An agent-based simulation model for business reopenings in New Orleans post Hurricane Katrina

The empirical study of business responses to disasters is relatively scarce, despite that they are a fundamental part of the cities, providing services, jobs and, taxes that are essential for urban sustainability. This dissertation develops an agent-based simulation model to represent and understand the businesses reopening process in a dynamic environment in New Orleans after Hurricane Katrina. The objectives are two-fold: 1) To identify the main reopening predictors involved and estimate their relative importance through time, using an empirical data set collected from another study; 2) To represent the business reopening process through a computer simulation model, using the parameters derived from the first objective. The results show that businesses located in flooded areas had lower reopening probabilities, however the effect was significant only in the first nine months after the disaster. Larger businesses had better reopening probabilities than smaller ones, although this variable stopped being significant after six months. Variables associated with higher social vulnerability, such as percent non-white population and percent population under 18, had a negative effect on the business reopening probabilities at different points of time. The influence of neighboring firms using 1-km buffer was found significantly positive only immediately after the disaster; it became significantly negative one year after the disaster. The simulation model developed proved to mimic the reopening process at a suitable level. The model was used to simulate two scenarios: 1) First, the flood depth was reduced by 1 meter as a way to represent the implementation of measures designed to increase the buildings and infrastructure resistance to floods. The simulation results indicate that there are specific areas that would obtain greater benefit from these measures, however ten months after the disaster the effect of the measures tends to diminish. 2) Second, the spatial effects of aids were simulated by making a limited number of businesses in specific locations totally resilient to the disaster. The results indicate that the beneficial effect is influenced by variables such as business density and socio-economic conditions of the area. The positive effect is perceivable until four months after the disaster, after this point it diminishes

LC3: A spatio-temporal and semantic model for knowledge discovery from geospatial datasets

International audienceThere is a need for decision-makers to be provided with both an overview of existing knowledge, and information which is as complete and up-to-date as possible on changes in certain features of the biosphere. Another objective is to bring together all the many attempts which have been made over the years at various levels (international, Community, national and regional) to obtain more information on the environment and the way it is changing. As a result, remote sensing tools monitor large amount of land cover informations enabling study of dynamic processes. However the size of the dataset require new tools to identify pattern and extract knowledge. We propose a model to discover knowledge on parcel data allowing analysis of dynamic geospatial phenomena using time, spatial and thematic data. The model is called Land Cover Change Continuum (LC3) and is able to track the evolution of spatial entities along time. Based on semantic web technologies, the model allows users to specify and to query spatio-temporal informations based on semantic definitions. The semantic of spatial relationships are of interest to qualify filiation relationships. The result of this process permit to identify evolutive patterns as a basis for studying the dynamics of the geospatial environment. To this end, we use CORINE datasets to study changes in a specific part of France. In our approach, we consider entities as having several representations during their lifecycle. Each representation includes identity, spatial and descriptives properties that evolve over time

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

Overview of the ImageCLEF 2017 Population Estimation (Remote) Task

Estimating population has many applications as planning disaster responses, communication infrastructure, or development activities. In 2017, ImageCLEF Lab introduced a new pilot task: the Population Estimation (or Remote) task which aims at estimating the population of an area of interest by exploring Copernicus earth observation data (i.e. free Sentinel-2 satellite images). In line with the goal of FabSpace 2.0 project, a European Unions initiative to bring Geo-Enthusiast together around the 6 European universities in collaboration with Business Incubation Centers, participated to this challenge. This paper presents the results that were obtained by the participants as well as a brief summary of some of the approaches that were used

Un modèle pour l'intégration sémantique de données géolocalisées d'observation de la Terre

Le domaine de l'observation de la terre est en forte évolution. L'Agence Spatiale Européenne a récemment lancé les satellites Sentinel qui livrent entre 8 à 10 To de données par jour, ce qui ouvre de nouvelles opportunités d'applications pour étudier l'environnement, l'urbanisme, l'océan, le climat, etc. Afin de mieux exploiter ou retrouver ces données d'observation, ces applications nécessitent de leur associer des données provenant de différentes sources. Un des défis à relever est alors d'intégrer ces données malgré leur hétérogénéité. Les technologies du web sémantique apportent une solution en fournissant une infrastructure basée sur RDF et des ontologies. Dans cet article, nous présentons une approche pour enrichir les méta-données habituelles des images satellites avec des données externes (e.g. les mesures de températures enregistrées pour la région représentée sur l'image). Nous proposons un vocabulaire sémantique et une formalisation des relations spatio-temporelles support au processus l'intégration des différentes données géolocalisées associées à des observations de la Terre

MPC for optimal dispatch of an AC-linked hybrid PV/wind/biomass/H2 system incorporating demand response

