Passability maps are cartographic studies that are generally used by commanders in order to plan military operations. Pursuant to standardisation documents, they are developed by marking passable, ...hardly passable and impassable (GO, SLOW GO and NO GO) areas. This article presents a methodology for the generalisation of passability maps that are created automatically. For this purpose, artificial neural networks (ANN) were used, and, specifically, a multilayer perceptron. Teaching the network consisted in presenting the neural network examples of manual generalisation of source maps. The paper describes the manner of preparing teaching data to train artificial neural networks and their implementation, which leads to the creation of the resulting maps. The maps were generated in multiple input configurations of teaching data, which allowed us to conduct comparisons of the obtained maps. Areas of various levels of passability generalised manually by the operator were compared to maps generated by the ANN. In order to test the consistency of maps, Moran's I spatial autocorrelation coefficient was determined. The conducted tests allowed us to obtain the optimum parameters of the generalisation process. The proposed methodology is fully automated and may be applied to any source data in any chosen area.
The development of web services technology and standardization of spatial data usage have initiated the process of automatization of cartographic generalization on the Internet.There are two ways ...by which web supported cartographic generalization can be accomplished (Foerster 2010):1. Limited control of data representation (selection of layers and symbolization)2. Complete control of the generalization process (usage of all generalization procedures with selection of specific parameters)The first option is for users that are amateurs in cartographic generalization, and it enables them to have limited control over the shaping of map content. The second option is intended to be used by experts in cartographic generalization which would support development of automated systems for cartographic generalization.
This paper introduces a new hierarchy for cartographic generalisation processes, applied in street networks. The aims of implementing this hierarchy are to emphasise on significant street features, ...and to provide more free spaces between street features. The hierarchy is obtained from the functional classes of the features and four centrality measures in a street network, i.e. betweenness, reach, straightness and closeness extracted from a primary graph. The values of centrality measures change in every zoom level by calculating a radius parameter, which depends on the users' field of view. The coefficients for the measures are constructed using a decision-making technique called fuzzy analytical hierarchy process (FAHP). The weights for each of the centrality measures are computed and normalised to form the proposed hierarchy. The hierarchy is applied and used later in the thinning process to omit insignificant features from the street network in medium scales.
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.
Detection and characterisation of spatial patterns is crucial for cartographic generalisation since it entails preserving the patterns as much as possible within scale limits. Building alignments are ...commonly confronted patterns in the topographic maps/databases. They are perceptually recognised in accordance with relevant Gestalt factors, namely proximity, similarity, common orientation and continuity. This study is concentrated on how to characterise building alignments detected by automated or manual methods. To this end, new measures based on Delaunay triangulation and regression line/curve are established to correspond to the Gestalt factors. The relationship between the measures and Gestalt principles has been illustrated with a decision tree. An index value was computed by total sum of measures’ values to compare and order alignments from quality aspect. Additionally, a supervised classification was performed with C4.5 algorithm thus a decision tree was obtained to be able to both associate the quality categories with the measure values and automatically assign alignments into a quality class. The findings demonstrate that proposed measures are substantially effective for representing Gestalt factors. The proposed methods can potentially enhance and ease the characterisation of building alignments in topographic map generalisation.
► We propose a method to automatically evaluate the quality of control knowledge used for cartographic generalisation. ► Our method consists in analysing the system’s execution logs. ► Our method ...allows detecting defective elements of knowledge. ► Our method uses the ELECTRE TRI method for evaluating the knowledge global quality.
The development of interactive map websites increases the need of efficient automatic cartographic generalisation. The generalisation process, which aims at decreasing the level of details of geographic data in order to produce a map at a given scale, is extremely complex. A classical method for automating the generalisation process consists in using a heuristic tree-search strategy. This type of strategy requires having high quality control knowledge (heuristics) to guide the search for the optimal solution. Unfortunately, this control knowledge is rarely perfect and its evaluation is often difficult. Yet, this evaluation can be very useful to manage knowledge and to determine when to revise it. The objective of our work is to offer an automatic method for evaluating the quality of control knowledge for cartographic generalisation based on a heuristic tree-search strategy. Our diagnosis method consists in analysing the system’s execution logs, and in using a multi-criteria analysis method for evaluating the knowledge global quality. We present an industrial application as a case study using this method for building block generalisation and this experiment shows promising results.
