Constrained set-up of the tGAP structure for progressive vector data transfer

A promising approach to submit a vector map from a server to a mobile client is to send a coarse representation first, which then is incrementally refined. We consider the problem of defining a sequence of such increments for areas of different land-cover classes in a planar partition. In order to submit well-generalised datasets, we propose a method of two stages: First, we create a generalised representation from a detailed dataset, using an optimisation approach that satisfies certain cartographic constraints. Second, we define a sequence of basic merge and simplification operations that transforms the most detailed dataset gradually into the generalised dataset. The obtained sequence of gradual transformations is stored without geometrical redundancy in a structure that builds up on the previously developed tGAP (topological Generalised Area Partitioning) structure. This structure and the algorithm for intermediate levels of detail (LoD) have been implemented in an object-relational database and tested for land-cover data from the official German topographic dataset ATKIS at scale 1:50 000 to the target scale 1:250 000. Results of these tests allow us to conclude that the data at lowest LoD and at intermediate LoDs is well generalised. Applying specialised heuristics the applied optimisation method copes with large datasets; the tGAP structure allows users to efficiently query and retrieve a dataset at a specified LoD. Data are sent progressively from the server to the client: First a coarse representation is sent, which is refined until the requested LoD is reached

Constrained tGAP for generalisation between scales: the case of Dutch topographic data

This article presents the results of integrating large- and medium-scale data into a unified data structure. This structure can be used as a single non-redundant representation for the input data, which can be queried at any arbitrary scale between the source scales. The solution is based on the constrained topological Generalized Area Partition (tGAP), which stores the results of a generalization process applied to the large-scale dataset, and is controlled by the objects of the medium-scale dataset, which act as constraints on the large-scale objects. The result contains the accurate geometry of the large-scale objects enriched with the generalization knowledge of the medium-scale data, stored as references in the constraint tGAP structure. The advantage of this constrained approach over the original tGAP is the higher quality of the aggregated maps. The idea was implemented with real topographic datasets from The Netherlands for the large- (1:1000) and medium-scale (1:10,000) data. The approach is expected to be equally valid for any categorical map and for other scales as well

A ZONE-BASED ITERATIVE BUILDING DISPLACEMENT METHOD THROUGH THE COLLECTIVE USE OF VORONOI TESSELLATION, SPATIAL ANALYSIS AND MULTICRITERIA DECISION MAKING

An iterative displacement method working based on generalisation zones is proposed as a part of contextual  building generalisation in topographic map production at medium scales. Displacement is very complicated operation since a compromise ought to be found between several conflicting criteria. Displacement requirement mainly arises from the violation of minimum distances imposed bygraphic limits after the enlargement of map objects for target scale. It is also important to maintain positional accuracy within scale limits and to propagate the changes to the related neighbouring objects by preserving spatial configurations asfar as possible. In the proposed method, first it is decided where and when to initiate building displacement based on spatial analysis in the generalisation zones created for building clusters in the blocks. Secondly, relevant criteria are defined to control the displacement. Finally displacement candidate and vector are decided by means of Voronoi tessellation, spatial analysis techniques and combined multiple criteria (i.e. displacement controls) in each iteration. The evaluation of the findings demonstrates that this method is largely effective in zone-based displacement of buildings

Automated processing for map generalization using web services

In map generalization various operators are applied to the features of a map in order to maintain and improve the legibility of the map after the scale has been changed. These operators must be applied in the proper sequence and the quality of the results must be continuously evaluated. Cartographic constraints can be used to define the conditions that have to be met in order to make a map legible and compliant to the user needs. The combinatorial optimization approaches shown in this paper use cartographic constraints to control and restrict the selection and application of a variety of different independent generalization operators into an optimal sequence. Different optimization techniques including hill climbing, simulated annealing and genetic deep search are presented and evaluated experimentally by the example of the generalization of buildings in blocks. All algorithms used in this paper have been implemented in a web services framework. This allows the use of distributed and parallel processing in order to speed up the search for optimized generalization operator sequence

A multi-agent system for on-the-fly web map generation and spatial conflict resolution