[EN] A Model Predictive Control (MPC) strategy based on the Evolutionary Algorithms (EA) is proposed for the optimal dispatch of renewable generation units and demand response in a grid-tied hybrid system. The generating system is based on the experimental setup installed in a Distributed Energy Resources Laboratory (LabDER), which includes an AC micro-grid with small scale PV/Wind/Biomass systems. Energy storage is by lead-acid batteries and an H2 system (electrolyzer, H2 cylinders and Fuel Cell). The energy demand is residential in nature, consisting of a base load plus others that can be disconnected or moved to other times of the day within a demand response program. Based on the experimental data from each of the LabDER renewable generation and storage systems, a micro-grid operating model was developed in MATLAB(C) to simulate energy flows and their interaction with the grid. The proposed optimization algorithm seeks the minimum hourly cost of the energy consumed by the demand and the maximum use of renewable resources, using the minimum computational resources. The simulation results of the experimental micro-grid are given with seasonal data and the benefits of using the algorithm are pointed out.Acevedo-Arenas, CY.; Correcher Salvador, A.; Sánchez-Diaz, C.; Ariza-Chacón, HE.; Alfonso-Solar, D.; Vargas-Salgado, C.; Petit-Suarez, JF. (2019). MPC for optimal dispatch of an AC-linked hybrid PV/wind/biomass/H2 system incorporating demand response. Energy Conversion and Management. 186:241-257. https://doi.org/10.1016/j.enconman.2019.02.044S24125718

LC3: un modèle spatial et sémantique pour découvrir la connaissance dans les jeux de données géospatiaux

National audienceIl est nécessaire pour les gérants de territoires d’avoir un aperçu des connaissances actuelles et de l’évolution de certaines caractéristiques de la biosphère. Les outils de télédétection enregistrent une grande quantité d’informations liées à la couverture terrestre permettant l’étude de processus dynamiques. Toutefois, le volume des jeux de données nécessite de nouveaux outils pour identifier des motifs et extraire de la connaissance. Nous proposons un modèle capable de découvrir la connaissance sur des données parcellaires et permettant l’analyse des phénomènes dynamiques à l’aide de données temporelles, spatiales et thématiques. Le modèle est appelé Land Cover Change Continuum (LC3) et se base sur les technologies du Web sémantique pour permettre une représentation accrue du contexte de l’environnement géospatial et fournir des résultats d’analyses proches de ceux des experts du domaine via des opérations de raisonnement automatique. En définitive, ce modèle permet d’améliorer notre compréhension de la dynamique des territoires

Using Semantic Web Technologies to Follow the Evolution of Entities in Time and Space

International audienceIn this paper we present the "continuum model". Our work follows a "perdurantism" approach and is designed to handle dynamic phenomena extending the 4D-fluent with the use of semantic web technologies. In our approach we represent dynamic entities as constituted by timeslices each with semantic, geometric, temporal and identity components. Our model is able to link the diverse representations of an entity and allows the inference of qualitative information from quantitative one. The inference results are later added to the ontology in order to improve knowledge about the phenomenon. The model has been implemented using OWL and SWRL. Our preliminary results are promising and we plan to further develop the model in the near future to increase the suitable data sources

Reasoning with Vague Spatial Information from Upper Mesopotamia (2000BC)

International audienceConcepts such as near, far, south of, etc., are by its own nature vague. However, they are quite common in human language. In the case of historical records, these concepts are often the only source of information regarding the position of ancient places whose exact location has been lost. In our research, we use digitized written records from Upper Mesopotamia (2000BC) from the HIGEOMES project. Our goal is to provide better understanding of the location of places, based on the analysis of spatial statements. In our approach, we analyse cardinal statements between places with known location. Using this information we construct a probabilistic function representing the vagueness of cardinal statements. For each place with unknown position, we combine multiple vague statements using our probabilistic function in order to limit the possible search area. At this point, our results look promising. In the near future, and thanks to new data, such as proximity statements as provided by the HIGEOMES project, we expect to improve our results

A Semantic Web Approach for Geodata Discovery

Abstract. Currently, vast amounts of geospatial information are offered through OGC’s services. However this information has limited formal semantics. The most common method to search for a dataset consists in matching keywords to metadata elements. By adding semantics to available descriptions we could use modern inference and reasoning mechanisms currently available in the Semantic Web. In this paper we present a novel architecture currently in development in which we use state of the art triplestores as the backend of a CSW service. In our approach, each metadata record is considered an instance of a given class in a domain ontology. Our architecture also adds a spatial dataset of features with toponym values. These additions allow us to provide advance searches based on 1) Instance to class matching, 2) Class to class subsuming relationships, 3) Spatial relationships resulting from comparing the bounding box of a metadata record with our toponym spatial dataset