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

Ideal for both undergraduate and graduate students in the fields of geography, forestry, ecology, geographic information science, remote sensing, and photogrammetric engineering, LiDAR Remote Sensing and Applications expertly joins LiDAR principles, data processing basics, applications, and hands-on practices in one comprehensive source. The LiDAR data within this book is collected from 27 areas in the United States, Brazil, Canada, Ghana, and Haiti and includes 183 figures created to introduce the concepts, methods, and applications in a clear context. It provides 11 step-by-step projects predominately based on Esri’s ArcGIS software to support seamless integration of LiDAR products and other GIS data. The first six projects are for basic LiDAR data visualization and processing and the other five cover more advanced topics: from mapping gaps in mangrove forests in Everglades National Park, Florida to generating trend surfaces for rock layers in Raplee Ridge, Utah. Features Offers a comprehensive overview of LiDAR technology with numerous applications in geography, forestry and earth science Gives necessary theoretical foundations from all pertinent subject matter areas Uses case studies and best practices to point readers to tools and resources Provides a synthesis of ongoing research in the area of LiDAR remote sensing technology Includes carefully selected illustrations and data from the authors' research projects Before every project in the book, a link is provided for users to download data

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.

Light detection and ranging (LIDAR) is an emerging remote-sensing technology with promising potential to assist in mapping, monitoring, and assessment of forest resources. Continuous technological advancement and substantial reductions in data acquisition cost have enabled acquisition of laser data over entire states and regions. These developments have triggered an explosion of interest in LIDAR technology. Despite a growing body of peer-reviewed literature documenting the merits of LIDAR for forest assessment, management, and planning, there seems to be little information describing in detail the acquisition, quality assessment, and processing of laser data for forestry applications. This report addresses this information deficit by providing a foundational knowledge base containing answers to the most frequently asked questions.

The treetops of the world's forests are where discovery and opportunity abound, however they have been relatively inaccessible until recently. This book represents an authoritative synthesis of data, anecdotes, case studies, observations, and recommendations from researchers and educators who have risked life and limb in their advocacy of the High Frontier. With innovative rope techniques, cranes, walkways, dirigibles, and towers, they finally gained access to the rich biodiversity that lives far above the forest floor and the emerging science of canopy ecology. In this new edition of Forest Canopies, nearly 60 scientists and educators from around the world look at the biodiversity, ecology, evolution, and conservation of forest canopy ecosystems. Comprehensive literature list State-of-the-art results and data sets from current field work Foremost scientists in the field of canopy ecology Expanded collaboration of researchers and international projects User-friendly format with sidebars and case studies Keywords and outlines for each chapter

Forest and fire ecology have long utilized remote sensing datasets to learn more about landscapes. Advances in gps spatial accuracy, GIS software capabilities, computing power, and remote sensing technology and software, as well as increases in the spatial and temporal resolution of remote sensing products, have made remote sensing a critical component of forest and fire ecology. Aerial light detection and ranging (LiDAR) is a fast-growing active remote-sensing technology that can be mined for detailed structural information about forests. These data are utilized in the fields of hydrology, forest ecology, silviculture, wildland fire ecology, wildlife ecology, and habitat modeling. LiDAR coverage has also become increasingly common, yet still contains much untapped potential. Despite widespread research that derived copious valuable metrics from aerial LiDAR, few of these metrics are available to managers due to a significant knowledge and software barrier for LiDAR processing. Even when LiDAR is utilized to derive more complex metrics by scientists and LiDAR experts, metrics are often predictions of plot-based data across the landscape. While these metrics are useful, LiDAR can offer so much more. Because it holds information about forest structure in 3 dimensions, new metrics can be derived that capture the full complexity of forest structure. I explore ways in which managers can use the plot network and data layers already available to them to derive large tree density, a metric that is critical for habitat modeling for many species, including the California spotted owl. I also explore the utility of LiDAR for estimating ladder fuels that carry fire from the ground into the canopy. Because there was no reliable method for quantifying these fuels, I also developed a plot-based methodology to collect these data. My dissertation work aims to increase LiDAR accessibility to managers and to develop new ways to use LiDAR to solve old problems. While there is much more work to be done, I am excited to share my work with LiDAR experts and forest managers, and hope that my findings improve the way we use LiDAR, the way we manage forests, and the way that we model and manage for wildland fire.