Résumé Internet est devenu un moyen de diffusion de l’information géographique par excellence. Il offre de plus en plus de services cartographiques accessibles par des milliers d’internautes à travers le monde. Cependant, la qualité de ces services doit être améliorée, principalement en matière de personnalisation. A cette fin, il est important que la carte générée corresponde autant que possible aux besoins, aux préférences et au contexte de l’utilisateur. Ce but peut être atteint en appliquant les transformations appropriées, en temps réel, aux objets de l’espace à chaque cycle de génération de la carte. L’un des défis majeurs de la génération d’une carte à la volée est la résolution des conflits spatiaux qui apparaissent entre les objets, essentiellement à cause de l’espace réduit des écrans d’affichage. Dans cette thèse, nous proposons une nouvelle approche basée sur la mise en œuvre d’un système multiagent pour la génération à la volée des cartes et la résolution des conflits spatiaux. Cette approche est basée sur l’utilisation de la représentation multiple et la généralisation cartographique. Elle résout les conflits spatiaux et génère les cartes demandées selon une stratégie innovatrice : la génération progressive des cartes par couches d’intérêt. Chaque couche d’intérêt contient tous les objets ayant le même degré d’importance pour l’utilisateur. Ce contenu est déterminé à la volée au début du processus de génération de la carte demandée. Notre approche multiagent génère et transfère cette carte suivant un mode parallèle. En effet, une fois une couche d’intérêt générée, elle est transmise à l’utilisateur. Dans le but de résoudre les conflits spatiaux, et par la même occasion générer la carte demandée, nous affectons un agent logiciel à chaque objet de l’espace. Les agents entrent ensuite en compétition pour l’occupation de l’espace disponible. Cette compétition est basée sur un ensemble de priorités qui correspondent aux différents degrés d’importance des objets pour l’utilisateur. Durant la résolution des conflits, les agents prennent en considération les besoins et les préférences de l’utilisateur afin d’améliorer la personnalisation de la carte. Ils améliorent la lisibilité des objets importants et utilisent des symboles qui pourraient aider l’utilisateur à mieux comprendre l’espace géographique. Le processus de génération de la carte peut être interrompu en tout temps par l’utilisateur lorsque les données déjà transmises répondent à ses besoins. Dans ce cas, son temps d’attente est réduit, étant donné qu’il n’a pas à attendre la génération du reste de la carte. Afin d’illustrer notre approche, nous l’appliquons au contexte de la cartographie sur le web ainsi qu’au contexte de la cartographie mobile. Dans ces deux contextes, nous catégorisons nos données, qui concernent la ville de Québec, en quatre couches d’intérêt contenant les objets explicitement demandés par l’utilisateur, les objets repères, le réseau routier et les objets ordinaires qui n’ont aucune importance particulière pour l’utilisateur. Notre système multiagent vise à résoudre certains problèmes liés à la génération à la volée des cartes web. Ces problèmes sont les suivants : 1. Comment adapter le contenu des cartes, à la volée, aux besoins des utilisateurs ? 2. Comment résoudre les conflits spatiaux de manière à améliorer la lisibilité de la carte tout en prenant en considération les besoins de l’utilisateur ? 3. Comment accélérer la génération et le transfert des données aux utilisateurs ? Les principales contributions de cette thèse sont : 1. La résolution des conflits spatiaux en utilisant les systèmes multiagent, la généralisation cartographique et la représentation multiple. 2. La génération des cartes dans un contexte web et dans un contexte mobile, à la volée, en utilisant les systèmes multiagent, la généralisation cartographique et la représentation multiple. 3. L’adaptation des contenus des cartes, en temps réel, aux besoins de l’utilisateur à la source (durant la première génération de la carte). 4. Une nouvelle modélisation de l’espace géographique basée sur une architecture multi-couches du système multiagent. 5. Une approche de génération progressive des cartes basée sur les couches d’intérêt. 6. La génération et le transfert, en parallèle, des cartes aux utilisateurs, dans les contextes web et mobile.Abstract Internet is a fast growing medium to get and disseminate geospatial information. It provides more and more web mapping services accessible by thousands of users worldwide. However, the quality of these services needs to be improved, especially in term of personalization. In order to increase map flexibility, it is important that the map corresponds as much as possible to the user’s needs, preferences and context. This may be possible by applying the suitable transformations, in real-time, to spatial objects at each map generation cycle. An underlying challenge of such on-the-fly map generation is to solve spatial conflicts that may appear between objects especially due to lack of space on display screens. In this dissertation, we propose a multiagent-based approach to address the problems of on-the-fly web map generation and spatial conflict resolution. The approach is based upon the use of multiple representation and cartographic generalization. It solves conflicts and generates maps according to our innovative progressive map generation by layers of interest approach. A layer of interest contains objects that have the same importance to the user. This content, which depends on the user’s needs and the map’s context of use, is determined on-the-fly. Our multiagent-based approach generates and transfers data of the required map in parallel. As soon as a given layer of interest is generated, it is transmitted to the user. In order to generate a given map and solve spatial conflicts, we assign a software agent to every spatial object. Then, the agents compete for space occupation. This competition is driven by a set of priorities corresponding to the importance of objects for the user. During processing, agents take into account users’ needs and preferences in order to improve the personalization of the final map. They emphasize important objects by improving their legibility and using symbols in order to help the user to better understand the geographic space. Since the user can stop the map generation process whenever he finds the required information from the amount of data already transferred, his waiting delays are reduced. In order to illustrate our approach, we apply it to the context of tourist web and mobile mapping applications. In these contexts, we propose to categorize data into four layers of interest containing: explicitly required objects, landmark objects, road network and ordinary objects which do not have any specific importance for the user. In this dissertation, our multiagent system aims at solving the following problems related to on-the-fly web mapping applications: 1. How can we adapt the contents of maps to users’ needs on-the-fly? 2. How can we solve spatial conflicts in order to improve the legibility of maps while taking into account users’ needs? 3. How can we speed up data generation and transfer to users? The main contributions of this thesis are: 1. The resolution of spatial conflicts using multiagent systems, cartographic generalization and multiple representation. 2. The generation of web and mobile maps, on-the-fly, using multiagent systems, cartographic generalization and multiple representation. 3. The real-time adaptation of maps’ contents to users’ needs at the source (during the first generation of the map). 4. A new modeling of the geographic space based upon a multi-layers multiagent system architecture. 5. A progressive map generation approach by layers of interest. 6. The generation and transfer of web and mobile maps at the same time to users

