An intelligent Geographic Information System for design

Recent advances in geographic information systems (GIS) and artificial intelligence (AI) techniques have been summarised, concentrating on the theoretical aspects of their construction and use. Existing projects combining AI and GIS have also been discussed, with attention paid to the interfacing methods used and problems uncovered by the approaches. AI and GIS have been combined in this research to create an intelligent GIS for design. This has been applied to off-shore pipeline route design. The system was tested using data from a real pipeline design project. [Continues.

Transportation linear referencing toolboxes : a 'reflective practitioner's' design approach

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2000."September, 2000."Includes bibliographical references (p. 395-407).Seventy percent of the data of a typical transportation agency (e.g., bridges, accidents, etc.) has location as a primary reference. A Linear Referencing System (LRS) is the main way of identifying the location of this data and providing a storage key for it in a database. LRS is based on a one-dimensional offset on a predefined network. In theory, it is one of the simplest spatial cases. In reality, it can be spatially and analytically quite complex. LRS to quite recent date has been little formally researched. That research which has occurred has been the construction of large and comprehensive conceptual data models. This thesis is not primarily aimed at new "tool building research". The existing models have been based to only a limited extent on a fuller analysis of the nature of transportation and spatial data; they have not considered relevant field and wider methodological concerns (i.e., they followed a "model-driven" approach). The goal here is to create a more appropriate foundation and base from which LRS tools may be most appropriately built (i.e., a 'field-driven" approach). A "practitioners perspective" view of LRS was sought. Such a more holistic understanding was sought through the adoption of a "layered methodology" of research that involved gaining the perspectives of a variety of disciplinary viewpoints. This research framework was developed especially for this thesis based on the ideas and work of Schon and Reich. The approach involved in short a desk exercise in fundamental consideration of the nature of LRS, a deeper, cross-field synthesis and literature research, four in-depth state DOT LRS case studies, a panel of transportation field experts, a panel of national data model experts, and a limited object-orientated modeling exercise. The conclusion reached is that while LRS in the simple case can be modeled in general forms, it is also an "exception-driven" field. Thus, a "toolkit approach" may be more appropriate for LRS. It is inferred that this may hold for other similar application areas in transportation and planning. Further research would further develop the holistic layered methodology adopted here and further define the proposed LRS transportation application toolboxes.by Simon Lewis.Ph.D

ATLAS: a framework for large scale automated mapping and localization

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 203-207).This thesis describes a scalable robotic navigation system that builds a map of the robot's environment on the fly. This problem is also known as Simultaneous Localization and Mapping (SLAM). The SLAM problem has as inputs the control of the robot's motion and sensor measurements to features in the environment. The desired output is the path traversed by the robot (localization) and a representation of the sensed environment (mapping). The principal contribution of this thesis is the introduction of a framework, termed Atlas, that alleviates the computational restrictions of previous approaches to SLAM when mapping extended environments. The Atlas framework partitions the SLAM problem into a graph of submaps, each with its own coordinate system. Furthermore, the framework facilitates the modularity of sensors, map representations, and local navigation algorithms by encapsulating the implementation specific algorithms into an abstracted module. The challenge of loop closing is handled with a module that matches submaps and a verification procedure that trades latency in loop closing with a lower chance of incorrect loop detections inherent with symmetric environments. The framework is demonstrated with several datasets that map large indoor and urban outdoor environments using a variety of sensors: a laser scanner, sonar rangers, and omni-directional video.by Michael Carsten Bosse.Ph.D

Mind out of matter: topics in the physical foundations of consciousness and cognition

This dissertation begins with an exploration of a brand of dual aspect monism and some problems deriving from the distinction between a first person and third person point of view. I continue with an outline of one way in which the conscious experience of the subject might arise from organisational properties of a material substrate. With this picture to hand, I first examine theoretical features at the level of brain organisation which may be required to support conscious experience and then discuss what bearing some actual attributes of biological brains might have on such experience. I conclude the first half of the dissertation with comments on information processing and with artificial neural networks meant to display simple varieties of the organisational features initially described abstractly.While the first half begins with a view of conscious experience and infers downwards in the organisational hierarchy to explore neural features suggested by the view, attention in the second half shifts towards analysing low level dynamical features of material substrates and inferring upwards to possible effects on experience. There is particular emphasis on clarifying the role of chaotic dynamics, and I discuss relationships between levels of description of a cognitive system and comment on issues of complexity, computability, and predictability before returning to the topic of representation which earlier played a central part in isolating features of brain organisation which may underlie conscious experience.Some themes run throughout the dissertation, including an emphasis on understanding experience from both the first person and the third person points of view and on analysing the latter at different levels of description. Other themes include a sustained effort to integrate the picture offered here with existing empirical data and to situate current problems in the philosophy of mind within the new framework, as well as an appeal to tools from mathematics, computer science, and cognitive science to complement the more standard philosophical repertoire

