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

LIPIcs, Volume 277, GIScience 2023, Complete Volume

LIPIcs, Volume 277, GIScience 2023, Complete Volum

12th International Conference on Geographic Information Science: GIScience 2023, September 12–15, 2023, Leeds, UK

No abstract available

Emerging concepts of data integration in pathogen phylodynamics

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modelling and testing can generate further insights into sequence evolution, trait evolution and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees.status: publishe

GROUND DEFORMATION ANALYSIS IN APENNINE AREAS, SEISMICALLY ACTIVE OR ASEISMIC, USING DATA FROM SAR INTERFEROMETRY AND INTEGRATION OF GEOMORPHOLOGICAL AND STRUCTURAL DATA

The core of the study herein has been the analysis of PS-InSAR datasets aimed at providing new constraints to the active tectonics framework, and seismotectonics, of several regions of the Apennines. The analysed Permanent Scatterers datasets result from processing of large amounts of temporally continuous series of radar images acquired with the ERS (1992-2000), ENVISAT (2003-2010) and COSMO SKYMED (2011-2014) satellite missions. Such datasets, which are available in the cartographic website (Geoportale Nazionale) of the Italian Ministry of Environment (MATTM) have been collected through time by the MATTM in the frame of the "Extraordinary Remote Sensing Plan" (Piano Straordinario di Telerilevamento Ambientale, PST-A, law n. 179/2002 - article 27), with the aim of supporting local administrations in the field of environmental policies. The database was realized through three phases: the first one (2008-2009), which involved the interferometric processing of SAR images acquired throughout the country by the ERS1/ERS2 and ENVISAT satellites in both ascending and descending orbits, from 1992 to 2008; the second one (2010-2011) integrated the existing database with the processing of the SAR images acquired by the ENVISAT satellite from 2008 to 2010; the third phase (2013-2015) provided an upgrading and updating of the previously developed database on critical areas, based on StripMap H image acquired with a 16-day recurrence, either in ascending or descending orbit, using the Italian national satellite system, the COSMO SKYMED. With this study, a massive use of Permanent Scatterer datasets is applied for the first time at assessment of ground deformation of large (hundreds of km2 wide) regions of Italy over the last decades, in order to unravelling their current tectonic behaviour. To date in the field of tectonics – in particular, of earthquake geology - the SAR images have been used essentially through the DinSAR technique (comparison between two images, acquired pre- and post-event) in order to constrain the co- and post-seismic deformation (Massonet et al., 1993; Peltzer et al., 1996, 1998; Stramondo et al., 1999; Atzori et al., 2009; Copley and Reynolds, 2014), while the approach that has been used in the case studies that are the object of the research herein is based on analyses of data that (with the exception of the Lunigiana case study) cover an about 20-year long time window. The opportunity of analysing so long, continuous SAR records has allowed detection of both coseismic displacement of moderate earthquakes (i.e., the M 6.3 2009 L’Aquila earthquake, and the M 5 2013 Lunigiana earthquake), and subdued ground displacements - and acceleration – on time scale ranging from yearly to decades. The specific approach used in this study rests on a combination of various techniques of analysis and processing of the PS datasets. In general, as the analyses that have been carried out aimed at identifying motion values with wide areal extent, a statistical filtering has been applied to PSs velocity values in order to discard from the initial, “native”, dataset fast-moving PSs that may be associated with the occurrence of local-scale phenomena (e.g., landslides, sediment compaction, water extraction, etc.). Furthermore, an in depth inspection of time series of PSs from all of the investigated areas has been carried out with the aim of identifying changing (LoS-oriented) motion trends over the analysed time windows. A distinctive feature of this study was the estimation of vertical ground displacements. In fact, while most studies on ground deformation are based on analysis of SAR data recorded along either ascending or descending satellite orbits (thus based on LoS-oriented motions), a specific focus of this study was to obtain - starting from LoS-oriented PS velocity values - displacement values in the vertical plane oriented west-east. In order to evaluate vertical displacements, a geometrical relationship was applied to ascending - descending PSs pairs. As PS from ascending and descending tracks are neither spatially coincident nor synchronous, each image pair was obtained by selecting ascending-descending radar images with a time separation within one month. In the L’Aquila region case study, the combination of data recorded along both the ascending and descending satellite orbits has been crucial to the identification of pre-seismic ground motions, undetected in previous works that – similarly – had addressed assessment of possible pre-seismic satellite-recorded signals. In the various case studies, different kinds of GIS-aided geostatistical analyses were used to extract and synthesise information on ground deformation through the construction of both raster maps of displacement values for the ascending and descending LoS, respectively, and maps of the vertical (z, up - down) component of the “real” displacement vector. In the Campania plain case study, the PS-InSAR data analysis and processing have been integrated by detail scale geomorphological-stratigraphical analysis. Results of analyses of the two independent data sets are consistent, and point to tectonically-controlled ground displacements in a large part of the northern part of the study area (Volturno plain) during the 1992-2010 analysed time span. In particular, the integrated data sets show that the boundaries of the area affected by current subsidence follow fault scarps formed in the 39 ka old Campania Ignimbrite, while the horst blocks of such faults are substantially stable (or slightly uplifting) during the analysed time window. Furthermore, mean rates of current subsidence and long-term (Late Pleistocene to present) mean subsidence rates are comparable, pointing to current vertical displacement assessed through the PS-InSAR data analysis as the expression of the