Journal ArticleDOI
Use of Artificial Neural Networks for Selective Omission in Updating Road Networks
TLDR
In this article, the use of a back propagation neural network (BPNN) and a self-organizing map (SOM) for selective omission in a road network was investigated.Abstract:
An important problem faced by national mapping agencies is frequent map updates. An ideal solution is only updating the large-scale map with other smaller scale maps undergoing automatic updates. This process may involve a series of operators, among which selective omission has received much attention. This study focuses on selective omission in a road network, and the use of an artificial neural network (i.e. a back propagation neural network, BPNN). The use of another type of artificial neural network (i.e. a self-organizing map, SOM) is investigated as a comparison. The use of both neural networks for selective omission is tested on a real-life road network. The use of a BPNN for practical application road updating is also tested. The results of selective omission are evaluated by overall accuracy. It is found that (1) the use of a BPNN can adaptively determine which and how many roads are to be retained at a specific scale, with an overall accuracy above 80%; (2) it may be hard to determine wh...read more
Citations
More filters
Journal ArticleDOI
Information from imagery: ISPRS scientific vision and research agenda
Jun Chen,Ian Dowman,Songnian Li,Zhilin Li,Marguerite Madden,Jon P. Mills,Nicolas Paparoditis,Franz Rottensteiner,Monika Sester,Charles K. Toth,John Trinder,Christian Heipke +11 more
TL;DR: The significant challenges currently facing ISPRS and its communities are examined, such as providing high-quality information, enabling advanced geospatial computing, and supporting collaborative problem solving.
Journal ArticleDOI
Machine Learning Classification of Buildings for Map Generalization
TL;DR: Although elimination is a direct part of the proposed process, generalization operations, such as simplification and aggregation of polygons, must still be performed for buildings classified as retained and aggregated, and these algorithms can be used for building classification and can serve as preparatory steps for building generalization.
Journal ArticleDOI
Multilane roads extracted from the OpenStreetMap urban road network using random forests
TL;DR: A machine‐learning‐based approach is proposed, in which the road networks are first converted from lines to polygons, and various geometric descriptors are used to train a random forest classifier and identify the candidates.
Journal ArticleDOI
A map‐algebra‐based method for automatic change detection and spatial data updating across multiple scales
TL;DR: This study examines the various possible changes from different perspectives, such as the reasons for their occurrence, the forms in which they manifest, and their effects on output, and applies map algebra theory to establish a cartographic model for updating polygonal building data.
References
More filters
Journal ArticleDOI
The Network Analysis of Urban Streets: A Primal Approach:
TL;DR: This paper introduces multiple centrality assessment (MCA), a methodology for geographic network analysis, which is defined and implemented on four 1-square-mile urban street systems and shows that, in the MCA primal approach, some centrality indices nicely capture the ‘skeleton’ of the urban structure that impacts so much on spatial cognition and collective behaviours.
Journal ArticleDOI
Centrality measures in spatial networks of urban streets
TL;DR: The results indicate that a spatial analysis based on a set of four centrality indices allows an extended visualization and characterization of the city structure and has a certain capacity to distinguish different classes of cities.
Journal ArticleDOI
The Principles of Selection
F. Töpfer,W. Pillewizer +1 more
TL;DR: The fundamental of cartographic generalisation, the reduction of the amount of information which can be shown on a map in relation to reduction in scale, is examined and the introduction of two constants to represent symbolic exaggeration and symbolic form is introduced.
Journal ArticleDOI
A Structural Approach to the Model Generalization of an Urban Street Network
Bin Jiang,Christophe Claramunt +1 more
TL;DR: This paper proposes a novel generalization model for selecting characteristic streets in an urban street network using graph principles where vertices represent named streets and links represent street intersections and centrality measures are introduced to qualify the status of each individual vertex within the graph.