Massive population evacuation in an urban context

International audienceIncreasing urban sprawl all over the world leads to an increase of vulnerabilities, as greater numbers of goods and people are exposed to hazards, both natural (flood, quakes, fires, tsunami, epidemic) and industrial (factories, plants). Population evacuation features amongst the tools political managers can use to mitigate these risks. When evacuations are decided, managers must strike a fine balance between displacing all the people needed to avoid injuries and fatalities, and not evacuating people that would finally not be struck by the hazard. Evacuated populations convoys must furthermore not lead to a sub-crisis where they become new vulnerabilities, or through disorder and density prevent the management of other vulnerabilities. There is regretfully a scarcity of tools to help risks manager make this kind of decision. We present here our works on such tools. Most risk management policies focus on a planar, continuous conception of space. Seveso Directives for example use different radius around the hazard center, a plant for example, to find which housings and business will be affected at which degree. We described in our presentation for UrbanNet 2013 how this approach was found lacking for handling road networks, both as vulnerabilities of the direct hazard, and as the means for a successful crisis management. In order to overcome this obstacle we proposed a city-wide agent based simulation called MOSAIIC to model the car traffic, both in normal and extraordinary situations. In MOSAIIC each driver is capable of strategical, tactical and operational planning and decision making. They have a list of destinations they try to reach, and choose a path to get there using their knowledge of the network. They accelerate, brake, change ways depending on their surroundings and personality. They choose alternative solutions if trapped in traffic jams of when facing a road networks altered from their initial knowledge. In this follow-up article we would like to discuss the data and its analysis we used to calibrate and validate simulations built with MOSAIIC to study theoretical all-car evacuation of the city of Rouen. Furthermore, since MOSAIIC, we started a new project, ESCAPE (Exploring by Simulation Cities Awareness on Population Evacuation), which aims at simulating massive evacuation

un modèle sémantique spatio-temporel pour capturer la dynamique des environnements

National audienceLes Systèmes d'Information Géographique se sont peu à peu imposés comme des outils performants pour organiser, représenter, analyser et visualiser des données géographiques. Toutefois, l'intégration d'une dimension temporelle dans les SIG reste un défi de la recherche en sciences de l'information géographique. Dès lors, le développement de modèles spatio-temporels adaptés à l'étude de phénomènes géographiques réels devient un enjeu majeur dans la conception de systèmes d'informations dédiés à l'évolution d'entités spatiales. Dans ces travaux, nous proposons un nouveau modèle spatio-temporel basé sur une ontologie intégrant les connaissances des experts sur les données géographiques représentées. A terme, les capacités sémantiques proposées dans ce modèle permettent d'assister les experts dans la représentation et l'analyse d'un phénomène spatio-temporel en prenant en compte les informations contextuelles de l'environnement géographique

Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

Identification of Change in a Dynamic Dot Pattern and its use in the Maintenance of Footprints

Examples of spatio-temporal data that can be represented as sets of points (called dot patterns) are pervasive in many applications, for example when tracking herds of migrating animals, ships in busy shipping channels and crowds of people in everyday life. The use of this type of data extends beyond the standard remit of Geographic Information Science (GISc), as classification and optimisation problems can often be visualised in the same manner. A common task within these fields is the assignment of a region (called a footprint) that is representative of the underlying pattern. The ways in which this footprint can be generated has been the subject of much research with many algorithms having been produced. Much of this research has focused on the dot patterns and footprints as static entities, however for many of the applications the data is prone to change. This thesis proposes that the footprint need not necessarily be updated each time the dot pattern changes; that the footprint can remain an appropriate representation of the pattern if the amount of change is slight. To ascertain the appropriate times at which to update the footprint, and when to leave it as it is, this thesis introduces the concept of change identifiers as simple measures of change between two dot patterns. Underlying the change identifiers is an in-depth examination of the data inherent in the dot pattern and the creation of descriptors that represent this data. The experimentation performed by this thesis shows that change identifiers are able to distinguish between different types of change across dot patterns from different sources. In doing so the change identifiers reduce the number of updates of the footprint while maintaining a measurably good representation of the dot pattern

Spatio-temporal visualisation and data exploration of traditional ecological knowledge/indigenous knowledge

