Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

The Repast Simulation/Modelling System for Geospatial Simulation

The use of simulation/modelling systems can simplify the implementation of agent-based models. Repast is one of the few simulation/modelling software systems that supports the integration of geospatial data especially that of vector-based geometries. This paper provides details about Repast specifically an overview, including its different development languages available to develop agent-based models. Before describing Repast’s core functionality and how models can be developed within it, specific emphasis will be placed on its ability to represent dynamics and incorporate geographical information. Once these elements of the system have been covered, a diverse list of Agent-Based Modelling (ABM) applications using Repast will be presented with particular emphasis on spatial applications utilizing Repast, in particular, those that utilize geospatial data

Integrating Research Data Management into Geographical Information Systems

Ocean modelling requires the production of high-fidelity computational meshes upon which to solve the equations of motion. The production of such meshes by hand is often infeasible, considering the complexity of the bathymetry and coastlines. The use of Geographical Information Systems (GIS) is therefore a key component to discretising the region of interest and producing a mesh appropriate to resolve the dynamics. However, all data associated with the production of a mesh must be provided in order to contribute to the overall recomputability of the subsequent simulation. This work presents the integration of research data management in QMesh, a tool for generating meshes using GIS. The tool uses the PyRDM library to provide a quick and easy way for scientists to publish meshes, and all data required to regenerate them, to persistent online repositories. These repositories are assigned unique identifiers to enable proper citation of the meshes in journal articles.Comment: Accepted, camera-ready version. To appear in the Proceedings of the 5th International Workshop on Semantic Digital Archives (http://sda2015.dke-research.de/), held in Pozna\'n, Poland on 18 September 2015 as part of the 19th International Conference on Theory and Practice of Digital Libraries (http://tpdl2015.info/

Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

Requirements engineering for computer integrated environments in construction

A Computer Integrated Environment (CIE) is the type of innovative integrated information system that helps to reduce fragmentation and enables the stakeholders to collaborate together in business. Researchers have observed that the concept of CIE has been the subject of research for many years but the uptake of this technology has been very limited because of the development of the technology and its effective implementation. Although CIE is very much valued by both industrialists and academics, the answers to the question of how to develop and how to implement it are still not clear. The industrialists and researchers conveyed that networking, collaboration, information sharing and communication will become popular and critical issues in the future, which can be managed through CIE systems. In order for successful development of the technology, successful delivery, and effective implementation of user and industry-oriented CIE systems, requirements engineering seems a key parameter. Therefore, through experiences and lessons learnt in various case studies of CIE systems developments, this book explains the development of a requirements engineering framework specific to the CIE system. The requirements engineering process that has been developed in the research is targeted at computer integrated environments with a particular interest in the construction industry as the implementation field. The key features of the requirements engineering framework are the following: (1) ready-to-use, (2) simple, (3) domain specific, (4) adaptable and (5) systematic, (6) integrated with the legacy systems. The method has three key constructs: i) techniques for requirements development, which includes the requirement elicitation, requirements analysis/modelling and requirements validation, ii) requirements documentation and iii) facilitating the requirements management. It focuses on system development methodologies for the human driven ICT solutions that provide communication, collaboration, information sharing and exchange through computer integrated environments for professionals situated in discrete locations but working in a multidisciplinary and interdisciplinary environment. The overview for each chapter of the book is as follows; Chapter 1 provides an overview by setting the scene and presents the issues involved in requirements engineering and CIE (Computer Integrated Environments). Furthermore, it makes an introduction to the necessity for requirements engineering for CIE system development, experiences and lessons learnt cumulatively from CIE systems developments that the authors have been involved in, and the process of the development of an ideal requirements engineering framework for CIE systems development, based on the experiences and lessons learnt from the multi-case studies. Chapter 2 aims at building up contextual knowledge to acquire a deeper understanding of the topic area. This includes a detailed definition of the requirements engineering discipline and the importance and principles of requirements engineering and its process. In addition, state of the art techniques and approaches, including contextual design approach, the use case modelling, and the agile requirements engineering processes, are explained to provide contextual knowledge and understanding about requirements engineering to the readers. After building contextual knowledge and understanding about requirements engineering in chapter 2, chapter 3 attempts to identify a scope and contextual knowledge and understanding about computer integrated environments and Building Information Modelling (BIM). In doing so, previous experiences of the authors about systems developments for computer integrated environments are explained in detail as the CIE/BIM case studies. In the light of contextual knowledge gained about requirements engineering in chapter 2, in order to realize the critical necessity of requirements engineering to combine technology, process and people issues in the right balance, chapter 4 will critically evaluate the requirements engineering activities of CIE systems developments that are explained in chapter 3. Furthermore, to support the necessity of requirements engineering for human centred CIE systems development, the findings from semi-structured interviews are shown in a concept map that is also explained in this chapter. In chapter 5, requirements engineering is investigated from different angles to pick up the key issues from discrete research studies and practice such as traceability through process and product modelling, goal-oriented requirements engineering, the essential and incidental complexities in requirements models, the measurability of quality requirements, the fundamentals of requirements engineering, identifying and involving the stakeholders, reconciling software requirements and system architectures and barriers to the industrial uptake of requirements engineering. In addition, a comprehensive research study measuring the success of requirements engineering processes through a set of evaluation criteria is introduced. Finally, the key issues and the criteria are comparatively analyzed and evaluated in order to match each other and confirm the validity of the criteria for the evaluation and assessment of the requirements engineering implementation in the CIE case study projects in chapter 7 and the key issues will be used in chapter 9 to support the CMM (Capability Maturity Model) for acceptance and wider implications of the requirements engineering framework to be proposed in chapter 8. Chapter 6 explains and particularly focuses on how the requirements engineering activities in the case study projects were handled by highlighting strengths and weaknesses. This will also include the experiences and lessons learnt from these system development practices. The findings from these developments will also be utilized to support the justification of the necessity of a requirements engineering framework for the CIE systems developments. In particular, the following are addressed. • common and shared understanding in requirements engineering efforts, • continuous improvement, • outputs of requirement engineering • reflections and the critical analysis of the requirements engineering approaches in these practices. The premise of chapter 7 is to evaluate and assess the requirements engineering approaches in the CIE case study developments from multiple viewpoints in order to find out the strengths and the weaknesses in these requirements engineering processes. This evaluation will be mainly based on the set of criteria developed by the researchers and developers in the requirements engineering community in order to measure the success rate of the requirements engineering techniques after their implementation in the various system development projects. This set of criteria has already been introduced in chapter 5. This critical assessment includes conducting a questionnaire based survey and descriptive statistical analysis. In chapter 8, the requirements engineering techniques tested in the CIE case study developments are composed and compiled into a requirements engineering process in the light of the strengths and the weaknesses identified in the previous chapter through benchmarking with a Capability Maturity Model (CMM) to ensure that it has the required level of maturity for implementation in the CIE systems developments. As a result of this chapter, a framework for a generic requirements engineering process for CIE systems development will be proposed. In chapter 9, the authors will discuss the acceptance and the wider implications of the proposed framework of requirements engineering process using the CMM from chapter 8 and the key issues from chapter 5. Chapter 10 is the concluding chapter and it summarizes the findings and brings the book to a close with recommendations for the implementation of the Proposed RE framework and also prescribes a guideline as a way forward for better implementation of requirements engineering for successful developments of the CIE systems in the future

