a highly accurate 3D model. The flood impact scenario is simulated as an application of spatial analysis on the generated 3D city model. Doi: 10.28991/CEJ-2022-08-01-08 Full Text: PD

Digital scenography in opera in the twenty-first century

This thesis undertakes an extensive analysis of current trends in digital scenography in opera production, including dramaturgical possibilities, historical precedents, and impacts on backstage processes. Drawing on examples of practice and interviews with major practitioners, the work proposes a method for assessing digitally-enhanced productions and reevaluating existing industry standards

Automatic procedural 3D modelling of buildings

The problem of modelling, especially of large-scale virtual urban environments such as city areas is today very challenging for cartographers. Cities are difficult to model in detail because of their often complex geometries. This paper describes the applied and tested new procedures for the development of a test three-dimensional urban area model using the Esri CityEngine software, which is based on procedural modelling. This process involves three steps. The first step is to collect the available data, as well as the Digital Model Relief data. The second step is to create a Computer Generated Architecture (CGA) file that contains a set of rules used by the software for an automatic generation of the model. The third step is to create and visualize 3D models in the CityEngine software because it can be programmed, for example, according to the rules of cartographic visualization. The Level of Detail (LOD) 2 was reconstructed. Several potential uses of such 3D visualization are also described

BlueHealth: a study programme protocol for mapping and quantifying the potential benefits to public health and well-being from Europe's blue spaces

This is the final version of the article. Available from BMJ Publishing Group via the DOI in this record.INTRODUCTION: Proximity and access to water have long been central to human culture and accordingly deliver countless societal benefits. Over 200 million people live on Europe's coastline, and aquatic environments are the top recreational destination in the region. In terms of public health, interactions with 'blue space' (eg, coasts, rivers, lakes) are often considered solely in terms of risk (eg, drowning, microbial pollution). Exposure to blue space can, however, promote health and well-being and prevent disease, although underlying mechanisms are poorly understood. AIMS AND METHODS: The BlueHealth project aims to understand the relationships between exposure to blue space and health and well-being, to map and quantify the public health impacts of changes to both natural blue spaces and associated urban infrastructure in Europe, and to provide evidence-based information to policymakers on how to maximise health benefits associated with interventions in and around aquatic environments. To achieve these aims, an evidence base will be created through systematic reviews, analyses of secondary data sets and analyses of new data collected through a bespoke international survey and a wide range of community-level interventions. We will also explore how to deliver the benefits associated with blue spaces to those without direct access through the use of virtual reality. Scenarios will be developed that allow the evaluation of health impacts in plausible future societal contexts and changing environments. BlueHealth will develop key inputs into policymaking and land/water-use planning towards more salutogenic and sustainable uses of blue space, particularly in urban areas. ETHICS AND DISSEMINATION: Throughout the BlueHealth project, ethics review and approval are obtained for all relevant aspects of the study by the local ethics committees prior to any work being initiated and an ethics expert has been appointed to the project advisory board. So far, ethical approval has been obtained for the BlueHealth International Survey and for community-level interventions taking place in Spain, Italy and the UK. Engagement of stakeholders, including the public, involves citizens in many aspects of the project. Results of all individual studies within the BlueHealth project will be published with open access. After full anonymisation and application of any measures necessary to prevent disclosure, data generated in the project will be deposited into open data repositories of the partner institutions, in line with a formal data management plan. Other knowledge and tools developed in the project will be made available via the project website (www.bluehealth2020.eu). Project results will ultimately provide key inputs to planning and policy relating to blue space, further stimulating the integration of environmental and health considerations into decision-making, such that blue infrastructure is developed across Europe with both public health and the environment in mind.This work was supported by funding received from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 666773