Multi-scale data storage schemes for spatial information systems

This thesis documents a research project that has led to the design and prototype implementation of several data storage schemes suited to the efficient multi-scale representation of integrated spatial data. Spatial information systems will benefit from having data models which allow for data to be viewed and analysed at various levels of detail, while the integration of data from different sources will lead to a more accurate representation of reality. The work has addressed two specific problems. The first concerns the design of an integrated multi-scale data model suited for use within Geographical Information Systems. This has led to the development of two data models, each of which allow for the integration of terrain data and topographic data at multiple levels of detail. The models are based on a combination of adapted versions of three previous data structures, namely, the constrained Delaunay pyramid, the line generalisation tree and the fixed grid. The second specific problem addressed in this thesis has been the development of an integrated multi-scale 3-D geological data model, for use within a Geoscientific Information System. This has resulted in a data storage scheme which enables the integration of terrain data, geological outcrop data and borehole data at various levels of detail. The thesis also presents details of prototype database implementations of each of the new data storage schemes. These implementations have served to demonstrate the feasibility and benefits of an integrated multi-scale approach. The research has also brought to light some areas that will need further research before fully functional systems are produced. The final chapter contains, in addition to conclusions made as a result of the research to date, a summary of some of these areas that require future work

Management of spatial data for visualization on mobile devices

Vector-based mapping is emerging as a preferred format in Location-based Services(LBS), because it can deliver an up-to-date and interactive map visualization. The Progressive Transmission(PT) technique has been developed to enable the ecient transmission of vector data over the internet by delivering various incremental levels of detail(LoD). However, it is still challenging to apply this technique in a mobile context due to many inherent limitations of mobile devices, such as small screen size, slow processors and limited memory. Taking account of these limitations, PT has been extended by developing a framework of ecient data management for the visualization of spatial data on mobile devices. A data generalization framework is proposed and implemented in a software application. This application can signicantly reduce the volume of data for transmission and enable quick access to a simplied version of data while preserving appropriate visualization quality. Using volunteered geographic information as a case-study, the framework shows exibility in delivering up-to-date spatial information from dynamic data sources. Three models of PT are designed and implemented to transmit the additional LoD renements: a full scale PT as an inverse of generalisation, a viewdependent PT, and a heuristic optimised view-dependent PT. These models are evaluated with user trials and application examples. The heuristic optimised view-dependent PT has shown a signicant enhancement over the traditional PT in terms of bandwidth-saving and smoothness of transitions. A parallel data management strategy associated with three corresponding algorithms has been developed to handle LoD spatial data on mobile clients. This strategy enables the map rendering to be performed in parallel with a process which retrieves the data for the next map location the user will require. A viewdependent approach has been integrated to monitor the volume of each LoD for visible area. The demonstration of a exible rendering style shows its potential use in visualizing dynamic geoprocessed data. Future work may extend this to integrate topological constraints and semantic constraints for enhancing the vector map visualization

Matching 2D images in 3D: metric relative pose from metric correspondences

Given two images, we can estimate the relative camera pose between them by establishing image-to-image correspondences. Usually, correspondences are 2D-to-2D and the pose we estimate is defined only up to scale. Some applications, aiming at instant augmented reality anywhere, require scale-metric pose estimates, and hence, they rely on external depth estimators to recover the scale. We present MicKey, a keypoint matching pipeline that is able to predict metric correspondences in 3D camera space. By learning to match 3D coordinates across images, we are able to infer the metric relative pose without depth measurements. Depth measurements are also not required for training, nor are scene reconstructions or image overlap information. MicKey is supervised only by pairs of images and their relative poses. MicKey achieves state-of-the-art performance on the Map-Free Relocalisation benchmark while requiring less supervision than competing approaches

Efficient bulk-loading methods for temporal and multidimensional index structures

