This book aims to promote the synergistic usage of advanced computational methodologies in close relationship to geospatial information across cities of different scales. A rich collection of chapters subsumes current research frontiers originating from disciplines such as geography, urban planning, computer science, statistics, geographic information science and remote sensing. The topics covered in the book are of interest to researchers, postgraduates, practitioners and professionals. The editors hope that the scientific outcome of this book will stimulate future urban-related international and interdisciplinary research, bringing us closer to the vision of a “new science of cities.”

Rapid population growth and climate change are driving urban renewal and urbanization at massive scales. New computational methods are needed to better support urban designers in developing sustainable, resilient, and livable urban environments. Despite the emergence of tools for mobility, public health, and environmental performance simulation, strategic urban design space exploration and multi-objective optimization of masterplans remain challenging due to a lack of generalizable methods for urban form generation. A variety of computational approaches have been proposed to facilitate the automatic generation of urban form. However, most of these developments have produced siloed tools and disconnected workflows. This research introduces a new generative urban design toolkit for rapid design space exploration and multi-objective optimization of masterplans that integrates with the Rhino/Grasshopper ecosystem of urban analysis and environmental performance simulation tools. We implement generative methods based on tensor fields. Tensor fields provide a generalized way to encode contextual constraints such as waterfront edges, terrain, view-axis, existing streets, landmarks, and non-geometric design inputs such as network directionality, desired densities of streets, amenities, buildings, and people as forces that the user can weigh. This allows users to generate various urban fabric configurations that resemble real-world cities with few inputs. Furthermore, this facilitates the sampling of complex parametric design solution spaces for multi-objective optimization while keeping dimensionality and computational overhead manageable. A series of case studies demonstrates flexibility, applicability and shows how modelers can identify design and environmental performance synergies that would be hard to find otherwise.

The classic work on the evaluation of city form. What does the city's form actually mean to the people who live there? What can the city planner do to make the city's image more vivid and memorable to the city dweller? To answer these questions, Mr. Lynch, supported by studies of Los Angeles, Boston, and Jersey City, formulates a new criterion—imageability—and shows its potential value as a guide for the building and rebuilding of cities. The wide scope of this study leads to an original and vital method for the evaluation of city form. The architect, the planner, and certainly the city dweller will all want to read this book.

Cities are home to more than half of the world population today and urbanization is one of this century's biggest drivers of global economic growth. The dynamics of the urban environment is thus an important question to investigate. In this thesis, techniques from statistical modeling, machine learning, data mining and econometrics are utilized to study digital traces of people's everyday lives. In particular, we investigated how people influence the economic growth of cities, as well as how the urban environment affect the decisions made by people. Focusing on the role of cities as centers of consumption, we found that a gravity model based on the availability of a large and diverse pool of amenities accurately explained human flows observed from credit card records. Investigation of the consumption patterns of individuals in Istanbul, Beijing and various metropolitan areas in the United States revealed a positive relationship between the diversity of urban amenities consumed and the city's economic growth. Taking the perspective of cities as hubs for information exchange, we modeled the interactions between individuals in the cities of Beijing and Istanbul using records of their home and work locations and demonstrated how cities which facilitate the mixing of diverse human capital are crucial to the flow of new ideas across communities and their productivity. This contributes to the body of evidence which supports the notion that efficient information exchange is the key factor that drives innovation. To investigate how urban environments shape people's decisions, we study the social influence city dwellers have on each other and showed how face-to-face interaction and information exchange across different residential communities can shape their behavior and increase the similarity of their financial habits and political views in Istanbul.

Papers presented at the CMEM 2017 conference form this book, which includes research from scientists, researchers and specialists who perform experiments, develop computer codes and carry out measurements on prototypes. A wide variety of topics related to new experimental and computational methods are explored.

Data, Matter, Design presents a comprehensive overview of current design processes that rely on the input of data and use of computational design strategies, and their relationship to an array of outputs. Technological changes, through the use of computational tools and processes, have radically altered and influenced our relationship to cities and the methods by which we design architecture, urban, and landscape systems. This book presents a wide range of curated projects and contributed texts by leading architects, urbanists, and designers that transform data as an abstraction, into spatial, experiential, and performative configurations within urban ecologies, emerging materials, robotic agents, adaptive fields, and virtual constructs. Richly illustrated with over 200 images, Data, Matter, Design is an essential read for students, academics, and professionals to evaluate and discuss how data in design methodologies and theoretical discourses have evolved in the last two decades and why processes of data collection, measurement, quantification, simulation, algorithmic control, and their integration into methods of reading and producing spatial conditions, are becoming vital in academic and industry practices.

This book collects ground-breaking works on the actual and potential impact of big data and data-integrated design for resilient urban environments, including human- and ecology-centred perspectives. Comprehending and designing for urban social, demographic and environmental change is a complex task. Big data, data structuring, data analysis (i.e. AI and ML) and data-integrated design can play a significant role in advancing approaches to this task. The themes presented in this book include urban adaptation, urban morphology, urban mobility, urban ecosystems, urban climate, urban ecology and agriculture. Given the compound nature of complex sustainability problems, most chapters address the correlation between several of these themes. The book addresses practitioners, researchers and graduate students concerned with the rapidly increasing role of data in developing urban environments.