Traditional Ecological Knowledge (TEK) has been at the centre of mapping efforts for decades. Indigenous knowledge (IK) is a critical subset of TEK, and Indigenous peoples utilize a wide variety of techniques for keeping track of time. Although techniques for mapping and visualizing the temporal aspects of TEK/IK have been utilized, the spatio-temporal dimensions of TEK are not well explored visually outside of seasonal data and narrative approaches. Existing spatio-temporal models can add new visualization approaches for TEK but are limited by ontological constraints regarding time, particularly the poor support for multi-cyclical data and localized timing. For TEK to be well represented, flexible systems are needed for modelling and mapping time that correspond well with traditional conceptions of time being supported. These approaches can take cues from previous spatio-temporal visualization work in the GIS community, and from temporal depictions extant in existing cultural traditions

Identification, Representation, and Analysis of Convective Storms

Large amount of time series of spatial snapshot data have been collected or generated for the monitoring and modeling of environmental systems. Those data provide an opportunity to study the movement and dynamics of natural phenomena. While the snapshot organization is conceptually simple and straightforward, it does not directly capture or represent the dynamic characteristics of the phenomena. This study presents computational methods to identify dynamic events from time series of spatial snapshots. Events are represented as directed spatiotemporal graphs to characterize their initiation, development, movement, and cessation. Graph-based algorithms are then used to analyze the dynamics of the events. The method is demonstrated using the time series radar reflectivity images during one of the deadliest storm outbreaks that impacted 15 states of southeastern U.S. between April 23 and 29, 2011. As shown in this case study, convective storm events identified using our methods are consistent with previous studies and our analysis indicates that the left split/merger occurs more than right split/merger in those convective storm events, which confirms theory, numerical simulations, and other observed case studies. This study also examines the spatial and temporal characteristics of thunderstorm life cycles in central United States mainly covering Kansas, Oklahoma, and northern Texas during the warm seasons from 2010 to 2014. Radar reflectivity and cloud-to-ground lightning data were used to identify thunderstorms. The thunderstorms were stored in a GIS database with a number of additional thunderstorm attributes. The spatial and temporal characteristics of thunderstorm occurrence, duration, initiation time, termination time, movement speed, and direction were analyzed. Results revealed that thunderstorms were most frequent in the eastern part of the study area, especially at the borders among Kansas, Missouri, Oklahoma, and Arkansas. We also linked thunderstorm features to land cover types and compared thunderstorm characteristics between urban and surrounding rural areas. Our results indicated that thunderstorms favor forests and urban areas. This research demonstrates that advanced GIS representations and analyses for spatiotemporal events provide insights in thunderstorm climatology study

The application of classical conditioning to the machine learning of a commonsense knowledge of visual events

In the field of artificial intelligence, possession of commonsense knowledge has long been considered to be a requirementto construct a machine that possesses artificial general intelligence. The conventional approach to providing this commonsense knowledge is to manually encode the required knowledge, a process that is both tedious and costly. After an analysis of classical conditioning, it was deemed that constructing a system based upon the stimulusstimulus interpretation of classical conditioning could allow for commonsense knowledge to be learned through a machine directly and passively observing its environment. Based upon these principles, a system was constructed that uses a stream of events, that have been observed within the environment, to learn rules regarding what event is likely to follow after the observation of another event. The system makes use of a feedback loop between three sub-systems: one that associates events that occur together, a second that accumulates evidence that a given association is significant and a third that recognises the significant associations. The recognition of past associations allows for both the creation of evidence for and against the existence of a particular association, and also allows for more complex associations to be created by treating instances of strongly associated event pairs to be themselves events. Testing the abilities of the system involved simulating the three different learning environments. The results found that measures of significance based on classical conditioning generally outperformed a probability-based measure. This thesis contributes a theory of how a stimulus-stimulus interpretation classical conditioning can be used to create commonsense knowledge and an observation that a significant sub-set of classical conditioning phenomena likely exist to aid in the elimination of noise. This thesis also represents a significant departure from existing reinforcement learning systems as the system presented in this thesis does not perform any form of action selection

Trame verte et papillons de jour en contexte agricole : influence du paysage sur la dispersion, la diversité génétique et la composition des communautés

