Anne Ruas

A method for building displacement in automated map generalisation

The automation of the map design process through map generalisation continues to be a challenging area of research. It is acknowledged that a diverse range of techniques are applied during the process of map generalisation and these have been mirrored by the creation of a range of algorithms that mimic these discrete operations (such as typification, aggregation, selection). This paper discusses in detail one such algorithm that resolves conflict among objects through displacement. Perhaps more critical than the algorithm itself, is the stage prior to the application of displacement (identification, modelling), and the phase after application (the evaluation). It is argued that these two stages are absolutely critical to the successful design of automated systems. The paper begins with a review of other approaches to displacement and then describes a methodology that encompasses detection, resolution through displacement, and evaluation. This methodology has been implemented in Stratege, an object oriente...

The CartACom model: transforming cartographic features into communicating agents for cartographic generalisation

Our research is concerned with automated generalisation of topographic vector databases in order to produce maps. This article presents a new, agent-based generalisation model called CartACom (Cartographic generalisation with Communicating Agents), dedicated to the treatment of areas of low density but where rubber sheeting techniques are not sufficient because some eliminations or aggregations are needed. In CartACom, the objects of the initial database are modelled as agents, that is, autonomous entities, that choose and apply generalisation algorithms to themselves in order to increase the satisfaction of their constraints as much as possible. The CartACom model focuses on modelling and treating the relational constraints, defined as constraints that concern a relation between two objects. In order to detect and assess their relational constraints, the CartACom agents are able to perceive their spatial surroundings. Moreover, to make the good generalisation decisions to satisfy their relational constraints, they are able to communicate with their neighbours using predefined dialogue protocols. Finally, a hook to another agent-based generalisation model – AGENT – is provided, so that the CartACom agents can handle not only their relational constraints but also their internal constraints. The CartACom model has been applied to the generalisation of low-density, heterogeneous areas like rural areas, where the space is not hierarchically organised. Examples of results obtained on real data show that it is well adapted for this application.

Knowledge formalization for vector data matching using belief theory

Nowadays geographic vector data is produced both by public and private institutions using well defined specifications or crowdsourcing via Web 2.0 mapping portals. As a result, multiple representations of the same real world objects exist, without any links between these different representations. This becomes an issue when integration, updates, or multi-level analysis needs to be performed, as well as for data quality assessment. In this paper a multi-criteria data matching approach allowing the automatic definition of links between identical features is proposed. The originality of the approach is that the process is guided by an explicit representation and fusion of knowledge from various sources. Moreover the imperfection (imprecision, uncertainty, and incompleteness) is explicitly modeled in the process. Belief theory is used to represent and fuse knowledge from different sources, to model imperfection, and make a decision. Experiments are reported on real data coming from different producers, having different scales and either representing relief (isolated points) or road networks (linear data).

Conception of a GIS-Platform to simulate urban densification based on the analysis of topographic data

The aim of our research is to analyze the evolution of urbanization and to simulate it on specific areas. We focus on the evolution between 1950 and now. We analyse the densification by means of comparing temporal topographic data bases created from existing topographic data base and maps and photo from 1950. In this paper we present how a simulation works - which input data are used, which functions are used to densify the space and how the simulation works, is tuned and run - the densification method for each urban block illustrated with results, the method used during the project to build the required knowledge for simulation and we conclude and present the main research perspectives. The methods are implemented on a dedicated open source software named GeOpenSim.

Optimal Deployment of Wireless Sensor Networks for Air Pollution Monitoring

Recently, air pollution monitoring emerges as a main service of smart cities because of the increasing industrialization and the massive urbanization. Wireless sensor networks (WSN) are a suitable technology for this purpose thanks to their substantial benefits including low cost and autonomy. Minimizing the deployment cost is one of the major challenges in WSN design, therefore sensors positions have to be carefully determined. In this paper, we propose two integer linear programming formulations based on real pollutants dispersion modeling to deal with the minimum cost WSN deployment for air pollution monitoring. We illustrate the concept by applying our models on real world data, namely the Nottingham City street lights. We compare the two models in terms of execution time and show that the second flow based formulation is much better. We finally conduct extensive simulations to study the impact of some parameters and derive some guidelines for efficient WSN deployment for air pollution monitoring.

GéoPeuple: The Creation and the Analysis of Topographic and Demographic Data Over 200 Years

The aim of the GeoPeuple project is to analyze the raise of population from the late twenty-eight to the early twenty-first century according to the topographic elements that characterize each commune (administrative area conceptually close to municipality): the infrastructure, the equipment, the settlements as well as the natural component such as the relief. We wish to learn more about the history of each commune but also to identify stylized facts if any. In order to understand the evolution of the population at the commune level, a first web interface has been proposed. It allows a better understanding of the aggregation processes. Then we built topographic vector data bases from old maps which required the understanding of the map content as well as a long process of interactive digitalization. To start the analysis step, we developed indices that characterize each commune. At least the analysis is performed: it is based first on the classification of each commune over time. Current study is focusing on the analysis of transitions over time.

