The Challenges to Coupling Dynamic Geospatial Models

Many applications of modeling spatial dynamic systems focus on a single system and a single process, ignoring the geographic and systemic context of the processes being modeled. A solution to this problem is the coupled modeling of spatial dynamic systems. Coupled modeling is challenging for both technical reasons, as well as conceptual reasons. This paper explores the benefits and challenges to coupling or linking spatial dynamic models, from loose coupling, where information transfer between models is done by hand, to tight coupling, where two (or more) models are merged as one. To illustrate the challenges, a coupled model of Urbanization and Wildfire Risk is presented. This model, called Vesta, was applied to the Santa Barbara, California region (using real geospatial data), where Urbanization and Wildfires occur and recur, respectively. The preliminary results of the model coupling illustrate that coupled modeling can lead to insight into the consequences of processes acting on their own

Dynamic Maps: Representations of Change in Geospatial Modeling and Visualization

By coining the descriptive phrase ―user-centric geographic cosmology, Goodchild (1998), challenges the geographically oriented to address GIS in the broadest imaginable context: as interlocutor between persons and geo-phenomena. This investigation responds both in a general way, and more specifically, to the representations of change in GIS modeling and visualization leading to dynamic mapping. The investigation, consisting of a report and a series of experiments, explores and demonstrates prototype workarounds that enhance GIS capabilities by drawing upon ideas, techniques, and components from agent-based modeling and visualization software, and suggests shifts at the conceptual, methodological, and technical levels. The workarounds and demonstrations presented here are four-dimensional visualizations, representing changes and behaviors of different types of entities such as living creatures, mobile assets, features, structures, and surfaces, using GIS, agent-based modeling and animation techniques. In a typical case, a creature begins as a point feature in GIS, becomes a mobile and interactive object in agent-based modeling, and is fleshed out to three dimensions in an animated representation. In contrast, a land surface remains much the same in all three stages. The experiments address change in location, orientation, shape, visual attributes, viewpoint, scale, and speed in applications representing predator-prey, search and destroy, sense and locate and urban sprawl. During the experiments, particular attention is paid to factors of modeling and visualization involved in engaging human sensing and cognitive abilities

A Review of Platforms for the Development of Agent Systems

Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such agent platforms have been developed. Meanwhile, some of them have been abandoned, others continue their development and new platforms are released. This paper presents a up-to-date review of the existing agent platforms and also a historical perspective of this domain. It aims to serve as a reference point for people interested in developing agent systems. This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used. It distinguishes between the active platforms and those no longer under development or with unclear status. It also classifies the agent platforms as general purpose ones, free or commercial, and specialized ones, which can be used for particular types of applications.Comment: 40 pages, 2 figures, 9 tables, 83 reference

