Qualitative Spatial Reasoning for High-Resolution Remote Sensing Image Analysis

International audienceHigh resolution remote sensing images allow us to access new kinds of information. Classical techniques for image analysis, such as pixel-based classifications or region-based segmentations, do not allow to fully exploit the richness of this kind of images. Indeed, for many applications, we are interested in complex objects which can only be identified and analysed by studying the relationships between the elementary objects which compose them. In this paper, the use of a spatial reasoning technique called Region Connection Calculus for the analysis of high resolution remote sensing images is presented. A graph based representation of the spatial relationships between the regions of an image is used within a graph-matching procedure in order to implement an object detection algorithm

OGRS2012 Symposium Proceedings

Do you remember the Open Source Geospatial Research and Education Symposium (OGRS) in Nantes? "Les Machines de l’Île", the Big Elephant, the "Storm Boat" with Claramunt, Petit et al. (2009), and "le Biniou et la Bombarde"? A second edition of OGRS was promised, and that promise is now fulfilled in OGRS 2012, Yverdon-les-Bains, Switzerland, October 24-26, 2012. OGRS is a meeting dedicated to sharing knowledge, new solutions, methods, practices, ideas and trends in the field of geospatial information through the development and the use of free and open source software in both research and education. In recent years, the development of geospatial free and open source software (GFOSS) has breathed new life into the geospatial domain. GFOSS has been extensively promoted by FOSS4G events, which evolved from meetings which gathered together interested GFOSS development communities to a standard business conference. More in line with the academic side of the FOSS4G conferences, OGRS is a rather neutral forum whose goal is to assemble a community whose main concern is to find new solutions by sharing knowledge and methods free of software license limits. This is why OGRS is primarily concerned with the academic world, though it also involves public institutions, organizations and companies interested in geospatial innovation. This symposium is therefore not an exhibition for presenting existing industrial software solutions, but an event we hope will act as a catalyst for research and innovation and new collaborations between research teams, public agencies and industries. An educational aspect has recently been added to the content of the symposium. This important addition examines the knowledge triangle - research, education, and innovation - through the lens of how open source methods can improve education efficiency. Based on their experience, OGRS contributors bring to the table ideas on how open source training is likely to offer pedagogical advantages to equip students with the skills and knowledge necessary to succeed in tomorrow’s geospatial labor market. OGRS brings together a large collection of current innovative research projects from around the world, with the goal of examining how research uses and contributes to open source initiatives. By presenting their research, OGRS contributors shed light on how the open-source approach impacts research, and vice-versa. The organizers of the symposium wish to demonstrate how the use and development of open source software strengthen education, research and innovation in geospatial fields. To support this approach, the present proceedings propose thirty short papers grouped under the following thematic headings: Education, Earth Science & Landscape, Data, Remote Sensing, Spatial Analysis, Urban Simulation and Tools. These papers are preceded by the contributions of the four keynote speakers: Prof Helena Mitasova, Dr Gérard Hégron, Prof Sergio Rey and Prof Robert Weibel, who share their expertise in research and education in order to highlight the decisive advantages of openness over the limits imposed by the closed-source license system

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