The implementation of the “Green and Blue Infrastructure” in France intends to ensure the functional connectivity of habitats (green veining). It is one of the nature conservation policies which aim to reduce the loss of biodiversity caused by the destruction and degradation of natural habitats. The objective of this work was to quantify the impact of connectivity, in comparison to other environmental factors, on the diversity of butterfly communities and their genetic diversity in three French agricultural regions. Two different approaches were applied to understand the underlying processes driving these diversity patterns: i) the study of the whole community and of the different ecological groups, ii) the study of landscape features resistances to butterfly dispersal using a landscape genetics approach on one species: the Meadow brown (Maniola jurtina L.). Our findings show that although local characteristics play a dominant role, landscape context does have an influence on community composition. Arable land cover decreases species diversity, and the Meadow brown genetic diversity and gene flow. Grasslands support more species rich communities, including non-frequent species. Grassy linear landscape elements host impoverished communities, but improve Meadow brown dispersal and enhance its genetic diversity. Species diversity is higher within grasslands in proximity to woody habitats: butterflies may benefit from resources on forest edges; moreover, woodlands seem to limit Meadow brown dispersal while increasing its genetic diversity. The habitat complementarity we evidenced here led us to question the classic model of ecological continuities as a collection of independent sub-networks, one for each type of habitat. According to conservation issues, species under interest and landscape contexts, we also need to identify situations where, among a broad panel of possible conservation actions, increasing connectivity is the most effective solution.La mise en place Trame Verte et Bleue sur le territoire français a pour vocation de garantir la connectivité fonctionnelle entre habitats. C’est une des réponses politiques qui vise à enrayer le déclin actuel de la biodiversité, lie notamment à la destruction et à la dégradation des habitats. L’objectif de cette thèse est de quantifier l’effet de la connectivité, au regard d’autres facteurs environnementaux, sur la diversité des communautés et la diversité génétique des papillons de jour dans trois régions agricoles. Deux approches sont utilisées pour comprendre les processus qui sous-tendent ces patrons de diversité : i) l’étude de la communauté dans son ensemble et des groupes écologiques qui la compose, ii) l’étude de la résistance des milieux a la dispersion par génétique du paysage sur une espèce : le Myrtil (Maniola jurtina L.). Les résultats montrent que même si les caractéristiques locales jouent un rôle plus fort, la structure du paysage influence la composition des communautés. Ainsi, la quantité de terres arables réduit la richesse spécifique, la diversité génétique, et les flux de gènes chez le Myrtil. Les prairies hébergent des communautés diversifiées, incluant des espèces peu fréquentes. Les éléments linéaires enherbes supportent des communautés appauvries, mais favorisent la dispersion et la diversité génétique du Myrtil. La diversité des papillons est plus forte a proximité de boisements : les papillons pourraient bénéficier de ressources sur les lisières ; par ailleurs, les milieux boises semblent à la fois limiter les flux de gènes du Myrtil tout en accroissant sa diversité génétique. La complémentarité des milieux soulevée ici nous invite à repenser le modèle classique en ≪ sous-trames ≫ indépendantes de la Trame Verte et Bleue. Selon les enjeux de conservation, les espèces et les contextes paysagers, il est nécessaire de distinguer les situations ou, parmi un panel d’actions envisageables, améliorer la connectivité est une solution pertinente

Réception des données spatiales et leurs traitements : analyse d'images satellites pour la mise à jour des SIG par enrichissement du système de raisonnement spatial RCC8

