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Airborne laser scanning (ALS) has emerged as one of the most promising remote sensing technologies to provide data for research and operational applications in a wide range of disciplines related to management of forest ecosystems. This book provides a comprehensive, state-of-the-art review of the research and application of ALS in a broad range of forest-related disciplines, especially forest inventory and forest ecology. However, this book is more than just a collection of individual contributions – it consists of a well-composed blend of chapters dealing with fundamental methodological issues and contributions reviewing and illustrating the use of ALS within various domains of application. The reviews provide a comprehensive and unique overview of recent research and applications that researchers, students and practitioners in forest remote sensing and forest ecosystem assessment should consider as a useful reference text.
This guidance is designed to help those intending to use airborne laser scanning (ALS), also known as lidar, for archaeological survey. The aim is to help archaeologists, researchers and those who manage the historic environment to decide first, whether using lidar data will actually be beneficial in terms of their research aims, and second, how the data can be used effectively. The guidance will be most useful to those who have access to data that have already been commissioned, or are planning to commission lidar for a specific purpose. They also provide an introduction to data interpretation in order to separate archaeological and non-archaeological features. Although important themes are introduced, this guidance are not intended as a definitive explanation of the technique or the complexities of acquiring and processing the raw data, particularly as this is a still developing technology. This document is intended to complement 3D Laser Scanning for Heritage, which covers a wider range of uses of laser scanning for heritage purposes (Historic England 2018). This Guidance is a revision of The Light Fantastic: Using Airborne Lidar in Archaeological Surveypublished by English Heritage in 2010. The text has largely been maintained except for certain areas where major changes have occurred in the ensuing years. This is particularly true with regard to increased access to data and the wide range of visualisation techniques now available. The case studies have also been updated to reflect more recent survey activity and to include examples from outside Historic England.
LiDAR (or airborne laser scanning) systems became a dominant player in high-precision spatial data acquisition to efficiently create DEM/DSM in the late 90's. With increasing point density, new systems are now able to support object extraction, such as extracting building and roads, from LiDAR data. The novel concept of this project was to use LiDAR data for traffic flow estimates. In a sense, extracting vehicles over transportation corridors represents the next step in complexity by adding the temporal component to the LiDAR data feature extraction process. The facts are that vehicles are moving at highway speeds and the scanning acquisition mode of the LiDAR certainly poses a serious challenge for the data extraction process. The OSU developed method and its implementation, the I FLOW program, have demonstrated that LiDAR data contain valuable information to support vehicle extraction, including vehicle grouping and localizations. The classification performance showed strong evidence that the major vehicle categories can be efficiently separated. The I FLOW program is ready for deployment.
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.
Written by a team of international experts, this book provides a comprehensive overview of the major applications of airborne and terrestrial laser scanning. It focuses on principles and methods and presents an integrated treatment of airborne and terrestrial laser scanning technology. After consideration of the technology and processing methods, the book turns to applications, such as engineering, forestry, cultural heritage, extraction of 3D building models, and mobile mapping. This book brings together the various facets of the subject in a coherent text that will be relevant for advanced students, academics and practitioners.
LiDAR Principles, Processing and Applications in Forest Ecology introduces the principles of LiDAR technology and explains how to collect and process LiDAR data from different platforms based on real-world experience. The book provides state-of the-art algorithms on how to extract forest parameters from LiDAR and explains how to use them in forest ecology. It gives an interdisciplinary view, from the perspective of remote sensing and forest ecology. Because LiDAR is still rapidly developing, researchers must use programming languages to understand and process LiDAR data instead of established software. In response, this book provides Python code examples and sample data. Sections give a brief history and introduce the principles of LiDAR, as well as three commonly seen LiDAR platforms. The book lays out step-by-step coverage of LiDAR data processing and forest structure parameter extraction, complete with Python examples. Given the increasing usefulness of LiDAR in forest ecology, this volume represents an important resource for researchers, students and forest managers to better understand LiDAR technology and its use in forest ecology across the world. The title contains over 15 years of research, as well as contributions from scientists across the world. - Presents LiDAR applications for forest ecology based in real-world experience - Lays out the principles of LiDAR technology in forest ecology in a systematic and clear way - Provides readers with state-of the-art algorithms on how to extract forest parameters from LiDAR - Offers Python code examples and sample data to assist researchers in understanding and processing LiDAR data - Contains over 15 years of research on LiDAR in forest ecology and contributions from scientists working in this field across the world
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.