Nahezu alle naturwissenschaftlichen Bereiche profitieren von neuesten Analyse- und Verarbeitungsmethoden für große Datenmengen. Diese Verfahren setzten eine effiziente Verarbeitung von geo- und zeitbezogenen Daten voraus, da die Zeit und die Position wichtige Attribute vieler Daten sind. Die effiziente Anfrageverarbeitung wird insbesondere durch den Einsatz von Indexstrukturen ermöglicht. Im Fokus dieser Arbeit liegen zwei Indexstrukturen: Multiversion B-Baum (MVBT) und R-Baum. Die erste Struktur wird für die Verwaltung von zeitbehafteten Daten, die zweite für die Indexierung von mehrdimensionalen Rechteckdaten eingesetzt. Ständig- und schnellwachsendes Datenvolumen stellt eine große Herausforderung an die Informatik dar. Der Aufbau und das Aktualisieren von Indexen mit herkömmlichen Methoden (Datensatz für Datensatz) ist nicht mehr effizient. Um zeitnahe und kosteneffiziente Datenverarbeitung zu ermöglichen, werden Verfahren zum schnellen Laden von Indexstrukturen dringend benötigt. Im ersten Teil der Arbeit widmen wir uns der Frage, ob es ein Verfahren für das Laden von MVBT existiert, das die gleiche I/O-Komplexität wie das externe Sortieren besitz. Bis jetzt blieb diese Frage unbeantwortet. In dieser Arbeit haben wir eine neue Kostruktionsmethode entwickelt und haben gezeigt, dass diese gleiche Zeitkomplexität wie das externe Sortieren besitzt. Dabei haben wir zwei algorithmische Techniken eingesetzt: Gewichts-Balancierung und Puffer-Bäume. Unsere Experimenten zeigen, dass das Resultat nicht nur theoretischer Bedeutung ist. Im zweiten Teil der Arbeit beschäftigen wir uns mit der Frage, ob und wie statistische Informationen über Geo-Anfragen ausgenutzt werden können, um die Anfrageperformanz von R-Bäumen zu verbessern. Unsere neue Methode verwendet Informationen wie Seitenverhältnis und Seitenlängen eines repräsentativen Anfragerechtecks, um einen guten R-Baum bezüglich eines häufig eingesetzten Kostenmodells aufzubauen. Falls diese Informationen nicht verfügbar sind, optimieren wir R-Bäume bezüglich der Summe der Volumina von minimal umgebenden Rechtecken der Blattknoten. Da das Problem des Aufbaus von optimalen R-Bäumen bezüglich dieses Kostenmaßes NP-hart ist, führen wir zunächst das Problem auf ein eindimensionales Partitionierungsproblem zurück, indem wir die Daten bezüglich optimierte raumfüllende Kurven sortieren. Dann lösen wir dieses Problem durch Einsatz vom dynamischen Programmieren. Die I/O-Komplexität des Verfahrens ist gleich der von externem Sortieren, da die I/O-Laufzeit der Methode durch die Laufzeit des Sortierens dominiert wird. Im letzten Teil der Arbeit haben wir die entwickelten Partitionierungsvefahren für den Aufbau von Geo-Histogrammen eingesetzt, da diese ähnlich zu R-Bäumen eine disjunkte Partitionierung des Raums erzeugen. Ergebnisse von intensiven Experimenten zeigen, dass sich unter Verwendung von neuen Partitionierungstechniken sowohl R-Bäume mit besserer Anfrageperformanz als auch Geo-Histogrammen mit besserer Schätzqualität im Vergleich zu Konkurrenzverfahren generieren lassen

Code and the Transduction of Space

The effects of software (code) on the spatial formation of everyday life are best understood through a theoretical framework that utilizes the concepts of technicity (the productive power of technology to make things happen) and transduction (the constant making anew of a domain in reiterative and transformative practices). Examples from the lives of three Londoners illustrate that code makes a difference to everyday life because its technicity alternatively modulates space through processes of transduction. Space needs to be theorized as ontogenetic, that is, understood as continually being brought into existence through transductive practices (practices that change the conditions under which space is (re)made). The nature of space transduced by code is detailed and illustrated with respect to domestic living, work, communication, transport, and consumption

