An agent-based simulation model for business reopenings in New Orleans post Hurricane Katrina

The empirical study of business responses to disasters is relatively scarce, despite that they are a fundamental part of the cities, providing services, jobs and, taxes that are essential for urban sustainability. This dissertation develops an agent-based simulation model to represent and understand the businesses reopening process in a dynamic environment in New Orleans after Hurricane Katrina. The objectives are two-fold: 1) To identify the main reopening predictors involved and estimate their relative importance through time, using an empirical data set collected from another study; 2) To represent the business reopening process through a computer simulation model, using the parameters derived from the first objective. The results show that businesses located in flooded areas had lower reopening probabilities, however the effect was significant only in the first nine months after the disaster. Larger businesses had better reopening probabilities than smaller ones, although this variable stopped being significant after six months. Variables associated with higher social vulnerability, such as percent non-white population and percent population under 18, had a negative effect on the business reopening probabilities at different points of time. The influence of neighboring firms using 1-km buffer was found significantly positive only immediately after the disaster; it became significantly negative one year after the disaster. The simulation model developed proved to mimic the reopening process at a suitable level. The model was used to simulate two scenarios: 1) First, the flood depth was reduced by 1 meter as a way to represent the implementation of measures designed to increase the buildings and infrastructure resistance to floods. The simulation results indicate that there are specific areas that would obtain greater benefit from these measures, however ten months after the disaster the effect of the measures tends to diminish. 2) Second, the spatial effects of aids were simulated by making a limited number of businesses in specific locations totally resilient to the disaster. The results indicate that the beneficial effect is influenced by variables such as business density and socio-economic conditions of the area. The positive effect is perceivable until four months after the disaster, after this point it diminishes

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

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

Housing and Community Development

Researchers in housing and community development design and evaluate policies regarding access to attractive, affordable and sustainable housing and improving the social, physical and economic infrastructure of communities, especially those in the urban core. Practitioners in this field confront political considerations, administrative guidelines and limited funding. Decision science can increase the efficiency and effectiveness of market-rate housing development and provide support for policy responses to issues such as affordable housing, race and class segregation, ineffective and/or inequitable economic development, and sustainable development. This research spans many disciplines, including systems modeling, urban economics, multi-criteria decision modeling, stochastic models and decision support systems, and is often interdisciplinary and applied in nature. A common thread in this work is the need to explicitly address the needs of multiple stakeholders, to capture the public and private nature of housing, and to incorporate best-available evidence regarding markets, policies and impacts of housing and community development. We describe the policy context for this work, review previous research through the lens of descriptive, prescriptive and decision support models, and identify important limitations to work in this area to date. We then describe diverse opportunities for research in this area that can address current policy concerns such as sustainable development, post-disaster reconstruction and individual and group decision support

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Spatial Distribution of Urban Territories at a Regional Scale: Modeling the Changjiang Delta’s Urban Network

The formation of ‘Urban Networks’ has become a wide-spread phenomenon around the world. In the study of metropolitan regions, there are competing or diverging views about management and control of environmental and land-use factors. Especially in China, these matters, regulatory aspects, infrastructure applications, and resource allocations, are important due to population concentrations and the overlapping of urban areas with other land resources. On the other hand, the increasing sophistication of models operating on iterative computational power and widely-available spatial information and techniques make it possible to investigate the spatial distribution of urban territories at a regional scale. This thesis applies a Scenario Cellular Automata (SCA) model to the case study of the Changjiang Delta Region, which produces useful and predictive scenario-based projections within the region, using quantitative methods and baseline conditions that address issues of regional urban development. The contribution of the research includes the improvement of computer simulation of urban growth, the application of urban form and other indices to evaluate complex urban conditions, and a heightened understanding of the performance of an urban network in the Changjiang Delta Region composed of big, medium, and small-sized cities and towns