MusA: Using Indoor Positioning and Navigation to Enhance Cultural Experiences in a museum

In recent years there has been a growing interest into the use of multimedia mobile guides in museum environments. Mobile devices have the capabilities to detect the user context and to provide pieces of information suitable to help visitors discovering and following the logical and emotional connections that develop during the visit. In this scenario, location based services (LBS) currently represent an asset, and the choice of the technology to determine users' position, combined with the definition of methods that can effectively convey information, become key issues in the design process. In this work, we present MusA (Museum Assistant), a general framework for the development of multimedia interactive guides for mobile devices. Its main feature is a vision-based indoor positioning system that allows the provision of several LBS, from way-finding to the contextualized communication of cultural contents, aimed at providing a meaningful exploration of exhibits according to visitors' personal interest and curiosity. Starting from the thorough description of the system architecture, the article presents the implementation of two mobile guides, developed to respectively address adults and children, and discusses the evaluation of the user experience and the visitors' appreciation of these application

OpenStreetMap Infrastructure Mapping and Its Usage on Flood Impact Assessment Using InaSAFE in Surabaya

OpenStreetMap has become one of the open data sources used for humanitarian purpose in the last decade. This paper focus on mapping process and flood impact assessment using InaSAFE on exposure data in Surabaya provided by OSM. Key infrastructure mapping by of one of the OSM groups HOT ID in Surabaya has provided various lessons and benefits for Surabaya. These lessons learned are very useful to improve the quality of OSM infrastructure data intrinsic quality and data management, particularly data that related to key and vulnerable infrastructure in the field of disaster risk reductio

Crowdsourced validation and updating of dynamic features in OpenStreetMap an analysis of shelter mapping after the 2015 Nepal earthquake

The paper presents results from a validation process of OpenStreetMap (OSM) rapid mapping activities using crowdsourcing technology in the aftermath of the Gorkha earthquake 2015 in Nepal. We present a framework and tool to iteratively validate and update OSM objects. Two main objectives are addressed: first, analyzing the accuracy of the volunteered geographic information (VGI) generated by the OSM community; second, investigating the spatio-temporal dynamics of spontaneous shelter camps in Kathmandu. Results from three independent validation iterations show that only 10 % of the OSM objects are false positives (no shelter camps). Unexpectedly, previous mapping experience only had a minor influence on mapping accuracy. The results further show that it is critical to monitor the temporal dynamics. Out of 4,893 identified shelter camps, 54% were already empty/closed six days after the first mapping. So far, updating geographical features during humanitarian crisis is not properly addressed by the existing crowdsourcing approaches

Volunteered Drone Imagery: Challenges and constraints to the development of an open shared image repository

Orthorectified imagery is valuable for a wide range of initiatives including environmental change detection, planning, and disaster response. Obtaining aerial imagery at high temporal and spatial scale has traditionally been expensive. Due to lower costs and improved ease of use, unmanned aerial vehicles (UAVs) have been increasingly prevalent. This presents an opportunity to share images as part of participatory geographic information systems initiatives similar to OpenStreetMap. We outline a workflow to generate maps from UAV aerial images. We then present a characterization of software platforms currently available to aid the development of maps from UAV imagery, defined by type of service, whether imagery hosting or data processing. From this analysis, we identify existing barriers to imagery sharing, including data licensing, data quality, and user engagement

Proceedings of the Academic Track at State of the Map 2020

Proceedings of the Academic Track at State of the Map 202

Proceedings of the Academic Track at the State of the Map 2020

Proceedings of the Academic Track at the State of the Map 2020 - Online (originally planned in Cape Town, South Africa) July 4-6, 2020

The tasks of the crowd : a typology of tasks in geographic information crowdsourcing and a case study in humanitarian mapping

In the past few years, volunteers have produced geographic information of different kinds, using a variety of different crowdsourcing platforms, within a broad range of contexts. However, there is still a lack of clarity about the specific types of tasks that volunteers can perform for deriving geographic information from remotely sensed imagery, and how the quality of the produced information can be assessed for particular task types. To fill this gap, we analyse the existing literature and propose a typology of tasks in geographic information crowdsourcing, which distinguishes between classification, digitisation and conflation tasks. We then present a case study related to the “Missing Maps” project aimed at crowdsourced classification to support humanitarian aid. We use our typology to distinguish between the different types of crowdsourced tasks in the project and choose classification tasks related to identifying roads and settlements for an evaluation of the crowdsourced classification. This evaluation shows that the volunteers achieved a satisfactory overall performance (accuracy: 89%; sensitivity: 73%; and precision: 89%). We also analyse different factors that could influence the performance, concluding that volunteers were more likely to incorrectly classify tasks with small objects. Furthermore, agreement among volunteers was shown to be a very good predictor of the reliability of crowdsourced classification: tasks with the highest agreement level were 41 times more probable to be correctly classified by volunteers. The results thus show that the crowdsourced classification of remotely sensed imagery is able to generate geographic information about human settlements with a high level of quality. This study also makes clear the different sophistication levels of tasks that can be performed by volunteers and reveals some factors that may have an impact on their performance