Geoinformation, Geotechnology, and Geoplanning in the 1990s

Over the last decade, there have been some significant changes in the geographic information available to support those involved in spatial planning and policy-making in different contexts. Moreover, developments have occurred apace in the technology with which to handle geoinformation. This paper provides an overview of trends during the 1990s in data provision, in the technology required to manipulate and analyse spatial information, and in the domain of planning where applications of computer technology in the processing of geodata are prominent. It draws largely on experience in western Europe, and in the UK and the Netherlands in particular, and suggests that there are a number of pressures for a strengthened role for geotechnology in geoplanning in the years ahead

Airborne LiDAR for DEM generation: some critical issues

Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented

Exploring Cities Using Agent-Based Models and GIS

Cities are faced with many problems such as urban sprawl, congestion, and segregation. They are also constantly changing. Computer modelling is becoming an increasingly important tool when examining how cities operate. Agent based models (ABM) allow for the testing of different hypotheses and theories for urban change, thus leading to a greater understanding of how cities work. This paper presents how ABMs can be developed by their integration with Geographical Information System (GIS). To highlight this, a generic ABM is presented. This is then applied to two model applications: a segregation model and a location model. Both models highlight how different theories can be incorporated into the generic model and demonstrate the importance of space in the modelling process. Cities are faced with many problems such as urban sprawl, congestion, and segregation. They are also constantly changing. Computer modelling is becoming an increasingly important tool when examining how cities operate. Agent based models (ABM) allow for the testing of different hypotheses and theories for urban change, thus leading to a greater understanding of how cities work. This paper presents how ABMs can be developed by their integration with Geographical Information System (GIS). To highlight this, a generic ABM is presented. This is then applied to two model applications: a segregation model and a location model. Both models highlight how different theories can be incorporated into the generic model and demonstrate the importance of space in the modelling process

Integrated urban evolutionary modeling

Cellular automata models have proved rather popular as frameworks for simulating the physical growth of cities. Yet their brief history has been marked by a lack of application to real policy contexts, notwithstanding their obvious relevance to topical problems such as urban sprawl. Traditional urban models which emphasize transportation and demography continue to prevail despite their limitations in simulating realistic urban dynamics. To make progress, it is necessary to link CA models to these more traditional forms, focusing on the explicit simulation of the socio-economic attributes of land use activities as well as spatial interaction. There are several ways of tackling this but all are based on integration using various forms of strong and loose coupling which enable generically different models to be connected. Such integration covers many different features of urban simulation from data and software integration to internet operation, from interposing demand with the supply of urban land to enabling growth, location, and distributive mechanisms within such models to be reconciled. Here we will focus on developin