Exploring zoning scenario impacts upon urban growth simulations using a dynamic spatial model

Dynamic spatial models are being increasingly used to explore urban changes and evaluate the social and environmental consequences of urban growth. However, inadequate representation of spatial complexity, regional differentiation, and growth management policies can result in urban models with a high overall prediction accuracy but low pixel-matching precision. Correspondingly, improving urban growth prediction accuracy and reliability has become an important area of research in geographic information science and applied urban studies. This work focuses on exploring the potential impacts of zoning on urban growth simulations. Although the coding of land-use types into distinct zones is an important growth management strategy, it has not been adequately addressed in urban modeling practices. In this study, we developed a number of zoning schemes and examined their impacts on urban growth predictions using a cellular automaton-based dynamic spatial model. Using the city of Jinan, a fast-growing large metropolis in China, as the study site, five zoning scenarios were designed: no zoning (S0), zoning based on land-use type (S1), zoning based on urbanized suitability (S2), zoning based on administrative division (S3), and zoning based on development planning subdivision (S4). Under these scenarios, growth was simulated and the respective prediction accuracies and projected patterns were evaluated against observed urban patterns derived from remote sensing. It was found that zoning can affect prediction accuracy and projected urbanized patterns, with the zoning scenarios taking spatial differentiation of planning policies into account (i.e., S2–4) generating better predictions of newly urbanized pixels, better representing urban clustered development, and boosting the level of spatial matching relative to zoning by land-use type (S1). The novelty of this work lies in its design of specific zoning scenarios based on spatial differentiation and growth management policies and in its insight into the impacts of various zoning scenarios on urban growth simulation. These findings indicate opportunities for the more accurate projection of urban pattern growth through the use of dynamic models with appropriately designed zoning scenarios. Keywords：urban growth simulation; zoning scenarios; cellular automaton models; spatial matching; prediction accurac

Data-driven modelling of biological multi-scale processes

Biological processes involve a variety of spatial and temporal scales. A holistic understanding of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript we review mathematical modelling approaches used to describe the individual spatial scales and how they are integrated into holistic models. We discuss the relation between spatial and temporal scales and the implication of that on multi-scale modelling. Based upon this overview over state-of-the-art modelling approaches, we formulate key challenges in mathematical and computational modelling of biological multi-scale and multi-physics processes. In particular, we considered the availability of analysis tools for multi-scale models and model-based multi-scale data integration. We provide a compact review of methods for model-based data integration and model-based hypothesis testing. Furthermore, novel approaches and recent trends are discussed, including computation time reduction using reduced order and surrogate models, which contribute to the solution of inference problems. We conclude the manuscript by providing a few ideas for the development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and Multiscale Dynamics (American Scientific Publishers

Scenarios of Urban Growth in Kenya Using Regionalised Cellular Automata based on Multi temporal Landsat Satellite Data