Enhancing Geospatial Preparedness for Disaster Management through the work of development organisations

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsDepending on the complexity of a disaster and the local capacities, international organizations and multidisciplinary response teams might be involved in the response. Geographic Information Systems (GIS) are used for coordination and information sharing. However, geospatial preparedness is necessary: reliable up to date geodata, tools, and people with the knowledge to use those tools. In least-developed countries the lack of geospatial preparedness, particularly geospatial pre-disaster information, hinders disaster response. In those places, the United Nations Office for the Coordination of Humanitarian Affairs creates a framework for cooperation with the Coordinated Data Scramble Initiative where Information Management Officers (IMOs) from different organisations are supported by volunteers and technical communities to provide ad-hoc datasets and infrastructure to use GIS. Nevertheless, long-term solutions are needed. Before the disaster, Non-Governmental Organizations (NGOs) might already be using GIS to implement development projects. Based on the theoretical concept of disaster management and development as a learning circle, this investigation proposes the engagement of development NGOS working in disaster-prone areas to enhance geospatial preparedness. The research was based on a multi-method approach including the study of the body of literature, authoritative reports, and repositories and databases, monitorization of the tools used during responses to real emergencies, and semi-structured interviews to IMOs. Finally, the study concluded with an online survey with a worldwide sample of more than 200 development NGOs. The result show that disaster response requires reliable and up to date geodata which is not always the case. Humanitarian missions often rely on OpenStreetMap as a source of information to overcome this limitation. Therefore, improving OpenStreetMap would improve geospatial preparedness. Many development NGOs use digital geographic information, mostly open-data. They could indeed improve geospatial preparedness allowing community empowerment while conveying relevant pre-disaster datasets to the humanitarian missions. This bottom-up approach would allow for the inclusion of information relevant to the community in the disaster response decision-making process. There is, however, a limitation; most of these development NGOs are not familiar with the platform used by the humanitarian community (i.e., OpenStreetMap). Therefore, the sustainability of this synergic approach requires further harmonization between development and humanitarian organizations working for the wellbeing of the same communitie

Volunteered geographic information in natural hazard analysis : a systematic literature review of current approaches with a focus on preparedness and mitigation

With the rise of new technologies, citizens can contribute to scientific research via Web 2.0 applications for collecting and distributing geospatial data. Integrating local knowledge, personal experience and up-to-date geoinformation indicates a promising approach for the theoretical framework and the methods of natural hazard analysis. Our systematic literature review aims at identifying current research and directions for future research in terms of Volunteered Geographic Information (VGI) within natural hazard analysis. Focusing on both the preparedness and mitigation phase results in eleven articles from two literature databases. A qualitative analysis for in-depth information extraction reveals auspicious approaches regarding community engagement and data fusion, but also important research gaps. Mainly based in Europe and North America, the analysed studies deal primarily with floods and forest fires, applying geodata collected by trained citizens who are improving their knowledge and making their own interpretations. Yet, there is still a lack of common scientific terms and concepts. Future research can use these findings for the adaptation of scientific models of natural hazard analysis in order to enable the fusion of data from technical sensors and VGI. The development of such general methods shall contribute to establishing the user integration into various contexts, such as natural hazard analysis

Being specific about geographic information crowdsourcing : a typology and analysis of the Missing Maps project in South Kivu

Recent development in disaster management and humanitarian aid is shaped by the rise of new information sources such as social media or volunteered geographic information. As these show great potential, making sense out of the new geographical datasets is a field of important scientific research. Therefore, this paper attempts to develop a typology of geographical information crowdsourcing. Furthermore, we use this typology to frame existing crowdsourcing projects and to further point out the potential of different kinds of crowdsourcing for disaster management and humanitarian aid. In order to exemplify its practical usage and value, we apply the typology to analyze the crowdsourcing methods utilized by the members of the Missing Maps project developed in South Kiv