recent tectonics of the analysed sectors of the Campania plain. The Campania plain substantially lacks strong historical seismicity. Such evidence suggests that the detected surface displacements result at least in part from aseismic fault activity. The Monte Marzano case study has allowed assessment of subdued deformation along both the major structures that were activated with the Irpinia 1980 earthquake, i.e. the NE-dipping Monte Marzano fault and the SW-dipping Conza fault, respectively. Ground deformation associated with such structures appears decreasing from the time window covered by the ERS satellites (1992-2000) to that covered by the ENVISAT (2003-2010). These data suggest that post-seismic slip of the M 6.9 has continued until 20 years after the main shock to become very weak in the following ten years. Furthermore, the PS-InSAR data analysis has shown that wide areas located between the Monte Marzano and Conza faults (i.e., in the one that is recognised as the graben structure bounded by those structures) show uplift in the range of 0-2 mm/yr, more evident in the period surveyed by the ERS satellites (1992-2000) and less evident in the 2003-2010 time span (ENVISAT). Such uplift might be related to the occurrence, at depth, of a fluid reservoir that has been independently identified by seismic tomography (Amoroso et al., 2014). In depth analysis of pre-seismic periods have been carried out in three study areas, i.e. those of the 1997 Colfiorito earthquake, of the 2009 L’Aquila earthquake and of the 2013 Lunigiana earthquake. The Colfiorito case study has not provided any significant information on possible pre-seismic ground deformation, most probably due to the PS spatial distribution in that region too much discontinuous to allow identification of both net signals from inspection of the rare and sparse PS time series, and statistically meaningful surface displacement patterns. Both in the L’Aquila and Lunigiana case studies, ground deformation signals in the pre-seismic period have been detected from inspection of PS time series. Pre-seismic ground deformation signals detected in the Lunigiana area (which was affected by a strike-slip faulting earthquake; Eva et al., 2014, Pezzo et al., 2014, Stramondo et al., 2014) are questionable, as they are quite complex and difficult to be interpreted and framed within the local tectonic scenario. Conversely, very clear and net pre-seismic signals have been identified in the region hit by the L’Aquila normal faulting earthquake. There, in the time span predating of some four years the 6th April 2009 main shock, ground deformation with distinct spatial patterns, and orientations, have been detected. In particular, the PS-InSAR analysis has shown that the hanging wall block of the Paganica fault (the surface expression of the structure activated with the main shock; e.g., Galli et al., 2010) has been subject to slow uplift and eastward horizontal motion from 2005 to September/October 2008, and then (October 2008-March 2009) subject to subsidence and westward oriented horizontal motion. Following coseismic collapse, in the early post-seismic period (April-May 2009), subsidence extended eastwards beyond the Paganica fault trace. The region affected by opposite pre-seismic motions covers the area in which the 6th April main shock and most of both foreshocks and aftershocks (Valoroso et al., 2013) were recorded, while the inversion of the pre-seismic displacements is coeval with onset of the foreshocks (October 2008; Di Luccio et al., 2010). In addition, such a region includes both topographic highs and lows. All of such features point to a correlation of the detected motions with the seismic phenomena, and suggest a deep-seated causative mechanism, such as volume changes in response to vertical/lateral fluids migration and fracturing processes at depth, with all phenomena having been documented in connection with the 2009 earthquake in the study region (e.g., Di Luccio et al., 2010; Lucente et al., 2010; Moro et al., 2017). Pre-seismic ground deformation that has been detected in the L’Aquila region could represent a precursor signal of the 2009, M 6.3 earthquake. Such a hypothesis should be tested, in the future, through the continuous monitoring through SAR satellites, but also high-resolution geodetic techniques, of seismically active regions worldwide aimed at detecting the possible occurrence of pre-seismic signals. However, the results of this study point to the long-term (yearly scale) PS-InSAR technique as a tool crucial to the detection of ground deformation in areas struck by recent earthquakes, and to monitoring active – possibly aseismic - structures. Such knowledge may strongly support strategies addressed at territorial planning and mitigation of seismic hazard, and represent an important sustenance for actions ruled by Civil Protection. On the other hand, the results of this study highlight the importance of the existing PS database, and the importance of continuing implementing such an instrument in the future

Book of short Abstracts of the 11th International Symposium on Digital Earth

The Booklet is a collection of accepted short abstracts of the ISDE11 Symposium

Visual Impairment and Blindness

Blindness and vision impairment affect at least 2.2 billion people worldwide with most individuals having a preventable vision impairment. The majority of people with vision impairment are older than 50 years, however, vision loss can affect people of all ages. Reduced eyesight can have major and long-lasting effects on all aspects of life, including daily personal activities, interacting with the community, school and work opportunities, and the ability to access public services. This book provides an overview of the effects of blindness and visual impairment in the context of the most common causes of blindness in older adults as well as children, including retinal disorders, cataracts, glaucoma, and macular or corneal degeneration

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically

Current Air Quality Issues

Air pollution is thus far one of the key environmental issues in urban areas. Comprehensive air quality plans are required to manage air pollution for a particular area. Consequently, air should be continuously sampled, monitored, and modeled to examine different action plans. Reviews and research papers describe air pollution in five main contexts: Monitoring, Modeling, Risk Assessment, Health, and Indoor Air Pollution. The book is recommended to experts interested in health and air pollution issues