A framework for models of movement in geographic space

This article concerns the theoretical foundations of movement informatics. We discuss general frameworks in which models of spatial movement may be developed. In particular, the article considers the object–field and Lagrangian–Eulerian dichotomies, and the SNAP/SPAN ontologies of the dynamic world, and classifies the variety of informatic structures according to these frameworks. A major challenge is transitioning between paradigms. Usually data is captured with respect to one paradigm but can usefully be represented in another. We discuss this process in formal terms and then describe experiments that we performed to show feasibility. It emerges that observational granularity plays a crucial role in these transitions

A New Geographic Process Data Model

Processes, although the subject matter of geography, have not been represented in a manner that aids their querying and analysis. This dissertation develops an appropriate data model that allows for such a process oriented representation, which is built upon a theory of process. The data model, called nen, focuses existing modeling approaches on representing and storing process information. The flux simulation framework was created utilizing the nen data model to represent processes; it extends the RePast agent based modeling environment. This simulator includes basic classes for developing a domain specific simulation and a set of query tools for inquiring after the results of a simulation. The methodology was then prototyped with a watershed runoff simulation

Qualitative Process Analysis : Theoretical Requirements and Practical Implementation in Naval Domain

Understanding complex behaviours is an essential component of everyday life, integrated into daily routines as well as specialised research. To handle the increasing amount of data available from (logistic) dynamic scenarios, analysis of the behaviour of agents in a given environment is becoming more automated and thus requires reliable new analytical methods. This thesis seeks to improve analysis of observed data in dynamic scenarios by developing a new model for transforming sparse behavioural observations into realistic explanations of agent behaviours, with the goal of testing that model in a real-world maritime navigation scenario

Agent Based Modeling in Land-Use and Land-Cover Change Studies

Agent based models (ABM) for land use and cover change (LUCC) holds the promise to provide new insight into the processes and patterns of the human and biophysical interactions in ways that have never been explored. Advances in computer technology make it possible to run almost infinite numbers of simulations with multiple heterogeneously shaped actors that reciprocally interact via vertical and horizontal power lines on various levels. Based upon an extensive literature review the basic components for such exercises are explored and discussed. This resulted in a systematic representation of these components consisting of: (1) Spatial static input data, (2) Actor and Actor-group static input data, (3) Spatial dynamic input, (4) Actor and Actor-group dynamic input data, (5) the model with the rules describing the rules, (6) Spatial static output, (7) Actor and Actor-group static output, (8) Dynamic output of Actor behaviour changes, (9) Dynamic output of actor-group behavioural changes, (10) Dynamic output of spatial patterns, (11) Dynamic output of temporal patterns. This representation proves to be epistemologically useful in the analysis of the relationships between the ABM LUCC components. In this paper, this representation is also used to enumerate the strengths and limitations of agent based modelling in LUCC

Microtheories for SDI - Accounting for diversity of local conceptualisations at a global level

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.The categorization and conceptualization of geographic features is fundamental to cartography, geographic information retrieval, routing applications, spatial decision support and data sharing in general. However, there is no standard conceptualization of the world. Humans conceptualize features based on numerous factors including cultural background, knowledge, motivation and particularly space and time. Thus, geographic features are prone to multiple, context-dependent conceptualizations reflecting local conditions. This creates semantic heterogeneity and undermines interoperability. Standardization of a shared definition is often employed to overcome semantic heterogeneity. However, this approach loses important local diversity in feature conceptualizations and may result in feature definitions which are too broad or too specific. This work proposes the use of microtheories in Spatial Data Infrastructures, such as INSPIRE, to account for diversity of local conceptualizations while maintaining interoperability at a global level. It introduces a novel method of structuring microtheories based on space and time, represented by administrative boundaries, to reflect variations in feature conceptualization. A bottom-up approach, based on non-standard inference, is used to create an appropriate global-level feature definition from the local definitions. Conceptualizations of rivers, forests and estuaries throughout Europe are used to demonstrate how the approach can improve the INSPIRE data model and ease its adoption by European member states

Representing and reasoning about changing spatial extensions of geographic features

This thesis presents a novel approach to representing and reasoning about geographic phenomena which can be interpreted based on changes affecting spatial extensions of geographic features. Of particular interest in this work are geographic features whose extensions can be described as 2-dimensional regions corresponding to portions of the earth surface under a specified projection, such as deserts, forests and oceans. The work resulted in the development of a logical framework for representing geographic events and processes. In developing such a framework, issues have been addressed regarding the relationship between these concepts and also between them and geographic features. Other crucial issues are how to define the relation between event and process types and their particular instances, and how to handle different kinds of vagueness to associate specific spatial and temporal boundaries with those instances. Of particular interest in this work is the development of a method of explicitly linking the formalism to spatio-temporal data. This requires work at multiple levels, both in consideration of how the data can be represented and in regards of how primitive elements of the logical framework can be defined. Although data can be regarded as a faithful reproduction of physical elements of the world, some conceptual elements are not always explicitly represented within data. For that reason, a logic-based approach to representing spatio-temporal geographic data was also developed and is presented in this thesis. Representing the data in a logical fashion allows implicit data to be derived by means of logical inferences, and provides a natural way of explicitly connecting the data to a semantic-based formalism. Derived data may include spatial extensions of geographic features at different times, based on existing data describing, for example, portions of the earth’s surface associated with different observable properties. Furthermore, a system has been implemented to evaluate the applicability of the proposed theory. The system takes time-stamped topographic data as an input and allows logical queries to be formulated about the data, returning textual and graphical information on geographic events, processes, and features which participate in them