CartAGen: an Open Source Research Platform for Map Generalization

International audienceAutomatic map generalization is a complex task that is still a research problem and requires the development of research prototypes before being usable in productive map processes. In the meantime, reproducible research principles are becoming a standard. Publishing reproducible research means that researchers share their code and their data so that other researchers might be able to reproduce the published experiments, in order to check them, extend them, or compare them to their own experiments. Open source software is a key tool to share code and software, and CartAGen is the first open source research platform that tackles the overall map generalization problem: not only the building blocks that are generalization algorithms, but also methods to chain them, and spatial analysis tools necessary for data enrichment. This paper presents the CartAGen platform, its architecture and its components. The main component of the platform is the implementation of several multi-agent based models of the literature such as AGENT, CartACom, GAEL, CollaGen, or DIOGEN. The paper also explains and discusses different ways, as a researcher, to use or to contribute to CartAGen

Automated Generalisation Results Using the Agent-Based Platform CartAGen

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ScaleMaster2.0: A ScaleMaster Extension to Monitor Automatic Multi-Scales Generalisations

International audienceLittle by little, the co-existing geographical datasets are integrated into Multi-Representation Databases, where the datasets represent different level of detail , or different point of views for the same geographical features. The ScaleMaster model from Brewer and Buttenfield (2007) allows formalising how to choose the features to map from the different datasets. The paper proposes an extension of the ScaleMaster model that drives automatic generalisation rather than guidelines for manual mapmaking. This ScaleMaster2.0 has been implemented and is tested for a use case with real data

Enhancing building footprints with squaring operations

Whatever the data source, or the capture process, the creation of a building footprint in a geographical dataset is error prone. Building footprints are designed with square angles, but once in a geographical dataset, the angles may not be exactly square. The almost-square angles blur the legibility of the footprints when displayed on maps, but might also be propagated in further applications based on the footprints, e.g., 3D city model construction. This paper proposes two new methods to square such buildings: a simple one, and a more complex one based on nonlinear least squares. The latter squares right and flat angles by iteratively moving vertices, while preserving the initial shape and position of the buildings. The methods are tested on real datasets and assessed against existing methods, proving the usefulness of the contribution. Direct applications of the squaring transformation, such as OpenStreetMap enhancement, or map generalization are presented

A framework to formalize multi-scales land-use generalization in the ScaleMaster 2.0

shortInternational audienceThis article presents a general framework to formalize the generalization of land-use coverages within the ScaleMaster2.0 model, a multi-scale automatic generalization system, developed to facilitate smooth transitions (i.e. cartographic continuum) between level of details in a multi-representation database (MRDB). The article describes the land-use simplification method developed, the strategy used to manage generalization on large areas, and the way to formalize multi-scales land-use generalization rules in the ScaleMaster2.0. Finally, an experiment is provided on two da-tasets to illustrate the proposition: a land-use coverage in the area of Dakar (Senegal) and a map of sedimentary floor off the coast of Brittany (France)

Cartographic generalization

This short paper gives a subjective view on cartographic generalization, its achievements in the past, and the challenges it faces in the future

Progressive Block Graying and Landmarks Enhancing as Intermediate Representations between Buildings and Urban Areas

workshopInternational audienceGeovisualization applications that allow the navigation between maps at different scales while zooming in and out often provide no smooth transition between the individual building level of abstraction and the representation of whole urban areas as polygons. In order to reduce the cognitive load of the user, we seek to add intermediate zoom levels with intermediate and progressive abstractions between buildings and urban areas. This paper proposes a method based on progressive block graying while enhancing building landmarks, to derive these intermediate representations from the individual buildings. Block graying is based on an automatic building classification, and a multiple criteria decision technique to infer inner city blocks. The landmarks identification relies on machine learning and several criteria based on geometry and spatial relations. The method is tested with real cartographic data between the 1:25k (with individual buildings) and the 1:100k scale (with urban areas): transitions with one, two, or three intermediate representations are derived and tested