Automated Pattern Detection and Generalization of Building Groups

This dissertation focuses on the topic of building group generalization by considering the detection of building patterns. Generalization is an important research field in cartography, which is part of map production and the basis for the derivation of multiple representation. As one of the most important features on map, buildings occupy large amount of map space and normally have complex shape and spatial distribution, which leads to that the generalization of buildings has long been an important and challenging task. For social, architectural and geographical reasons, the buildings were built with some special rules which forms different building patterns. Building patterns are crucial structures which should be carefully considered during graphical representation and generalization. Although people can effortlessly perceive these patterns, however, building patterns are not explicitly described in building datasets. Therefore, to better support the subsequent generalization process, it is important to automatically recognize building patterns. The objective of this dissertation is to develop effective methods to detect building patterns from building groups. Based on the identified patterns, some generalization methods are proposed to fulfill the task of building generalization. The main contribution of the dissertation is described as the following five aspects: (1) The terminology and concept of building pattern has been clearly explained; a detailed and relative complete typology of building patterns has been proposed by summarizing the previous researches as well as extending by the author; (2) A stroke-mesh based method has been developed to group buildings and detect different patterns from the building groups; (3) Through the analogy between line simplification and linear building group typification, a stroke simplification based typification method has been developed aiming at solving the generalization of building groups with linear patterns; (4) A mesh-based typification method has been developed for the generalization of the building groups with grid patterns; (5) A method of extracting hierarchical skeleton structures from discrete buildings have been proposed. The extracted hierarchical skeleton structures are regarded as the representations of the global shape of the entire region, which is used to control the generalization process. With the above methods, the building patterns are detected from the building groups and the generalization of building groups are executed based on the patterns. In addition, the thesis has also discussed the drawbacks of the methods and gave the potential solutions.:Abstract I Kurzfassung III Contents V List of Figures IX List of Tables XIII List of Abbreviations XIV Chapter 1 Introduction 1 1.1 Background and motivation 1 1.1.1 Cartographic generalization 1 1.1.2 Urban building and building patterns 1 1.1.3 Building generalization 3 1.1.4 Hierarchical property in geographical objects 3 1.2 Research objectives 4 1.3 Study area 5 1.4 Thesis structure 6 Chapter 2 State of the Art 8 2.1 Operators for building generalization 8 2.1.1 Selection 9 2.1.2 Aggregation 9 2.1.3 Simplification 10 2.1.4 Displacement 10 2.2 Researches of building grouping and pattern detection 11 2.2.1 Building grouping 11 2.2.2 Pattern detection 12 2.2.3 Problem analysis . 14 2.3 Researches of building typification 14 2.3.1 Global typification 15 2.3.2 Local typification 15 2.3.3 Comparison analysis 16 2.3.4 Problem analysis 17 2.4 Summary 17 Chapter 3 Using stroke and mesh to recognize building group patterns 18 3.1 Abstract 19 3.2 Introduction 19 3.3 Literature review 20 3.4 Building pattern typology and study area 22 3.4.1 Building pattern typology 22 3.4.2 Study area 24 3.5 Methodology 25 3.5.1 Generating and refining proximity graph 25 3.5.2 Generating stroke and mesh 29 3.5.3 Building pattern recognition 31 3.6 Experiments 33 3.6.1 Data derivation and test framework 33 3.6.2 Pattern recognition results 35 3.6.3 Evaluation 39 3.7 Discussion 40 3.7.1 Adaptation of parameters 40 3.7.2 Ambiguity of building patterns 44 3.7.3 Advantage and Limitation 45 3.8 Conclusion 46 Chapter 4 A typification method for linear building groups based on stroke simplification 47 4.1 Abstract 48 4.2 Introduction 48 4.3 Detection of linear building groups 50 4.3.1 Stroke-based detection method 50 4.3.2 Distinguishing collinear and curvilinear patterns 53 4.4 Typification method 55 4.4.1 Analogy of building typification and line simplification 55 4.4.2 Stroke generation 56 4.4.3 Stroke simplification 57 4.5 Representation of newly typified buildings 60 4.6 Experiment 63 4.6.1 Linear building group detection 63 4.6.2 Typification results 65 4.7 Discussion 66 4.7.1 Comparison of reallocating remained nodes 66 4.7.2 Comparison with classic line simplification method 67 4.7.3 Advantage 69 4.7.4 Further improvement 71 4.8 Conclusion 71 Chapter 5 A mesh-based typification method for building groups with grid patterns 73 5.1 Abstract 74 5.2 Introduction 74 5.3 Related work 75 5.4 Methodology of mesh-based typification 78 5.4.1 Grid pattern classification 78 5.4.2 Mesh generation 79 5.4.3 Triangular mesh elimination 80 5.4.4 Number and positioning of typified buildings 82 5.4.5 Representation of typified buildings 83 5.4.6 Resizing Newly Typified Buildings 85 5.5 Experiments 86 5.5.1 Data derivation 86 5.5.2 Typification results and evaluation 87 5.5.3 Comparison with official map 91 5.6 Discussion 92 5.6.1 Advantages 92 5.6.2 Further improvements 93 5.7 Conclusion 94 Chapter 6 Hierarchical extraction of skeleton structures from discrete buildings 95 6.1 Abstract 96 6.2 Introduction 96 6.3 Related work 97 6.4 Study area 99 6.5 Hierarchical extraction of skeleton structures 100 6.5.1 Proximity Graph Network (PGN) of buildings 100 6.5.2 Centrality analysis of proximity graph network 103 6.5.3 Hierarchical skeleton structures of buildings 108 6.6 Generalization application 111 6.7 Experiment and discussion 114 6.7.1 Data statement 114 6.7.2 Experimental results 115 6.7.3 Discussion 118 6.8 Conclusions 120 Chapter 7 Discussion 121 7.1 Revisiting the research problems 121 7.2 Evaluation of the presented methodology 123 7.2.1 Strengths 123 7.2.2 Limitations 125 Chapter 8 Conclusions 127 8.1 Main contributions 127 8.2 Outlook 128 8.3 Final thoughts 131 Bibliography 132 Acknowledgements 142 Publications 14

