Simulating Land Use Land Cover Change Using Data Mining and Machine Learning Algorithms

The objectives of this dissertation are to: (1) review the breadth and depth of land use land cover (LUCC) issues that are being addressed by the land change science community by discussing how an existing model, Purdue\u27s Land Transformation Model (LTM), has been used to better understand these very important issues; (2) summarize the current state-of-the-art in LUCC modeling in an attempt to provide a context for the advances in LUCC modeling presented here; (3) use a variety of statistical, data mining and machine learning algorithms to model single LUCC transitions in diverse regions of the world (e.g. United States and Africa) in order to determine which tools are most effective in modeling common LUCC patterns that are nonlinear; (4) develop new techniques for modeling multiple class (MC) transitions at the same time using existing LUCC models as these models are rare and in great demand; (5) reconfigure the existing LTM for urban growth boundary (UGB) simulation because UGB modeling has been ignored by the LUCC modeling community, and (6) compare two rule based models for urban growth boundary simulation for use in UGB land use planning. The review of LTM applications during the last decade indicates that a model like the LTM has addressed a majority of land change science issues although it has not explicitly been used to study terrestrial biodiversity issues. The review of the existing LUCC models indicates that there is no unique typology to differentiate between LUCC model structures and no models exist for UGB. Simulations designed to compare multiple models show that ANN-based LTM results are similar to Multivariate Adaptive Regression Spline (MARS)-based models and both ANN and MARS-based models outperform Classification and Regression Tree (CART)-based models for modeling single LULC transition; however, for modeling MC, an ANN-based LTM-MC is similar in goodness of fit to CART and both models outperform MARS in different regions of the world. In simulations across three regions (two in United States and one in Africa), the LTM had better goodness of fit measures while the outcome of CART and MARS were more interpretable and understandable than the ANN-based LTM. Modeling MC LUCC require the examination of several class separation rules and is thus more complicated than single LULC transition modeling; more research is clearly needed in this area. One of the greatest challenges identified with MC modeling is evaluating error distributions and map accuracies for multiple classes. A modified ANN-based LTM and a simple rule based UGBM outperformed a null model in all cardinal directions. For UGBM model to be useful for planning, other factors need to be considered including a separate routine that would determine urban quantity over time

Multi-Agent Fitness Functions For Evolutionary Architecture

The dynamics of crowd movements are self-organising and often involve complex pattern formations. Although computational models have recently been developed, it is unclear how well their underlying methods capture local dynamics and longer-range aspects, such as evacuation. A major part of this thesis is devoted to an investigation of current methods, and where required, the development of alternatives. The main purpose is to utilise realistic models of pedestrian crowds in the design of fitness functions for an evolutionary approach to architectural design. We critically review the state-of-the-art in pedestrian and evacuation dynamics. The concept of 'Multi-Agent System' embraces a number of approaches, which together encompass important local and longer-range aspects. Early investigations focus on methods-cellular automata and attractor fields-designed to capture these respective levels. The assumption that pattern formations in crowds result from local processes is reflected in two dimensional cellular automata models, where mathematical rules operate in local neighbourhoods. We investigate an established cellular automata and show that lane-formation patterns are stable only in a low-valued density range. Above this range, such patterns suddenly randomise. By identifying and then constraining the source of this randomness, we are only able to achieve a small degree of improvement. Moreover, when we try to integrate the model with attractor fields, no useful behaviour is achieved, and much of the randomness persists. Investigations indicate that the unwanted randomness is associated with 2-lattice phase transitions, where local dynamics get invaded by giant-component clusters during the onset of lattice percolation. Through this in-depth investigation, the general limits to cellular automata are ascertained-these methods are not designed with lattice percolation properties in mind and resulting models depend, often critically, on arbitrarily chosen neighbourhoods. We embark on the development of new and more flexible methodologies. Rather than treating local and global dynamics as separate entities, we combine them. Our methods are responsive to percolation, and are designed around the following principles: 1) Inclusive search provides an optimal path between a pedestrian origin and destination. 2) Dynamic boundaries protect search and are based on percolation probabilities, calculated from local density regimes. In this way, more robust dynamics are achieved. Simultaneously, longer-range behaviours are also specified. 3) Network-level dynamics further relax the constraints of lattice percolation and allow a wider range of pedestrian interactions. Having defined our methods, we demonstrate their usefulness by applying them to lane-formation and evacuation scenarios. Results reproduce the general patterns found in real crowds. We then turn to evolution. This preliminary work is intended to motivate future research in the field of Evolutionary Architecture. We develop a genotype-phenotype mapping, which produces complex architectures, and demonstrate the use of a crowd-flow model in a phenotype-fitness mapping. We discuss results from evolutionary simulations, which suggest that obstacles may have some beneficial effect on crowd evacuation. We conclude with a summary, discussion of methodological limitations, and suggestions for future research