Bicriteria Aggregation of Polygons via Graph Cuts

We present a new method for the task of detecting groups of polygons in a given geographic data set and computing a representative polygon for each group. This task is relevant in map generalization where the aim is to derive a less detailed map from a given map. Following a classical approach, we define the output polygons by merging the input polygons with a set of triangles that we select from a constrained Delaunay triangulation of the input polygons\u27 exterior. The innovation of our method is to compute the selection of triangles by solving a bicriteria optimization problem. While on the one hand we aim at minimizing the total area of the outputs polygons, we aim on the other hand at minimizing their total perimeter. We combine these two objectives in a weighted sum and study two computational problems that naturally arise. In the first problem, the parameter that balances the two objectives is fixed and the aim is to compute a single optimal solution. In the second problem, the aim is to compute a set containing an optimal solution for every possible value of the parameter. We present efficient algorithms for these problems based on computing a minimum cut in an appropriately defined graph. Moreover, we show how the result set of the second problem can be approximated with few solutions. In an experimental evaluation, we finally show that the method is able to derive settlement areas from building footprints that are similar to reference solutions

Prise en compte des dépendances entre données thématiques utilisateur et données topographiques lors d’un changement de niveau de détail

With the large availability of reference topographic data, creating geographic data is not exclusive to experts of geographic information any more. More and more users rely on reference data to create their own data, hereafter called thematic data. Reference data then play the role of support for thematic data. Thematic data make sense by themselves, but even more by their relations with topographic data. Not taking into account the relations between thematic and topographic data during processes that modify the former or the latter may cause inconsistencies, especially for processes that are related to changing the level of detail. The objective of this thesis is to define a methodology to preserve the consistency between thematic and topographic when the level of detail is modified. This thesis focuses on the adaptation of thematic data after a modification of topographic data: we call this process thematic data migration. We first propose a model for the migration of punctual thematic data hosted by a network. This model is composed of: (1) a model to describe the referencing of thematic data on topographic data using spatial relations (2) a method to re-locate thematic data based on these relations. The approach consists in identifying the expected final relations according to the initial relations and the modifications of topographic data between the initial and the final state. The thematic data are then re-located using a multi-criteria method in order to satisfy, as much as possible, the expected relations. An implementation is presented on toy problems and on a real use case provided by a French public authority in charge of road network management. The extension of the proposed model to take into account the relations for other applications than thematic data migration is also discussedAvec l'importante disponibilité de données topographiques de référence, la création des données géographiques n'est plus réservée aux professionnels de l'information géographique. De plus en plus d'utilisateurs saisissent leurs propres données, que nous appelons données thématiques, en s'appuyant sur ces données de référence qui jouent alors le rôle de données support. Les données thématiques ainsi saisies font sens en tant que telles, mais surtout de par leurs relations avec les données topographiques. La non prise en compte des relations entre données thématiques et topographiques lors de traitements modifiant les unes ou les autres peut engendrer des incohérences, notamment pour les traitements liés au changement de niveau de détail. L'objectif de la thèse est de définir une méthodologie pour préserver la cohérence entre les données thématiques et topographiques lors d'un changement de niveau de détail. Nous nous concentrons sur l'adaptation des données thématiques suite à une modification des données topographiques, processus que nous appelons migration des données thématiques. Nous proposons d'abord un modèle pour la migration de données thématiques ponctuelles sur réseau composé de : (1) un modèle pour décrire le référencement des données thématiques sur les données topographiques par des relations spatiales (2) une méthode de relocalisation basée sur ces relations. L'approche consiste à identifier les relations finales attendues en fonction des relations initiales et des changements sur les données topographiques entre les états initial et final. La relocalisation est alors effectuée grâce à une méthode multicritère de manière à respecter au mieux les relations attendues. Une mise en œuvre est présentée sur des cas d'étude jouets et sur un cas réel fourni par un service de l'Etat gestionnaire de réseau routier. Nous discutons enfin l'extension du modèle proposé pour traiter la prise en compte des relations pour d'autres applications que la migration de données thématique