AUTOMATED RECONSTRUCTION OF 3D BUILDINGS IN HISTORIC CITY CENTERS FROM LIDAR DATA AND 2D BUILDING FOOTPRINTS

This paper describes a process for the automated generation of 3D buildings using 2D building footprints derived from cadastral maps and LIDAR point cloud data. In our approach we extract relevant geometric information from 2D building footprints in order to classify point cloud data. One key concept is the fact that roofs in most cases are aligned to the angles of the walls of a building. This concept is utilized to create contiguous surfaces and to extract ridges. In a field study involving two historic city centers in Switzerland we evaluate the results of our approach

Artificial intelligence and visual analytics in geographical space and cyberspace: Research opportunities and challenges

In recent decades, we have witnessed great advances on the Internet of Things, mobile devices, sensor-based systems, and resulting big data infrastructures, which have gradually, yet fundamentally influenced the way people interact with and in the digital and physical world. Many human activities now not only operate in geographical (physical) space but also in cyberspace. Such changes have triggered a paradigm shift in geographic information science (GIScience), as cyberspace brings new perspectives for the roles played by spatial and temporal dimensions, e.g., the dilemma of placelessness and possible timelessness. As a discipline at the brink of even bigger changes made possible by machine learning and artificial intelligence, this paper highlights the challenges and opportunities associated with geographical space in relation to cyberspace, with a particular focus on data analytics and visualization, including extended AI capabilities and virtual reality representations. Consequently, we encourage the creation of synergies between the processing and analysis of geographical and cyber data to improve sustainability and solve complex problems with geospatial applications and other digital advancements in urban and environmental sciences

A framework for classifying participant motivation that considers the typology of citizen science projects

Citizen science, the participation of the public in scientific projects, is growing significantly, especially with technological developments in recent years. Volunteers are the heart of citizen science projects; therefore, understanding their motivation and how to sustain their participation is the key to success in any citizen science project. Studies on participants of citizen science projects illustrate that there is an association between participant motivation and the type of contribution to projects. Thus, in this paper, we define a motivational framework, which classifies participant motivation taking into account the typologies of citizen science projects. Within this framework, we also take into account the importance of motivation in initiating and sustaining participation. This framework helps citizen science practitioners to have comprehensive knowledge about potential motivational factors that can be used to recruit participants, as well as sustaining participation in their projects

How to Evaluate the Quality of Airborne Laser-Scanning Data

The discussion on the quality of digital elevation models form airborne laser scanner was dominated by the proof of vertical and horizontal accuracy. If the accuracy criteria were verified by ground control points, the evidence of high quality was produced. Based on experiences in projects for the Swiss Federal Office of Topography and according to the lidar requirements formulated by the US American Federal Emergency and Mapping Agency (FEMA) the interpretation of quality must change. Six different quality indicators are described as starting point for enhanced specification of laser data sets. Indicators are worthless if they do not contain a level of acceptance; for each indicator a proposal is discussed. With the help of the more precise requirements and specifications the quality evaluation is simplified. A common understanding of the quality between contractual partners is mandatory for efficient and effective lidar projects.ISSN:1682-1750ISSN:2194-9034ISSN:1682-177