Generative design in building information modelling (BIM) : approaches and requirements

The integration of generative design (GD) and building information modelling (BIM), as a new technology consolidation, can facilitate the constructability of GD’s automatic design solutions, while improving BIM’s capability in the early design phase. Thus, there has been an increasing interest to study GD-BIM, with current focuses mainly on exploring applications and investigating tools. However, there are a lack of studies regarding methodological relationships and skill requirement based on different development objectives or GD properties; thus, the threshold of developing GD-BIM still seems high. This study conducts a critical review of current approaches for developing GD in BIM, and analyses methodological relationships, skill requirements, and improvement of GD-BIM development. Accordingly, novel perspectives of objective-oriented, GD component-based, and skill-driven GD-BIM development as well as reference guides are proposed. Finally, future research directions, challenges, and potential solutions are discussed. This research aims to guide designers in the building industry to properly determine approaches for developing GD-BIM and inspire researchers’ future studies

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

Big Data Computing for Geospatial Applications

The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms

Dynamic land use/cover change modelling

Landnutzungswandel ist eine komplexe Angelegenheit, die durch zahlreiche biophysikalische, sozioökonomische und wirtschaftliche Faktoren verursacht wird. Eine offensichtliche Art des Landnutzungswandels, die in den suburbanen Gebieten einer Metropole stattfindet, ist die Zersiedelung. Es gibt viele Modellierungstechniken, um dieses Phänomen zu studieren. Diese wurden seit den 1960iger Jahren entwickelt und finden weite Verbreitung. Einige dieser Modelle leiden unter dem Vernachlässigen signifikanter Variablen. Traditionelle Methoden wie etwa zellulare Automaten, Markow-Ketten-Modelle, zellulare Automaten-Markow-Modelle und logistische Regressionsmodelle, weisen inhärente Schwächen auf in Bezug auf menschliche Aktivitäten in der Umwelt. Das liegt daran, dass der Mensch der Hauptakteur in der Transformation der Umwelt ist und die suburbanen Gebiete durch Niederlassungspräferenzen und Lebensstil prägt. Das Hauptziel dieser Dissertation ist es, einige dieser traditionellen Techniken zu untersuchen, um ihre Vor- und Nachteile zu identifizieren. Diese Modelle werden miteinander verglichen, um ihre Funktionalität zu hinterfragen. Obwohl die Methodologie zur Evaluierung agentenbasierter Modelle unzureichend ist, wurde hier versucht, ein selbst-kalibriertes agentenbasiertes Modell für den Großraum Teheran zu erstellen. Einige Variablen, die in der Wirklichkeit die Zersiedelung im Studiengebiet kontrollieren, wurden durch Expertenwissen und ähnliche Studien extrahiert. Drei Hauptagenten, die mit der Ausbreitung von Städten zu tun haben, wurden definiert: Entwickler, Bewohner, Behörden. Jeder einzelne Agent beeinflusst Variablen; d.h. die Entscheidungen eines Agenten werden von einer Reihe realer Variablen beeinflusst. Das Verhalten der einzelnen Agenten wurde in einer GIS Umgebung kodiert und anschließend zusammengeführt, um einen Prototyp zur Simulation der Landnutzungsänderung zu erzeugen. Dieser Geosimulations-Prototyp ist in der Lage, die Quantität und die Lage von Landnutzungsänderungen insbesondere in der Umgebung von Teheran zu simulieren. Dieses agentenbasierte Modell zieht Nutzen aus der Stärke traditioneller Techniken wie etwa zellularen Automaten zur Änderungsallokation, Markow-Modellen zur Schätzung der Quantität der Änderung und einer Gewichtung der individuellen Faktoren. Eine detaillierte Diskussion der Implementierung der unterschiedlichen Methoden sowie eine Stärken-Schwächen-Analyse werden präsentiert und die Ergebnisse mit der tatsächlichen Situation verglichen, um die Modelle zu verifizieren. In dieser Arbeit wurden GIS Funktionen verwendet und zusätzliche Funktionen in Python programmiert. Diese Untersuchungen sollen Stadtplaner und Entscheidungsträger unterstützen, Städte und deren Ausbreitung zu simulieren.Land use/ cover change is a complex matter, which is caused by numerous biophysical, socio-economical and economic factors. An obvious form of land use change in the suburbs of the metropolis is defined as urban sprawl. There are a number of techniques to model this issue in order to investigate this topic. These models have been developed since the 1960s and are increasing in terms of quantity and popularity. Some of these models suffer from a lack of consideration of some significant variables. The traditional methods (e.g. Cellular Automata, the Markov Chain Model, the CA-Markov Model, and the Logistic Regression Model) have some inherent weaknesses in consideration of human activity in the environment. The particular significance of this problem is the fact that humans are the main actors in the transformation of the environment, and impact upon the suburbs due to their settlement preferences and lifestyle choices. The main aim of this thesis was to examine some of those traditional techniques in order to discover their considerable advantages and disadvantages. These models were compared against each other to challenge their functionality. Whereas there is a lack of methodology in evaluation of agent-based models, it was presumed to create a self-calibrated agent based model, by focussing on the Tehran metropolitan area. Some variables in reality control urban sprawl in the study area, which were extracted through the expert knowledge and similar studies. Three main agents, which deal with urban expansion, were defined: developers, residents, government. Each particular agent affects some variables, i.e. the agents‟ decisions are being influenced by a set of real variables. Agents‟ behaviours were coded in a GIS environment and, thereafter, the predefined agents were combined through a function to create a prototype for simulation of land change. This designed geosimulation prototype can simulate the quantity and location of changes specifically in the vicinity of the metropolis of Tehran. This customised agent-based model benefits from the strengths of traditional techniques; for instance, a Cellular Automata structure for change allocation, a Markov model for change quantity estimation and a weighting system to differentiate between the weights of the driving factors. A detailed discussion of each methodology implementation, and their weakness and strengths, is then presented, specifically comparing results with the reality to verify the models. In this research, we used only the GIS functionalities within GIS environments and the required functions were coded in the Python engine. This investigation will help urban planners and urban decision-makers to simulate cities and their movements over time