CORSE-81: The 1981 Conference on Remote Sensing Education

Summaries of the presentations and tutorial workshops addressing various strategies in remote sensing education are presented. Course design from different discipline perspectives, equipment requirements for image interpretation and processing, and the role of universities, private industry, and government agencies in the education process are covered

Image Registration Workshop Proceedings

Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research

The Development of a bi-level geographic information systems (GIS) database model for informal settlement upgrading

Bibliography : leaves 348-369.Existing Urban GIS models are faced with several limitations. Firstly, these models tend to be single-scale in nature. They are usually designed to operate at either metropolitan- or at the local-level. Secondly, they are generally designed to cater only for the needs of the formal and environmental sectors of the city system. These models do not cater for the "gaps" of data that exist in digital cadastres throughout the world. In the developed countries, these gaps correspond to areas of physical decay or economic decline. In the developing countries, they correspond to informal settlement areas. In this thesis, a new two-scale urban GIS database model, termed the "Bi-Ievel model" is proposed. This model has been specifically designed to address these gaps in the digital cadastre. Furthermore, the model addresses the short-comings facing current informal settlement upgrading models by providing mechanisms for community participation, project management, creating linkages to formal and environmental sectoral models, and for co-ordinating initiatives at a global-level. The Bi-Ievel model is comprised of a metropolitan-level and a series of local-level database components. These components are inter-linked through bi-directional database warehouse connections. While the model requires Internet-connectivity to achieve its full potential across a metropolitan region, it recognises the need for community participation-based methods at a local-level. Members of the community are actually involved in capturing and entering informal settlement data into the local-level database

Evaluating human-centered approaches for geovisualization

Working with two small group of domain experts I evaluate human-centered approaches to application development which are applicable to geovisualization, following an ISO13407 taxonomy that covers context of use, eliciting requirements, and design. These approaches include field studies and contextual analysis of subjects' context; establishing requirements using a template, via a lecture to communicate geovisualization to subjects and by communicating subjects' context to geovisualization experts with a scenario; autoethnography to understand the geovisualization design process; wireframe, paper and digital interactive prototyping with alternative protocols; and a decision making process for prioritising application improvement. I find that the acquisition and use of real user data is key; that a template approach and teaching subjects about visualization tools and interactions both fail to elicit useful requirements for a visualization application. Consulting geovisualization experts with a scenario of user context and samples of user data does yield suggestions for tools and interactions of use to a visualization designer. The complex and composite natures of both visualization and human-centered domains, incorporating learning from both domains, with user context, makes design challenging. Wireframe, paper and digital interactive prototypes mediate between the user and visualization domains successfully, eliciting exploratory behaviour and suggestions to improve prototypes. Paper prototypes are particularly successful at eliciting suggestions and especially novel visualization improvements. Decision-making techniques prove useful for prioritising different possible improvements, although domain subjects select data-related features over more novel alternative and rank these more inconsistently. The research concludes that understanding subject context of use and data is important and occurs throughout the process of engagement with domain experts, and that standard requirements elicitation techniques are unsuccessful for geovisualization. Engagement with subjects at an early stage with simple prototypes incorporating real subject data and moving to successively more complex prototypes holds the best promise for creating successful geovisualization 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

If you build it, will they come? Evolution towards the application of multi-dimensional GIS to fisheries-oceanography

The development of new technologies in science is a balance between existence and use. There are three versions of this duality – something is built and users come, something is built and users don’t come, and, finally, potential users show up but the ballpark has not yet been built. In each instance there is a combination of three factors at work. The first is a scientific need for a type of data or analysis. The second is a technology or technique developed to meet the need; and the third is a perception that using the technology is somehow "better" that the existing tools and that the tool is easy to use. This work examines closely the development of a tool within oceanography – the Stommel diagram for displaying the time and space spectra of oceanographic phenomena – and the spread of the use of the diagram to other disciplines. The diagram was the product of a number of elements - the mind of a truly original oceanographer, the development of equipment able to collect the detailed temporal and spatial data used to create the plot, and the rise of "big oceanography", which led Stommel to argue graphically for taking care in the design of expeditions. Understanding the spread of the Stommel plot provides a viewpoint for examining the unexpectedly slow development of multi-dimensional geographic information systems (GIS). The development of GIS’s began in the 1970's. Data structures to hold multi-dimensional data have been developed, tools for multidimensional map algebra have been created, and test applications have been developed. The current non-development of multi-dimensional GIS is examined as a background for creating and disseminating GeoModeler, a prototype of scientific GIS able to ingest and display multi-dimensional data. Taking advantage of recent technical developments, we have created a scientific GIS that can display three-dimensional oceanographic data. GeoModeler is used to visually explore and analyze the relationship between water temperature and larval walleye pollock (Theragra chalcogramma) growth in Shelikof Strait, Alaska