Multi-technique approach to rockfall monitoring in the Montserrat massif (Catalonia, NE Spain)

Montserrat Mountain is located near Barcelona in Catalonia, in the northeast of Spain, and its massif is formed by conglomerate interleaved by siltstone/sandstone with steep slopes very prone to rockfalls. The increasing number of visitors in the monastery area, reaching 2.4 million per year, has highlighted the risk derived from rockfalls for this building area and also for the terrestrial accesses, both roads and the rack railway. A risk mitigation plan has been launched, and its first phase during 2014-2016 has been focused largely on testing several monitoring techniques for their later implementation. The results of the pilot tests, performed as a development from previous sparse experiences and data, are presented together with the first insights obtained. These tests combine four monitoring techniques under different conditions of continuity in space and time domains, which are: displacement monitoring with Ground-based Synthetic Aperture Radar and characterization at slope scale, with an extremely non-uniform atmospheric phase screen due to the stepped topography and atmosphere stratification; Terrestrial Laser Scanner surveys quantifying the frequency of small or even previously unnoticed rockfalls, and monitoring rock block centimetre scale displacements; the monitoring of rock joints implemented through a wireless sensor network with an ad hoc design of ZigBee loggers developed by ICGC; and, finally, monitoring singular rock needles with Total Station.Peer ReviewedPostprint (author's final draft

An interpretable machine learning framework for measuring urban perceptions from panoramic street view images

The proliferation of street view images (SVIs) and the constant advancements in deep learning techniques have enabled urban analysts to extract and evaluate urban perceptions from large-scale urban streetscapes. However, many existing analytical frameworks have been found to lack interpretability due to their end-to-end structure and "black-box" nature, thereby limiting their value as a planning support tool. In this context, we propose a five-step machine learning framework for extracting neighborhood-level urban perceptions from panoramic SVIs, specifically emphasizing feature and result interpretability. By utilizing the MIT Place Pulse data, the developed framework can systematically extract six dimensions of urban perceptions from the given panoramas, including perceptions of wealth, boredom, depression, beauty, safety, and liveliness. The practical utility of this framework is demonstrated through its deployment in Inner London, where it was used to visualize urban perceptions at the Output Area (OA) level and to verify against real-world crime rate

Caracterización geométrica y visualización interactiva 3d del patrimonio histórico y artístico en la provincia de Cáceres (España)

[EN] The three-dimensional (3D) visualization of historical and cultural heritage in the province of Cáceres is essential for tourism promotion. This study uses panoramic spherical photography and terrestrial laser scanning (TLS) for the geometric characterization and cataloguing of sites of cultural interest, according to the principles of the Charter of Krakow. The benefits of this project include improved knowledge dissemination of the cultural heritage of Cáceres in a society that demands state-of-the-art tourist information. In this sense, this study has three specific aims: to develop a highly reliable methodology for modeling heritage based on a combination of non-destructive geomatics methods; to design and develop software modules for interactive 3D visualization of models; and to promote knowledge of the historical and cultural heritage of Cáceres by creating a hypermedia atlas accessible via the Internet. Through this free-of-charge hypermedia atlas, the tourist accesses 3D photographic and interactive scenes, videos created by 3D point clouds obtained from laser scanning and 3D models available for downloading in ASCII format, and thus acquire a greater knowledge of the touristic attractions in the province of Cáceres.[ES] La visualización tridimensional (3D) del patrimonio histórico-cultural en la provincia de Cáceres es una herramienta vital para su promoción turística. Este trabajo emplea la fotografía panorámica esférica y el uso del escáner láser terrestre para la caracterización geométrica de los bienes de interés cultural, así como su catalogación, de acuerdo a los principios de la Carta de Cracovia. El beneficio de este proyecto es alcanzar un mayor conocimiento del patrimonio cultural de Cáceres para una sociedad que demanda información turística actualizada. En este sentido, hay tres objetivos específicos en el trabajo: desarrollar una metodología de alto grado de fiabilidad para la modelización del patrimonio basado en la combinación de diferentes métodos geomáticos no destructivos; diseñar y desarrollar módulos de software para la visualización interactiva de modelos 3D; y promover el conocimiento del patrimonio histórico de Cáceres mediante la creación de un atlas hipermedia accesible en Internet. A través del atlas hipermedia, el turista accede gratuitamente a los escenarios fotográficos tridimensionales e interactivos, los videos a partir de las nubes de puntos 3D adquiridas con láser escáner y a la descarga de los modelos 3D en formato ASCII, adquiriendo un mayor conocimiento de los atractivos turísticos de la provincia de Cáceres.The article has been possible thanks to the funding granted by the Junta de Extremadura and the Fondo Europeo de Desarrollo Regional (FEDER), through the reference aid GR15069 for the research groups NEXUS and DESOSTE. In addition, the present work was developed under the 2013 Plan of Initiation to Research of the University of Extremadura within the Program Orientated at Projects of Initiation to Research called Action VII, financed by the Provincial Government in Cáceres. We also thank the Regional Government of Extremadura for providing aerial images. The authors would like to thank Alan D.J. Atkinson Gordo, José Antonio Gutiérrez Gallego, Juan Antonio Pérez Alvárez, Mercedes Jiménez Muñoz, Manuel Sánchez Fernández and David Díaz Paredes for the guidance received. Likewise, thanks are also extended to Mr. Fergus Crystal and Mr. Giles Petty for help with revising the English version of this text.Naranjo, JM.; Parrilla, Á.; De Sanjosé, JJ. (2018). Geometric characterization and interactive 3D visualization of historical and cultural heritage in the province of Cáceres (Spain). Virtual Archaeology Review. 9(18):1-11. https://doi.org/10.4995/var.2018.601011191

