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This thesis addresses the challenging problems in creating 3D photorealistic building models using mobile LiDAR and images. We focus on ground-based sensing techniques, consisting of two stages. In the first stage, I present two new methods using either images or mobile LiDAR data alone for 3D urban modeling. The limitations of using each data alone are discussed, which leads to the sensor fusion research in the next phase. In the second stage, I introduce methodologies to maximize the synergy by fusing images and mobile LIDAR for upsampling range data towards the goal of generating 3D photorealistic urban models. There are fundamental research challenges involved in each stage of this work. In the first stage, I address the ill-posed problem of how much 3D information we can infer from single images. Proposed is a new model-based approach to 3D building reconstruction from single images. This method does not require model-to-image projection and readjustment ...
Compared with traditional remote sensing technologies, airborne Lidar data can provide researchers with additional 3D positional information, which is a key factor for advanced urban research, and particularly that of urban landscape ecology. Therefore, the need for applying Lidar data to a variety of disciplines is rapidly growing. However, the lack of remote sensing background makes the wider use of Lidar data highly difficult for scholars from other disciplines. In contrast to the majority of Lidar-related books that focus on sophisticated principles and general applications of Lidar data, this book provides the reader with a feasible framework for applying airborne Lidar data to urban research. In addition to providing a general introduction to the subject, this book explains in detail a series of case studies to demonstrate how these theoretical models can be employed to address practical urban issues. As such, this book not only provides Lidar scholars with a series of specifically designed research methods, but will also serve to inspire scholars from other disciplines, such as geographers, urban planners, ecologists, and decision-makers, with a complete framework of potential application fields.
Urban Remote Sensing The second edition of Urban Remote Sensing is a state-of-the-art review of the latest progress in the subject. The text examines how evolving innovations in remote sensing allow to deliver the critical information on cities in a timely and cost-effective way to support various urban management activities and the scientific research on urban morphology, socio-environmental dynamics, and sustainability. Chapters are written by leading scholars from a variety of disciplines including remote sensing, GIS, geography, urban planning, environmental science, and sustainability science, with case studies predominately drawn from North America and Europe. A review of the essential and emerging research areas in urban remote sensing including sensors, techniques, and applications, especially some critical issues that are shifting the directions in urban remote sensing research. Illustrated in full color throughout, including numerous relevant case studies and extensive discussions of important concepts and cutting-edge technologies to enable clearer understanding for non-technical audiences. Urban Remote Sensing, Second Edition will be of particular interest to upper-division undergraduate and graduate students, researchers and professionals working in the fields of remote sensing, geospatial information, and urban & environmental planning.
More than half the world's population now lives in cities. Creating sustainable, healthy and aesthetic urban environments is therefore a major policy goal and research agenda. This comprehensive handbook provides a global overview of the state of the art and science of urban forestry. It describes the multiple roles and benefits of urban green areas in general and the specific role of trees, including for issues such as air quality, human well-being and stormwater management. It reviews the various stresses experienced by trees in cities and tolerance mechanisms, as well as cultural techniques for either pre-conditioning or alleviating stress after planting. It sets out sound planning, design, species selection, establishment and management of urban trees. It shows that close interactions with the local urban communities who benefit from trees are key to success. By drawing upon international state-of-art knowledge on arboriculture and urban forestry, the book provides a definitive overview of the field and is an essential reference text for students, researchers and practitioners.
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.
" TRB's National Cooperative Highway Research Program (NCHRP) Report 748: Guidelines for the Use of Mobile LIDAR in Transportation Applications presents guidelines for the application of mobile 3D light detection and ranging (LIDAR) technology to the operations of state departments of transportation. Mobile LIDAR uses laser scanning equipment mounted on vehicles in combination with global positioning systems (GPS) and inertial measurement units (IMU) to rapidly and safely capture large datasets necessary to create highly accurate, high resolution digital representations of roadways and their surroundings. " -- Publisher's description.
Urban spaces are being called upon to develop a capacity for resilience and sustainability in order to meet the major challenges they face. To achieve such a goal, a practical development framework must be implemented in order to take advantage of the technological innovations that characterize the field of construction and urban engineering. Today, multi-scale BIM is bringing about significant changes that are redefining the paradigms of urban management. It facilitates simulations of the sustainability of urban spaces with respect to several criteria; most notably relating to energy, the economy and the environment. Building Information Modeling for a Smart and Sustainable Urban Space proposes a theoretical and practical framework for implementing BIM models for the creation of sustainable and intelligent urban spaces. It addresses the issues of acquisition, modeling, interoperability, and BIM and GIS integration for the production of BIM models. Case studies are presented, providing a practical dimension that demonstrates the production process of the urban model and its contribution to multiscale simulations, particularly in real estate evaluation and urban renewal.
Due to the increasing availability of high-resolution remotely sensed imagery and detailed terrain surface elevation models, urban planners and municipal managers can now model and visualize the urban space in three dimensions. The traditional approach to the representation of urban space is 2D planimetric maps with building footprints, facilities and road networks. Recently, a number of methods have been developed to represent true 3D urban models. Those include panoramic imaging, Virtual Reality Modeling Language (VRML), and Computer-aided Design (CAD). These methods focus on aesthetic representation, but they do not have sufficient spatial query and analytical capabilities. This research evaluates the conventional approaches to 3D urban models, and identifies their advantages and limitations; GIS functionalities have been combined with 3D urban visualization techniques to develop a GIS-based urban modeling method; The algorithms and techniques have been explored to derive urban objects and their attributes from airborne LiDAR and high-resolution imagery for constructing and visualizing 3D urban models; and 3D urban models for the Texas A & M University (TAMU) campus and downtown Houston have been implemented using the algorithms and techniques developed in this research. By adding close-range camera images and highresolution aerial photographs as the texture of urban objects, effect of photorealism visualization has been achieved for walk-through and fly-through animations. The Texas A & M University campus model and the downtown Houston model have been implemented to offer proof-of-concept, namely, to demonstrate the advantages of the GIS-based approach. These two prototype applications show that the GIS-based 3D urban modeling method, by coupling ArcGIS and MultiGen- Paradigm Site Builder 3D software, can realize the desired functionalities in georeferencing, geographical measurements, spatial query, spatial analysis, and numerical modeling in 3D visual environment.
This book showcases the different ways in which contemporary forms of data analysis are being used in urban planning and management. It highlights the emerging possibilities that city-regional governance, technology and data have for better planning and urban management - and discusses how you can apply them to your research. Including perspectives from across the globe, it’s packed with examples of good practice and helps to demystify the process of using big and open data. Learn about different kinds of emergent data sources and how they are processed, visualised and presented. Understand how spatial analysis and GIS are used in city planning. See examples of how contemporary data analytics methods are being applied in a variety of contexts, such as ‘smart’ city management and megacities. Aimed at upper undergraduate and postgraduate students studying spatial analysis and planning, this timely text is the perfect companion to enable you to apply data analytics approaches in your research.