INVESTIGATION INTO GAME-BASED CRISIS SCENARIO MODELLING AND SIMULATION SYSTEM

A crisis is an infrequent and unpredictable event. Training and preparation process requires tools for representation of crisis context. Particularly, crisis events consist of different situations, which can occur at the same time combining into complex situation and becoming a challenge in coordinating several crisis management departments. In this regards, disaster prevention, preparedness and relief can be conceptualized into a design of hypothetical crisis game. Many complex tasks during development of emergency circumstance provide an opportunity for practitioners to train their skills, which are situation analysis, decision-making, and coordination procedures. While the training in physical workouts give crisis personal a hand-on experience in the given situation, it often requires a long time to prepare with a considerable budget. Alternatively, computational framework which allows simulation of crisis models tailoring into crisis scenario can become a cost-effective substitution to this study and training. Although, there are several existing computational toolsets to simulate crisis, there is no system providing a generic functionality to define crisis scenario, simulation model, agent development, and artificial intelligence problem planning in the single unified framework. In addition, a development of genetic framework can become too complex due to a multi-disciplinary knowledge required in each component. Besides, they have not fully incorporated a game technology toolset to fasten the system development process and provide a rich set of features and functionalities to these mentioned components. To develop such crisis simulation system, there are several technologies that must be studied to derive a requirement for software engineering approach in system’s specification designs. With a current modern game technology available in the market, it enables fast prototyping of the framework integrating with cutting-edge graphic render engine, asset management, networking, and scripting library. Therefore, a serious game application for education in crisis management can be fundamentally developed early. Still, many features must be developed exclusively for the novel simulation framework on top of the selected game engine. In this thesis, we classified for essential core components to design a software specification of a serious game framework that eased crisis scenario generation, terrain design, and agent simulation in UML formats. From these diagrams, the framework was prototyped to demonstrate our proposed concepts. From the beginning, the crisis models for different disasters had been analysed for their design and environment representation techniques, thus provided a choice of based simulation technique of a cellular automata in our framework. Importantly, a study for suitability in selection of a game engine product was conducted since the state of the art game engines often ease integration with upcoming technologies. Moreover, the literatures for a procedural generation of crisis scenario context were studied for it provided a structure to the crisis parameters. Next, real-time map visualization in dynamic of resource representation in the area was developed. Then the simulation systems for a large-scale emergency response was discussed for their choice of framework design with their examples of test-case study. An agent-based modelling tool was also not provided from the game engine technology so its design and decision-making procedure had been developed. In addition, a procedural content generation (PCG) was integrated for automated map generation process, and it allowed configuration of scenario control parameters over terrain design during run-time. Likewise, the artificial planning architecture (AI planning) to solve a sequence of suitable action toward a specific goal was considered to be useful to investigate an emergency plan. However, AI planning most often requires an offline computation with a specific planning language. So the comparison study to select a fast and reliable planner was conducted. Then an integration pipeline between the planner and agent was developed over web-service architecture to separate a large computation from the client while provided ease of AI planning configuration using an editor interface from the web application. Finally, the final framework called CGSA-SIM (Crisis Game for Scenario design and Agent modelling simulation) was evaluated for run-time performance and scalability analysis. It shown an acceptable performance framerate for a real-time application in the worst 15 frame-per-seconds (FPS) with maximum visual objects. The normal gameplay performed capped 60 FPS. At same time, the simulation scenario for a wildfire situation had been tested with an agent intervention which generated a simulation data for personal or case evaluation. As a result, we have developed the CGSA-SIM framework to address the implementation challenge of incorporating an emergency simulation system with a modern game technology. The framework aims to be a generic application providing main functionality of crisis simulation game for a visualization, crisis model development and simulation, real-time interaction, and agent-based modelling with AI planning pipeline

Modeling urban growth and land use/land cover change in the Houston Metropolitan Area from 2002 - 2030

The Houston-Galveston-Brazoria Consolidated Metropolitan Statistical Area (Houston CMSA) has experienced rapid population growth during the past decades and is the only major US metropolitan area with no zoning regulations. We use SLEUTH, a spatially explicit cellular automata model, to simulate future (2002-2030) urban growth in the Houston metropolitan area, one of the fastest growing metropolises in the United States during the past decades. The model is calibrated with historical data for the period 1974-2002 that are extracted from a time series of satellite images. The dataset consists of four historical urban extents (1974, 1984, 1992, 2002), two land use layers (1992, 2002), five transportation layers (1974, 1984, 1990, 2002, 2025), slope layer, hillshade layer, and excluded layer. Future growth patterns are predicted based on growth coefficients derived during the calibration phase. After calibrating the model successfully, the spatial pattern of urban growth of the Houston CMSA for the period from 2002 to 2030 is predicted. Within SLEUTH, growth in the Houston CMSA is predominately "organic" with most growth occurring along the urban/rural fringe. Projected increases in urban area from 2002 to 2030 parallel projected increases in population growth within the Houston CMSA. We design three specific scenarios to simulate the spatial consequences of urban growth under different environmental conditions. The first scenario is to simulate the unmanaged growth with no restrictions. The second scenario is to project the moderate growth trend by taking into consideration environmental protection, specifically for agricultural areas, forests and wetlands. The last scenario is to simulate the managed growth with maximum environmental protection. Adjusting the level of protection for different land cover types was found to markedly affect the land use changes in the Houston CMSA. Without any protection on resource lands, Houston CMSA is estimated to lose 2,000 km2 of forest land by 2030, about 600 km2 of agricultural land, and approximately 400 km2 of wetland. Approximately half of all resource land could be saved by the third scenario, managed growth with maximum protection