Drawing From a Larger Canvas – a Gestalt Perspective on Location-Based Services

Location-based services (LBS) provide mobile users with information and functionality tailored to their geographical location. Within recent years these kinds of mobile information systems have received increasing attention from the software industry as well as from researchers within a wide range of disciplines concerned with the development and use of computer technology. This paper presents a user study of a prototype locationbased service providing an informational overlay to the civic space of Federation Square in Melbourne, Australia. In analysing our field data, we reintroduce the perspective of “gestalt theory”, and argue that describing people’s use of location-based services through gestalt theory’s principles of proximity, closure, symmetry, continuity, and similarity can help explain how people make sense of small and fragmented pieces of information on mobile information systems in context

Dataset of Panoramic Images for People Tracking in Service Robotics

We provide a framework for constructing a guided robot for usage in hospitals in this thesis. The omnidirectional camera on the robot allows it to recognize and track the person who is following it. Furthermore, when directing the individual to their preferred position in the hospital, the robot must be aware of its surroundings and avoid accidents with other people or items. To train and evaluate our robot's performance, we developed an auto-labeling framework for creating a dataset of panoramic videos captured by the robot's omnidirectional camera. We labeled each person in the video and their real position in the robot's frame, enabling us to evaluate the accuracy of our tracking system and guide the development of the robot's navigation algorithms. Our research expands on earlier work that has established a framework for tracking individuals using omnidirectional cameras. We want to contribute to the continuing work to enhance the precision and dependability of these tracking systems, which is essential for the creation of efficient guiding robots in healthcare facilities, by developing a benchmark dataset. Our research has the potential to improve the patient experience and increase the efficiency of healthcare institutions by reducing staff time spent guiding patients through the facility.We provide a framework for constructing a guided robot for usage in hospitals in this thesis. The omnidirectional camera on the robot allows it to recognize and track the person who is following it. Furthermore, when directing the individual to their preferred position in the hospital, the robot must be aware of its surroundings and avoid accidents with other people or items. To train and evaluate our robot's performance, we developed an auto-labeling framework for creating a dataset of panoramic videos captured by the robot's omnidirectional camera. We labeled each person in the video and their real position in the robot's frame, enabling us to evaluate the accuracy of our tracking system and guide the development of the robot's navigation algorithms. Our research expands on earlier work that has established a framework for tracking individuals using omnidirectional cameras. We want to contribute to the continuing work to enhance the precision and dependability of these tracking systems, which is essential for the creation of efficient guiding robots in healthcare facilities, by developing a benchmark dataset. Our research has the potential to improve the patient experience and increase the efficiency of healthcare institutions by reducing staff time spent guiding patients through the facility