Code and the Transduction of Space

The effects of software (code) on the spatial formation of everyday life are best understood through a theoretical framework that utilizes the concepts of technicity (the productive power of technology to make things happen) and transduction (the constant making anew of a domain in reiterative and transformative practices). Examples from the lives of three Londoners illustrate that code makes a difference to everyday life because its technicity alternatively modulates space through processes of transduction. Space needs to be theorized as ontogenetic, that is, understood as continually being brought into existence through transductive practices (practices that change the conditions under which space is (re)made). The nature of space transduced by code is detailed and illustrated with respect to domestic living, work, communication, transport, and consumption

An examination of the application of a geographical information system to rural development planning in Shixini Location, Transkei

Digital geographical information systems (GIS) are tools for handling spatial data. Initially developed in First World countries, the technology is fast being taken up as a tool for handling spatial information by many Third World countries. GIS has been used for any number of applications involving spatial data, one of its primary uses has been in various planning fields where the advantages offered to planners by the technology have been highlighted by a number of publications and studies. GIS has been actively used as an urban planning tool in South Africa since the mid-1980s, (Vosloo 1987) however its use as a tool for rural planning has not developed to the same extent. As early as 1986 reference was made to the possible advantages offered by GIS to rural planning in South Africa (Fincham 1986). Despite this early recognition, the use of GIS in the rural planning sphere remains negligible. This study examines the. possible reasons for this by attempting to answer the question, "is GIS appropriate to rural planning in South Africa?" A number of approaches to rural planning are practised in South Africa. This study examines the appropriateness of applying GIS to one of these approaches, rural community development planning. Components of the study included i) an examination of the issues affecting the use of GIS in the rural development field, achieved through the use of a literature and questionnaire survey and ii) a case study examining the feasibility of incorporating GIS as a tool to the Shixini Development Project, Transkei. The study does not examine the intricacies of rural development theory, but it does acknowledge the fact that the approach employed by an organisation to rural development will have important implications concerning the use of a GIS in a project. The approach adopted to a project affects amongst others the administrative structure, the planning process, the flow of spatial data and its use, and consequently the possible role of GIS. The Shixini Rural Development Project was classified as a community development project, and as a result the study concentrates on this approach to rural development. This may limit the study to a particular planning process, however most rural case studies will have certain aims and factors which are unique to its situation. In order to place the results of the Shixini case study in a wider context the results of the study are linked to the questionnaire and literature survey. From this basis the usefulness of GIS in the rural development sphere was examined. Available literature on GIS indicates that the majority of problems associated with GIS rarely reside with the technology itself but rather with its supporting mechanisms. The study identified and concentrated on these support mechanisms, both at the project level and what is referred to in the study as the operating environment in South Africa. The results of the study revealed that a number of problems exist with regard to the attitude with which GIS is regarded in development organisations. It was found that these attitudes are legitimately based on a number of problems associated with incorporating the technology into project based organisations. It was concluded that GIS was appropriate to rural community planning, but is presently limited to certain aspects of the planning process and possibly to certain applications

Assessment and visualisation of uncertainty in remote sensing land cover classifications