De nos jours, la résolution des images satellites et le volume des bases de données géographiques disponibles sont en constante augmentation. Les images de télédétection à haute résolution représentent des sources de données hétérogènes de plus en plus nécessaires et difficiles à exploiter. Ces images sont considérées comme des sources très riches et utiles pour la mise à jour des Systèmes d'Information Géographique (SIG). Afin de mettre à jour ces bases de données, une étape de détection de changements est nécessaire. Cette thèse s'attache à l'étude de l'analyse d'images satellites par enrichissement du système de raisonnement spatial RCC8 (Region Connection Calculus) pour la détection des changements topologiques dans le but de mettre à jour des SIG. L'objectif à terme de cette étude est d'exploiter, de détailler et d'enrichir les relations topologiques du système RCC8. L'intérêt de l'enrichissement, l'exploitation et la description détaillée des relations du système RCC8 réside dans le fait qu'elles permettent de détecter automatiquement les différents niveaux de détails topologiques et les changements topologiques entre des régions géographiques représentées sur des cartes numériques (CN) et dans des images satellitaires. Dans cette thèse, nous proposons et développons une extension du modèle topologique d'Intersection et Différence (ID) par des invariants topologiques qui sont : le nombre de séparations, le voisinage et le type des éléments spatiaux. Cette extension vient enrichir et détailler les relations du système RCC8 à deux niveaux de détail. Au premier niveau, l'enrichissement du système RCC8 est fait par l'invariant topologique du nombre de séparations, et le nouveau système est appelé "système RCC-16 au niveau-1". Pour éviter des problèmes de confusion entre les relations de ce nouveau système, au deuxième niveau, l'enrichissement du "RCC-16 au niveau-1" est fait par l'invariant topologique du type d'éléments spatiaux et le nouveau système est appelé "système RCC-16 au niveau-2". Ces deux systèmes RCC-16 (au niveau-1 et au niveau-2) seront appliqués pour l'analyse d'images satellites, la détection de changements et l'analyse spatiale dans des SIG. Nous proposons à partir de celà une nouvelle méthode de détection de changements entre une nouvelle image satellite et une ancienne carte numérique des SIG qui intègre l'analyse topologique par le système RCC-16 afin de détecter et d'identifier les changements entre deux images satellites, ou entre deux cartes vectorielles produites à différentes dates. Dans cette étude de l'enrichissement du système RCC8, les régions spatiales ont de simples représentations spatiales. Cependant, la représentation spatiale et les relations topologiques entre régions dans des images satellites et des données des SIG sont plus complexes, floues et incertaines. Dans l'objectif d'étudier les relations topologiques entre régions floues, un modèle appelé le modèle topologique Flou d'Intersection et Différence (FID) pour la description des relations topologiques entre régions floues sera proposé et développé. 152 relations topologiques peuvent être extraites à l'aide de ce modèle FID. Ces 152 relations sont regroupées dans huit clusters qualitatifs du système RCC8 : Disjoint (Déconnexion), Meets (Connexion Extérieure), Overlaps (Chevauchement), CoveredBy (Inclusion Tangentielle), Inside (Inclusion Non-Tangentielle), Covers (Inclusion Tangentielle Inverse), Contains (Inclusion Non-Tangentielle Inverse), et Equal (Égalité). Ces relations seront évaluées et extraites à partir des images satellites pour donner des exemples de leur intérêt dans le domaine de l'analyse d'image et dans des SIG. La contribution de cette thèse est marquée par l'enrichissement du système RCC8 donnant lieu à un nouveau système, RCC-16, mettant en ouvre une nouvelle méthode de détection de changements, le modèle FID, et regroupant les 152 relations topologiques floues dans les huit clusters qualitatifs du système RCC8.Nowadays, the resolution of satellite images and the volume of available geographic databases are constantly growing. Images of high resolution remote sensing represent sources of heterogeneous data increasingly necessary and difficult to exploit. These images are considered very rich and useful sources for updating Geographic Information Systems (GIS). To update these databases, a step of change detection is necessary and required. This thesis focuses on the study of satellite image analysis by enriching the spatial reasoning system RCC8 (Region Connection Calculus) for the detection of topological changes in order to update GIS databases. The ultimate goal of this study is to exploit and enrich the topological relations of the system RCC8. The interest of the enrichment and detailed description of RCC8 system relations lies in the fact that they can automatically detect the different levels of topological details and topological changes between geographical regions represented on GIS digital maps and satellite images. In this thesis, we propose and develop an extension of the Intersection and Difference (ID) topological model by using topological invariants which are : the separation number, the neighborhood and the spatial element type. This extension enriches and details the relations of the system RCC8 at two levels of detail. At the first level, the enrichment of the system RCC8 is made by using the topological invariant of the separation number and the new system is called "system RCC-16 at level-1". To avoid confusion problems between the topological relations of this new system, the second level by enriching the "system RCC-16 at level-1" is done by using the topological invariant of the spatial element type and the new system is called "system RCC-16 at level-2". These two systems RCC-16 (at two levels : level-1 and level-2) will be applied to satellite image analysis, change detection and spatial analysis in GIS. We propose a new method for detecting changes between a new satellite image and a GIS old digital map. This method integrates the topological analysis of the system RCC-16 to detect and identify changes between two satellite images, or between two vector maps produced at different dates. In this study of the enrichment of the system RCC8, spatial regions have simple spatial representations. However, the spatial and topological relations between regions in satellite images and GIS data are more complex, vague and uncertain. With the aim of studying the topological relations between fuzzy regions, a model called the Fuzzy topological model of Intersection and Difference (FID) for the description of topological relations between fuzzy regions is proposed and developed. 152 topological relations can be extracted using this model FID. These 152 relations are grouped into eight clusters of the qualitative relations of the system RCC8 : Disjoint (Disconnected), Meets (Externally Connected), Overlaps (Partially Overlapping), CoveredBy (Tangential Proper Part), Inside (Non-Tangential Proper Part), Covers (Tangential Proper Part Inverse), Contains (Non-Tangential Proper Part Inverse), and Equal. These relations will be evaluated and extracted from satellite images to give examples of their interest in the image analysis field and GIS. The contribution of this thesis is marked by enriching the qualitative spatial reasoning system RCC8 giving rise to a new system, RCC-16, implementing a new method of change detection, the model FID, and clustering the 152 fuzzy topological relations in eight qualitative clusters of the system RCC8