The paper describes processing methods for portraying forest areas on maps utilizing point symbols. The forest map design is based on the use of individual tree data, which is detected from airborne ...laser scanning data and colour-infrared orthophotos. Several generalisation and symbolisation approaches have been tested in order to use the tree data set for cartographic purposes. Our generalisation method differentiates between trees in dense forests and tree structures in open areas, such as isolated trees, tree groups, tree rows and sparsely scattered trees. The tree symbols are integrated visually with the other map content. The results show that the production of attractive and useful maps requires an advanced generalisation method due to the massive amount of tree objects extracted from the laser scanning data as well as a generalisation level and a symbol type for the trees that are carefully chosen according to the map scale. Furthermore, sophisticated visualisation methods are needed for composing the maps. The created maps are part of a project that aims at supporting outdoor activities using multi-scale maps as part of a multi-publishing service.
The automation of cartographic map production is still an important research field in Geographical Information Systems (GIS). With the increasing development of monitoring and decision-aid systems ...either on computer networks or wireless networks, efficient methods are needed to visualise geographical data while respecting some application constraints (accuracy, legibility, security, etc.). This paper introduces a B-spline snake model to deal with the current operators involved in the cartographic generalisation process of lines. This model enables us to perform those operators with a continuous approach. In order to avoid local conflicts such as intersections or self-intersections, the consistency of the lines is checked and discrete operations such as segment removal are performed during the process. We apply the method to map production in the highly constrained domain of maritime navigation systems. Experimental results of marine chart generalisation yield some discussions about generalisation robustness and quality.
Humans frequently have to face complex problems. A classical approach to solve them is to search the solution by means of a trial and error method. This approach is often used with success by ...artificial systems. However, when facing highly complex problems, it becomes necessary to introduce control knowledge (heuristics) in order to limit the number of trials needed to find the optimal solution. Unfortunately, acquiring and maintaining such knowledge can be fastidious. In this paper, we propose an automatic knowledge revision approach for systems based on a trial and error method. Our approach allows to revise the knowledge off-line by means of experiments. It is based on the analysis of solved instances of the considered problem and on the exploration of the knowledge space. Indeed, we formulate the revision problem as a search problem: we search the knowledge set that maximises the performances of the system on a sample of problem instances. Our knowledge revision approach has been implemented for a real-world industrial application: automated cartographic generalisation, a complex task of the cartography domain. In this implementation, we demonstrate that our approach improves the quality of the knowledge and thus the performance of the system.
The International Union for Conservation of Nature (IUCN) considers that a decrease in the area of occupancy (AOO) is a critical criterion for listing a species as rare, endemic or threatened. ...However, methods for the accurate measurement of changes in the area of occupancy are relatively limited, and existing methods are influenced by spatial scale and sampling methods. To overcome such cartographic problems, different cartographic methods were proposed in this study and implemented in a free and open source GIS library. A single species (Helianthemum caput-felis Boiss.), which is distributed in many countries of the western Mediterranean, was used as a case study. This plant is threatened and protected because its preferred habitat is near the sea where urban growth is high in the Mediterranean regions. Intensive field work was initially conducted to create a geodatabase with more than 13,000 GPS points. Cartographic methods were then applied to the geodatabase to obtain AOO measurements at different scales to support sustainable urban planning. Based on positive experiences with the use of the programming library, it is believed that these open source tools can be customised and extended to other similar biogeographic studies that require data analysis at different scales.
► We propose a method for calculating the area of occupancy for endangered species. ► The developed software is available as a FOSS library and two user interfaces. ► We modified an existing generalization algorithm to adjust it to our study area.
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