The ability of space- and airborne instruments to measure the amount of electromagnetic radiation reflected and emitted by the Earths surface has proved to be valuable for the understanding of our environment, as it provides for an overwhelming flow of data on the appearance and condition of our planet. The data yielded by remote sensing can be subjected to various types of computer-assisted manipulation, to arrive at derived data sets tailored to different types of application. Computer-assisted classification of remotely sensed data into qualitative classes, for example, is useful for extracting information that can be exploited for cartographic purposes, such as in the generation of thematic maps of land cover types. For a proper cartographic application, the fitness for use of a set of remotely sensed data needs be assessed. The practicability of the data and their classification can be established by means of an accuracy assessment procedure. An error matrix is created for the classification by matching a random sample and its counterpart from a reference data set representing the actual environment. Accuracy assessment based on an error matrix, however, has several drawbacks. Among these is the non-spatial and general character of a global statement like 95% accuracy for an entire classification; moreover, accuracy assessment is a time-consuming and cost-intensive process. As a consequence, it is easily omitted which, of course, is undesirable and may lead to the use of data that are unfit for the application at hand. For assessing the fitness for use of a set of remotely sensed data, accuracy is not the only consideration. More generally, the phrase data quality is used to refer to the extent to which the characteristics of the data meet the requirements of the application aimed at by the user. A high quality indicates a relatively high information value for the considered application - a good fitness for use. Uncertainty is a key-issue in quality assessment and, therefore, in the assessment of fitness for use of a data set. During the life cycle of remotely sensed data uncertainties are introduced and propagated in an often unknown way. For investigating uncertainty, effective measures need to be designed. To this end, it is relevant to consider the purpose to which these measures are to be employed. Here, the focus is on an exploratory perspective. Exploratory analysis of a set of remotely sensed data aims at acquiring insight into the stability of various possible classifications of these data. For this purpose, knowledge about the uncertainties underlying these classifications is imperative. As in exploratory analysis, classification is an iterative process, needing not only measures for assessing the uncertainty in a classification but also effective ways to convey this information to the user. Visualisation is generally considered a useful means of communication of potentially relevant information. In this thesis a class of measures of uncertainty is presented, tailored to the purpose of exploratory analysis of remotely sensed data, together with various ways of cartographic visualisation of uncertainty. The uncertainty that is introduced during classification of a set of remotely sensed data is characterised by the probability vectors that are yielded as a by-product of most probabilistic classification procedures. Here, emphasis is laid on maximum a?x posteriori classifications where for every pixel in the data a vector of probabilities is calculated that specifies for each distinguished class its probability of being the true class. The probability vectors reflect the differences in uncertainty in the resulting classification and can be stored in a gis to serve as a basis for the derivation of weighted uncertainty measures such as entropy. Besides the assessment of uncertainty, efforts can be aimed at the reduction of the amount of uncertainty present in a remotely sensed data set. The maximum a posteriori classification rules being dealt with in this thesis allow for the introduction of a priori knowledge in the classification process, at different levels of sophistication -thereby exceeding the simple approaches embraced in existing image processing packages. Another strategy within the realm of dealing with spatial data uncertainty is based on the idea of decision analysis that allows for an optimal decision-making given uncertain information classes. Combining probability theory (defining the uncertainty related to the occurrence of a particular class) and utility theory (defining the desirability of the consequences resulting from the actions that are taken assuming that particular class) contributes to the selection of the best decision under the given conditions. This idea is particularly interesting when dealing with huge data sets under uncertain circumstances and with far-reaching consequences for wrong decisions (e.g. agricultural fraud detection by European Union). Both the probabilistic results from the classification procedure and other quality information are subjected to cartographic visualisation rules in order to develop a framework for the communication of this spatial metadata. Static as well as more dynamic approaches offer grips for the gis user who needs to consider simple but persuasive maps to assess the fitness for use of a classification. Commercial gis packages are still failing when the sound consideration of spatial data uncertainty is at stake, a fact that has incited the participants of the camotius project to look for the functionality of an uncertainty-sensitive information system. Such a system is valuable for the Dutch situation in which the extra value added by remotely sensed data is not always beyond all doubt; the explicit evaluation of these data as well as their inherent uncertainty reveals their true information value. Two case studies have stressed the role of remote sensing for planning purposes by demonstrating its ability to monitor changes in the extent of greenhouses over space and time, and making inventories of their area. The inclusion of uncertainty information allows for an exploratory approach in which an appeal can be made to several levels of knowledge in order to improve the processing results. It is stated that a user will be encouraged to use remotely sensed data if their extra value is clearly demonstrable. The components that have been scrutinised in the methodological part of this thesis are formalised in a demonstration programme that could serve as a blueprint for commercial gis packages. It can be downloaded from: http://cartography.geog.uu.nl/research/ph