Symbolization and Generalization to Map Water Pipe Data Flow and Water Quality at Different Scales

Mapping drinking water flow is a real challenge not only to detect water leaks but also to control the quality of the water. In France, 900,000 km of water pipe serves 99% of the population. A recent law imposes the mapping of these pipelines on a known geographical system with a planar positional accuracy from 0.4 to 1.5 m according to the age and type of the pipeline. Wireless sensors and models based on computational fluid mechanics (CFD) allow to study flow and to reconstruct parameters such as velocity, pressure and a chemical concentration at each point. This information can be used to detect leaks and to control the concentration of chlorine or other chemical products. However, this information is not easy to map on GIS due to the small width of water pipe and the very high quantity of points necessary for data flow computation. In this research work, we propose solutions to map this information at different levels of detail with other information such as roads and buildings. We first propose to use area symbols instead of punctual symbols to improve zoom-in visual effects. We also propose to generalize initial water data for zoom-out processes. We use the axis of the water pipe as basic geometry and we segment it. We then compute a generalized value of pressure, velocity or chemical concentration for each segment with specific function adapted to the property we wish to study. We propose a conceptual data schema that describes the required information to map this data at different levels of detail. The solution has been fully implemented on experimental data and illustrated by means of a dedicated web mapping that proposes a set of GIS functions such as the selection of the data, zooming functions but also the animation to see the propagation of a chemical product in the water pipe.

Preservation and Modification of Relations Between Thematic and Topographic Data Throughout Thematic Data Migration Process

Nowadays, users often use topographic data to reference their own thematic data. When reference data are updated or if the user wants to replace the reference, the thematic data have to be processed in order to maintain data consistency. We call this processing thematic data migration. This paper proposes an updated version of a previously proposed thematic data migration process, which includes the case where the relations between thematic and topographic data have to be modified between the initial and the final state. A model to describe the relations and their modifications is proposed. A multi-criteria decision method is used to relocalise the thematic data on the topographic data guided by the described relations. The whole process is illustrated on a running example, on which obtained results are presented and discussed.

Models and Methods to Represent and Explore Phenomena on GIS

Many models have been developed by experts to compute a specific phenomenon from a set of measures. In France for example the model named Saturne, based on fluid dynamic (CFD), allows to study either the effect of a phenomenon on the environment (such as the pollution on a district) or the effect of the environment on a phenomenon (such as the impact of buildings on the local rising of temperature). These models are of prime importance today. They use and produce geographical information. In this context, we can question the role of GIS and cartography to map phenomena. The first easy diagnostic is that the work flow between measures and the representation of phenomena is sometime weak, even thought all the technology exists today to propose efficient solutions. The other diagnostic is that the representation of phenomena is often limited to a DPM (a digital phenomenon model), inspired by DTM and using DTM format, to overlay the representation of phenomena on the geographical space. But phenomena should be represented in better way: they are not constant in Z, they vary in time, and moreover their impacts depend on the duration and on the subject located in a specific place. In this paper we identify the workflow from the measure to its representation, we identify the necessary information to represent topographical data, a 3D phenomenon (such as noise or chemical pollution) and the effect of phenomena on alive ‘bodies’ (such as a baby, a child, a person working during the night, a person having breathing difficulties, a cat or even a plant). We first propose a data model including the description of phenomena episode, the description of the different ways to represent graphically this phenomenon in quantitative and qualitative ways. Then we propose some graphical solutions that could enrich GIS software to improve our capacity of representing phenomena in 2D or 3D environment. To illustrate our ideas we take the example from the Immanent project in which we were involved.

Carte de Kohonen et classification ascendante hiérarchique pour l’analyse de données géohistoriques

Nous presentons dans ce papier une methode de classification de donnees geohistoriques depuis la fin du XVIIIe siecle jusqu’a nos jours. La methode de classification proposee, qui a pour but de caracteriser l’espace en fonction de la topographie, est une methode mixte combinant la carte de Kohonen et la classification ascendante hierarchique (CAH). La carte de Kohonen est utilisee pour organiser les donnees d’entree en zones homogenes, tandis que la CAH est utilisee pour grouper ces zones homogenes en classes afin d’identifier les communes ayant des caracteristiques semblables. La methode est illustree sur la zone de Grenoble a trois epoques, a savoir la fin du XVIIIe , la fin du XIXe et le debut du XXIe siecle.