The exponential increase of urban areas in Africa during the last decade has become a major concern in the context of local climatic change and the increasing amount of impervious surface. Major African cities such as Nairobi and Nakuru have undergone rapid urban growth in comparison to the rest of the world. In this research we investigated the land-use changes and used the results in urban growth modelling which integrates cellular automata (CA), remote sensing (RS) and geographic information systems (GIS) in order to simulate urban growth up to the year 2030. We used multi-temporal Landsat imageries for the years 1986, 2000 and 2010 to map urban land-use changes in Nairobi and Nakuru. The use of multi-sensor imageries was also explored incorporating World view 2, and Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data for urban land-use mapping in Nakuru. We conducted supervised classification using support vector machine (SVM) which performed better than maximum likelihood classification. Land-use change estimates were obtained indicating increased urban growth into the year 2010. We used the land-use change analysis information to model urban growth in Nairobi and Nakuru. Our urban growth model (UGM) utilised various datasets in modelling urban growth namely urban land-use extracted from land-use maps, road network data, slope data and exclusion layer defining areas excluded from development. The Monte-Carlo technique was used in model calibration. The model was validated using Multiple Resolution Validation (MRV) technique. Prediction of urban land-use was done up to the year 2030 when Kenya plans to attain Vision 2030. Three scenarios were explored in the urban modelling process; unmanaged growth with no restriction on environmental areas, managed growth with moderate protection, and a managed growth with maximum protection on forest, agricultural areas, and urban green. Furthermore, we explored the spatial effects of varying UGM parameters using the city of Nairobi. The objective here was to investigate the contribution of each model parameter in simulating urban growth. The results obtained indicate that varying model coefficients leads to urban growth in different directions and magnitude. However, several model parameters were observed to be highly correlated namely; spread, breed and road. The lowest spatial effect was achieved by at least maintaining spread, breed and road while varying the other parameters. The highest spatial effect was observed by at least keeping slope constant while varying the other four parameters. Additionally, we used kappa statistics to compare the simulation maps. High values of Khisto indicated high similarity between the maps in terms of quantity and location thus indicating the lowest spatial effect obtained. Kenya plans to achieve Vision 2030 in the year 2030 and information on spatial effects of our UGM can help in identifying different scenarios of future urban growth. It is thus possible to discover areas that are likely to experience; spontaneous growth, edge growth, road influenced growth or new spreading centres growth. Policy makers can see the influence of establishing new infrastructure such as housing and road in new areas compared to existing settlements. Moreover, the outcome of this research indicates that Nairobi and Nakuru are experiencing fast urban sprawl with urban land-use consuming the available land. The results obtained illustrate the possibility of urban growth modelling in addressing regional planning issues. This can help in comprehensive land-use planning and an integrated management of resources to ensure sustainability of land and to achieve social equity, economic efficiency and environmental sustainability. Hence, cellular automata are a worthwhile approach for regional modelling of African cities such as Nairobi and Nakuru. This provides opportunities for other cities in Africa to be studied using UGM and its adaptability noted accordingly.Das exponentielle Wachstum afrikanischer Städte im letzten Jahrzehnt ist mit Blick auf die lokalen klimatischen Veränderungen und der zunehmenden Menge an versiegelten Oberflächen von besonderer Tragweite. Im Vergleich zu anderen Metropolen erfuhren afrikanische Städte wie Nairobi und Nakuru ein extensives Wachstum der urbanen Flächen. Die vorliegende Arbeit setzt sich mit dem urbanen Landnutzungswandel auseinander und modelliert die Siedlungsflächenausdehnung für das Jahr 2030 mit Hilfe eines Zellulären Automaten (CA), Fernerkundungsdaten (RS) sowie Geographischen Informationssystemen (GIS). Zur Kartierung der Siedlungsflächenausdehnung von Nairobi und Nakuru wurden multitemporale Landsat-Daten der Jahre 1986, 2000 und 2010 verwendet. Zusätzlich wurden multisensorale Daten von World View 2 und ALOS PALSAR für Nakuru eingesetzt. Die Landnutzungsklassifikation erfolgte mit support vector machines (SVM). Dieses Verfahren zeigte bessere Ergebnisse als eine Maximum-Likelihood-Klassifikation. Auf Basis der klassifizierten Satellitendaten erfolgte die Landnutzungsmodellierung für Nairobi und Nakuru. Hierzu wurde die von Goetzke (2011) modifizierte Version von Clarke’s Urban Growth Model (Clarke, Hoppen, & Gaydos, 1997) benutzt. Neben den Landnutzungskarten fungieren Informationen zum Verkehrsnetz, zur Hangneigung und zu Ausschlussflächen als Hauptinputdaten. Die Kalibration erfolgte mit Hilfe von Monte Carlo Iterationen. Zur Validation des Modells wurde eine Multiple Resolution Validation (MRV) durchgeführt. Die Siedlungsflächenausdehnung wurde für das Jahr 2030 simuliert. Zu diesem Zeitpunkt plant das Land Kenia die Umsetzung des Vision 2030 Programmes. Es wurden insgesamt drei Szenarien mit dem Wachstumsmodell gerechnet: (1) Wachstum ohne Planungszwänge, so dass auch Siedlungsflächen in Naturschutzgebieten entstehen dürfen. (2) Siedlungsflächenausdehnung unter moderaten Planungsbedingungen. (3) Wachstum mit sehr restriktiven Planungsbedingungen, unter Einschluss des Schutzes von Wald-, Grün- und- Agrarflächen. Des Weiteren wurde eine Sensitivitätsanalyse der modelleigenen Wachstumsparameter am Beispiel von Nairobi durchgeführt. Es konnte gezeigt werden, welchen Einfluss die Parameter auf die Intensität und das Muster der modellierten Siedlungsflächenausdehnung ausüben. Dabei zeigten die Wachstumskoeffizienten „spread“, „breed“ und „road“ eine signifikante Korrelation. Zur weiteren Analyse der erzielten Modellierungsergebnisse und zum Vergleich der räumlichen Muster wurden Kappa-Statistiken herangezogen. Die Arbeit sieht sich als Beitrag zum Vision 2030 Diskurs der kenianischen Regierung. Die simulierten Szenarien der Siedlungsflächenausdehnung von Nairobi und Nakuru identifizieren die für eine Urbanisierung wahrscheinlich in Frage kommenden Regionen. Die Studie zeigt zudem, dass sich die Siedlungsflächenausdehnung von Nairobi und Nakuru schnell und mit hohen Wachstumsraten vollzieht. Der Einsatz von CA Modellen ist ein wertvoller Ansatz zur regionalen Modellierung nicht nur von kenianischen sondern auch von afrikanischen Städten. Die Arbeit kann somit Entscheidungsträger aus Politik und Verwaltung unterstützen, indem sie die räumlichen Auswirkungen des zukünftigen Ausbaus der Infrastruktur und von Wohnflächen aufzeigt. Eine umfassende Planung von Landnutzungswandel und ein integriertes Management sind essentiell auf dem Weg zu einem bewussteren Umgang mit der Ressource Land sowie zu einer sozialen Gleichheit, wirtschaftlichen Effizienz und einer ökologischen Nachhaltigkeit

Comparing the structural uncertainty and uncertainty management in four common Land Use Cover Change (LUCC) model software packages