An Agent-Based Variogram Modeller: Investigating Intelligent, Distributed-Component Geographical Information Systems

Geo-Information Science (GIScience) is the field of study that addresses substantive questions concerning the handling, analysis and visualisation of spatial data. Geo- Information Systems (GIS), including software, data acquisition and organisational arrangements, are the key technologies underpinning GIScience. A GIS is normally tailored to the service it is supposed to perform. However, there is often the need to do a function that might not be supported by the GIS tool being used. The normal solution in these circumstances is to go out and look for another tool that can do the service, and often an expert to use that tool. This is expensive, time consuming and certainly stressful to the geographical data analyses. On the other hand, GIS is often used in conjunction with other technologies to form a geocomputational environment. One of the complex tools in geocomputation is geostatistics. One of its functions is to provide the means to determine the extent of spatial dependencies within geographical data and processes. Spatial datasets are often large and complex. Currently Agent system are being integrated into GIS to offer flexibility and allow better data analysis. The theis will look into the current application of Agents in within the GIS community, determine if they are used to representing data, process or act a service. The thesis looks into proving the applicability of an agent-oriented paradigm as a service based GIS, having the possibility of providing greater interoperability and reducing resource requirements (human and tools). In particular, analysis was undertaken to determine the need to introduce enhanced features to agents, in order to maximise their effectiveness in GIS. This was achieved by addressing the software agent complexity in design and implementation for the GIS environment and by suggesting possible solutions to encountered problems. The software agent characteristics and features (which include the dynamic binding of plans to software agents in order to tackle the levels of complexity and range of contexts) were examined, as well as discussing current GIScience and the applications of agent technology to GIS, agents as entities, objects and processes. These concepts and their functionalities to GIS are then analysed and discussed. The extent of agent functionality, analysis of the gaps and the use these technologies to express a distributed service providing an agent-based GIS framework is then presented. Thus, a general agent-based framework for GIS and a novel agent-based architecture for a specific part of GIS, the variogram, to examine the applicability of the agent- oriented paradigm to GIS, was devised. An examination of the current mechanisms for constructing variograms, underlying processes and functions was undertaken, then these processes were embedded into a novel agent architecture for GIS. Once the successful software agent implementation had been achieved, the corresponding tool was tested and validated - internally for code errors and externally to determine its functional requirements and whether it enhances the GIS process of dealing with data. Thereafter, its compared with other known service based GIS agents and its advantages and disadvantages analysed

The Application of Geographic Information Systems Cellular Automata Based Models to Land Use Change Modelling of Lagos, Nigeria

The urban expansion of Lagos continues unabated and calls for urgent concern. This thesis explored the use of both the conventional and unconventional techniques for modelling land use change. Two conventional methods (ordinary least squares and geographically weighted regression) were based on geographic information systems, while four unconventional methods (logistic regression, artificial neural networks, and two proposed types of support vector machine) were based on cellular automata. These techniques were evaluated using three land use epochs: 1963-1978, 1978-1984, and 1984-2000. The conventional methods make quite strong statistical assumptions, some of which are shown not to be met by the land use data at hand. Despite this, these methods do exhibit substantial agreement between observed and the predicted maps. The non cellular automata and cellular automata modelling were then implemented with the logistic regression, artificial neural network, support vector machine, and fuzzy support vector machine models, with model parameters set by k-fold cross-validation. The cellular automata predicted maps were more accurate than those of the non cellular automata. The cellular automata modelling results from the proposed support vector machine and fuzzy support vector machine were compared with those from the geographic information systems based geographically weighted regression, logistic regression, and artificial neural network. The results from the geographic information systems based geographically weighted regression were the best, followed by those from the support vector machine and fuzzy support vector machine, followed by the artificial neural network, and logistic regression. This research demonstrated that the proposed support vector machine and fuzzy support vector machine based cellular automata models are promising tools for land use change modelling