A semi-supervised learning framework based on spatio-temporal semantic events for maritime anomaly detection and behavior analysis

International audienceDetection of abnormal movements of mobile objects has recently received a lot of attention due to the increasing availability of movement data and their potential for ensuring security in many different contexts. As timely detection of these events is often important, most current approaches use automated data-driven approaches. While these approaches have proved to be effective in specific contexts, they are not easily accepted by operators in charge of surveillance due, among other reasons, to the lack of user involvement during the detection process. To improve the detection and analysis of maritime anomalies this paper explores the potential of spatial ontologies for modeling maritime operator knowledge. The goal of this research is to facilitate the integration of human knowledge by modeling it in the form of semantic rules to improve confidence and trust in the anomaly detection system

Visually Representing Geo-Temporal Differences

Data sets that contain geospatial and temporal elements can be challenging to analyze. In particular, it can be difficult to determine how the data have changed over spatial and temporal ranges. In this poster, we present a visual approach for representing the pair-wise differences between geographically and temporally binned data. In addition to providing a novel method for visualizing such geotemporal differences, GTdiff provides a high degree of interactivity that supports the exploration and analysis of the data

A Roadmap for Using the UN Decade of Ocean Science for Sustainable Development in Support of Science, Policy, and Action

The health of the ocean, central to human well-being, has now reached a critical point. Most fish stocks are overexploited, climate change and increased dissolved carbon dioxide are changing ocean chemistry and disrupting species throughout food webs, and the fundamental capacity of the ocean to regulate the climate has been altered. However, key technical, organizational, and conceptual scientific barriers have prevented the identification of policy levers for sustainability and transformative action. Here, we recommend key strategies to address these challenges, including (1) stronger integration of sciences and (2) ocean-observing systems, (3) improved science-policy interfaces, (4) new partnerships supported by (5) a new ocean-climate finance system, and (6) improved ocean literacy and education to modify social norms and behaviors. Adopting these strategies could help establish ocean science as a key foundation of broader sustainability transformations

Geographic Visualization in Archaeology

Archaeologists are often considered frontrunners in employing spatial approaches within the social sciences and humanities, including geospatial technologies such as geographic information systems (GIS) that are now routinely used in archaeology. Since the late 1980s, GIS has mainly been used to support data collection and management as well as spatial analysis and modeling. While fruitful, these efforts have arguably neglected the potential contribution of advanced visualization methods to the generation of broader archaeological knowledge. This paper reviews the use of GIS in archaeology from a geographic visualization (geovisual) perspective and examines how these methods can broaden the scope of archaeological research in an era of more user-friendly cyber-infrastructures. Like most computational databases, GIS do not easily support temporal data. This limitation is particularly problematic in archaeology because processes and events are best understood in space and time. To deal with such shortcomings in existing tools, archaeologists often end up having to reduce the diversity and complexity of archaeological phenomena. Recent developments in geographic visualization begin to address some of these issues, and are pertinent in the globalized world as archaeologists amass vast new bodies of geo-referenced information and work towards integrating them with traditional archaeological data. Greater effort in developing geovisualization and geovisual analytics appropriate for archaeological data can create opportunities to visualize, navigate and assess different sources of information within the larger archaeological community, thus enhancing possibilities for collaborative research and new forms of critical inquiry

Conception d'un système multidimensionnel d'information sur la qualité des données géospatiales

Jury:Yvan Bédard, Professeur à l'Université Laval, Directeur (Canada)Bernard Cervelle, Professeur à l'Université de Marne-la-Vallée, Président(France)David Coleman, Professeur à l'Université du Nouveau Brunswick, Rapporteur (Canada)Robert Jeansoulin, Professeur à l'Université de Provence, Directeur (France)Bernard Moulin, Professeur à l'Université Laval,Rapporteur (Canada)Nowadays Geographic information is a mass-product often manipulated by users without expertise in geomatics and who have little or no knowledge about the quality of the data being manipulated. Such context significantly increases the risks of data misuse and of negative consequences resulting from these misuses. This thesis aims at providing expert-users and data-quality experts with a new approach allowing them to better evaluate spatial data quality in order to advise non-expert users. This approach is based on the management of quality information within a multidimensional database and on the dynamic and contextual exploration of quality information through quality indicators displayed into a SOLAP system (Spatial On-Line Analytical Processing) built on a Geographical Information System (GIS).L'information géographique est maintenant un produit de masse fréquemment manipulé par des utilisateurs non-experts en géomatique qui ont peu ou pas de connaissances de la qualité des données qu'ils utilisent. Ce contexte accroît significativement les risques de mauvaise utilisation des données et ainsi les risques de conséquence néfaste résultant de ces mauvaises utilisations. Cette thèse vise à fournir à des utilisateurs experts ou des experts en qualité une approche leur permettant d'évaluer la qualité des données et ainsi être à même de conseiller des utilisateurs non-experts dans leur utilisation des données. Cette approche se base sur une structuration des données de qualité dans une base de données multidimensionnelle et une communication dynamique et contextuelle utilisant des indicateurs de qualité affichés dans un système SOLAP (Spatial On-Line Analytical Processing) combiné à un système d'information géographique

The use of GIS and geospatial technologies in support of coastal zones management-results of an international survey

This paper reports on the results of an international survey looking at the use of Geographic Information Systems (GIS) and other geospatial technologies in support of coastal zones management. The survey, conducted in fall 2012, was answered by 328 respondents coming from 59 different countries. It aimed at assessing the proportion of people using such technologies, identifying which specific technologies are used, how often they are used, what they are used for, etc. A set of questions also asked more specifically about the potential of using volunteered geographic information (VGI) in the context of coastal zones management. Results indicate that 92% of the respondents’ organizations use geospatial tools, with 89% of those using GIS tools. They also indicated that although possibly useful, the use of VGI in this context may be challenging, mainly due to a perception that the quality of those data may not be sufficient

Qualité de l'information géographique

(384 pp.

Spatial Data Quality: concepts

incollectio

Fundamentals of Spatial Data Quality

ISBN: 1905209568 (312 pp.)This book explains the concept of spatial data quality, a key theory for minimizing the risks of data misuse in a specific decision-making context. Drawing together chapters written by authors who are specialists in their particular field, it provides both the data producer and the data user perspectives on how to evaluate the quality of vector or raster data which are both produced and used. It also covers the key concepts in this field, such as: how to describe the quality of vector or raster data; how to enhance this quality; how to evaluate and document it, using methods such as metadata; how to communicate it to users; and how to relate it with the decision-making process. Also included is a Foreword written by Professor Michael F. Goodchild