Research on the uncertainty of Land Use Cover Change (LUCC) models is still limited. Through this paper, we aim to globally characterize the structural uncertainty of four common software packages (CA_Markov, Dinamica EGO, Land Change Modeler, Metronamica) and analyse the options that they offer for uncertainty management. The models have been compared qualitatively, based on their structures and tools, and quantitatively, through a study case for the city of Cape Town. Results proved how each model conceptualised the modelled system in a different way, which led to different outputs. Statistical or automatic approaches did not provide higher repeatability or validation scores than user-driven approaches. The available options for uncertainty management vary depending on the model. Communication of uncertainties is poor across all models.Spanish GovernmentEuropean Commission INCERTIMAPS PGC2018-100770-B-100Spanish Ministry of Economy and Competitiveness and the European Social Fund [Ayudas para contratos predoctorales para la formacion de doctores 2014]University of Granada [Contratos Puente 2018]Spanish Ministry of Science and Innovation [Ayudas para contratos Juan de la Cierva-for-macion] 2019-FJC2019-040043University of Cape Town (Centre for Transport Studies

A probabilistic approach to risk management in mission-critical information technology infrastructure

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2008.Includes bibliographical references (p. 111-112) and index.In the nuclear, aerospace and chemical industries, the need for risk management is straightforward. When a system failure mode may cause a very high cost in lives or economic value, risk management becomes a necessity. In its short history, Information Technology (IT) came to be a crucial part and sometimes the platform of business activities for many large companies such as telecommunication or financial services organizations. However, due to scale and complexity, risk management methods used by other industries are not widely applied in IT.In this thesis, we investigate how probabilistic risk assessments methods used in other industries can be applied to IT network environments. A comparison is done using a number of possible approaches, improvements to these approaches are suggested, and different tradeoffs are discussed. The thesis examines ways to apply probabilistic risk assessment to a Service Oriented Architecture environment (where each service is an application or a business process that depends on other services, local and networked resources) to estimate the service reliability, availability, expected costs over time and the importance measures of elements and configurations. Finally, a method of performing cost benefit analysis is presented to estimate the implication of changing the services-supporting infrastructure, while taking into consideration the varying impact of different services to the business.A case study is used to demonstrate the methods suggested in the thesis. The case study compares four different configurations, showing how equipment failure and human error can be placed into a single framework and addressed as a single system. The implications and application of the results are discussed and recommendations for further research are provided.by Gadi Oren.S.M

Predicting the impact of lava flows at Mount Etna (Italy)

Forecasting the time, nature and impact of future eruptions is difficult at volcanoes such as Mount Etna, in Italy, where eruptions occur from the summit and on the flanks, affecting areas distant from each other. Nonetheless, the identification and quantification of areas at risk from new eruptions is fundamental for mitigating potential human casualties and material damage. Here, we present new results from the application of a methodology to define flexible high-resolution lava invasion susceptibility maps based on a reliable computational model for simulating lava flows at Etna and on a validation procedure for assessing the correctness of susceptibility mapping in the study area. Furthermore, specific scenarios can be extracted at any time from the simulation database, for land-use and civil defence planning in the long-term, to quantify, in real-time, the impact of an imminent eruption, and to assess the efficiency of protective measures

Exploring foundations for using simulations in IS research

Simulation has been adopted in many disciplines as a means for understanding the behavior of a system by imitating it through an artificial object that exhibits a nearly identical behavior. Although simulation approaches have been widely adopted for theory building in disciplines such as engineering, computer science, management, and social sciences, their potential in the IS field is often overlooked. The aim of this paper is to understand how different simulation approaches are used in IS research, thereby providing insights and methodological recommendations for future studies. A literature review of simulation studies published in top-tier IS journals leads to the definition of three classes of simulations, namely the self-organizing, the elementary, and the situated. A set of stylized facts is identified for characterizing the ways in which the premise, the inference, and the contribution are presented in IS simulation studies. As a result, this study provides guidance to future simulation researchers in designing and presenting findings

Reliability-based lifetime performance analysis of long-span bridges

2010 Fall.Includes bibliographical references.Long-span bridges generally serve as the significant hub in the transportation system for normal transportation and critical evacuation paths when any disaster happens. Thus, the safety and serviceability of long-span bridges are related to huge economic cost and safety of thousands of lives. The objective of this research is to establish a general framework to evaluate the lifetime performance of long-span bridges through taking account of more realistic load situations, such as traffic flow and wind environment. After some background information is introduced in Chapter 1, Chapter 2 covers the modeling of stochastic traffic flow for the bridge infrastructure system in a more realistic way by using the Cellular Automaton model. Based on the detailed information of individual vehicles of the stochastic traffic flow, the general framework to study Bridge/Traffic/Wind dynamic performance is developed in Chapter 3. Chapter 3 and Chapter 4 also report the results of the bridge's serviceability under normal and extreme loads events, respectively. In Chapter 5, the scenario-based fatigue model is further developed based on the dynamic framework developed in Chapter 3. Finally, the reliability-based analysis is conducted in Chapter 6 to study the fatigue damage caused by the coupling effects among bridge, traffic flow and wind throughout the bridge's service life