Land Use Dynamics and Implications for Water Management in the Urbanizing Wasatch Range Metropolitan Area of Utah

Utah is one of the fastest growing states in the USA. Utah’s Wasatch Range Metropolitan Area (WRMA), where 80% of Utah’s population resides, is growing at unprecedented rates and has seen extensive urban landscape transformation in the last half century. Many of Utah’s agricultural lands, grasslands, and wetlands have been transformed into urban areas during this time. Local residents have watched and experienced these changes to their local environment, but without a clear understanding of the processes and impacts of urbanization. It is not until we study these landscapes from a spatial perspective and the time scale of decades that we can begin to measure the changes that have occurred and predict the impact of changes to come if current trajectories continue. In this dissertation research I worked with my research colleagues to provide a comprehensive analysis of the WRMA’s past land use changes and future land use trends. In doing so, we: (1) measured the rate, the magnitude, and the process of past urban growth; (2) compared the changes of irrigated agricultural lands and non-irrigated agricultural lands in relation to urban development; and, (3) predicted how future urban growth could occur under various policy scenarios. We found that several counties at the heart of the WRMA have reached the limits of their capacity for future urban expansion. Thus, increasing urban density and land use efficiency will be key aspects of addressing the WRMA’s future growth. Also, variations of growth trends exist among and within the ten counties located in the WRMA, so it is necessary to develop contextualized and localized growth management plans. Furthermore, past land use dynamics prove that irrigated agricultural lands are more affected by urbanization than non-irrigated agricultural lands, with evidence of increasing agricultural lands fragmentation. Agricultural lands have been and will likely continue to be the major land source for future urban development. Utah’s public has indicated it wants to preserve agricultural lands to maintain open space and preserve cultural heritage, but this will require political attention and actions focused on areas where these lands are particularly vulnerable in the face of urban growth trajectories. The overall dissertation provides quantitative measurement of Utah’s urban landscape transformation and a science-based foundation for crafting successful land use policies to help guide future growth of the WRMA