Controlled Line Smoothing by Snakes

A major focus of research in recent years has been the development of algorithms for automated line smoothing. However, combination of the algorithms with other generalization operators is a challenging problem. In this research a key aim was to extend a snakes optimization approach, allowing displacement of lines, to also be used for line smoothing. Furthermore, automated selection of control parameters is important for fully automated solutions. An existing approach based on line segmentation was used to control the selection of smoothing parameters dependent on object characteristics. Additionally a new typification routine is presented, which uses the same preprocessed analysis for the segmentation of lines to find suitable candidates from curve bends. The typification is realized by deleting undersized bends and emphasizing the remaining curve bends. The main results of this research are two new algorithms for line generalization, where the importance of the line smoothing algorithm lies in the usage of a optimization approach which can also be used for line displacemen

A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community

In recent years, deep learning (DL), a re-branding of neural networks (NNs), has risen to the top in numerous areas, namely computer vision (CV), speech recognition, natural language processing, etc. Whereas remote sensing (RS) possesses a number of unique challenges, primarily related to sensors and applications, inevitably RS draws from many of the same theories as CV; e.g., statistics, fusion, and machine learning, to name a few. This means that the RS community should be aware of, if not at the leading edge of, of advancements like DL. Herein, we provide the most comprehensive survey of state-of-the-art RS DL research. We also review recent new developments in the DL field that can be used in DL for RS. Namely, we focus on theories, tools and challenges for the RS community. Specifically, we focus on unsolved challenges and opportunities as it relates to (i) inadequate data sets, (ii) human-understandable solutions for modelling physical phenomena, (iii) Big Data, (iv) non-traditional heterogeneous data sources, (v) DL architectures and learning algorithms for spectral, spatial and temporal data, (vi) transfer learning, (vii) an improved theoretical understanding of DL systems, (viii) high barriers to entry, and (ix) training and optimizing the DL.Comment: 64 pages, 411 references. To appear in Journal of Applied Remote Sensin