Unmanned aircraft systems (UAS) are rapidly emerging as flexible platforms for capturing imagery and other data across the sciences. Many colleges and universities are developing courses on UAS-based data acquisition. Fundamentals of Capturing and Processing Drone Imagery and Data is a comprehensive, introductory text on how to use unmanned aircraft systems for data capture and analysis. It provides best practices for planning data capture missions and hands-on learning modules geared toward UAS data collection, processing, and applications.
FEATURES
Includes real-world environmental applications along with data interpretations and software used; exercises in chapters 8 through 19 have support materials for free download.
This book provides a general introduction to drones along with a series of hands-on exercises that students and researchers can engage with to learn to integrate drone data into real-world applications. No prior background in remote sensing, GIS, or drone knowledge is needed to use this book. Readers will learn to process different types of UAS imagery for applications (such as precision agriculture, forestry, urban landscapes) and apply this knowledge in environmental monitoring and land-use studies.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Amy E. Frazier is an Assistant Professor in the School of Geographical Sciences and Urban Planning at Arizona State University. She has over 10 years of experience in remote sensing data acquisition, processing, and analysis and has been working with UAS for the past 5 years. She holds her FAA Part 107 UAS Pilot’s license and has experience with both fixed wing and rotor aircraft. Most recently, she has been part of a multi-institutional team funded by the U.S. National Science Foundation that are developing systems and integrated sensors onboard UAS to better understand severe weather from formation through damage assessment.
Kunwar K. Singh
is a Geospatial Scientist at AidData research lab and an Affiliate Faculty in the Center for Geospatial Analysis at the College of William & Mary. He has extensive experience in remote sensing data acquisition, processing, and analysis, including the application of LiDAR (light detection and ranging) and UAS to measure, map, and model landscape characteristics and resources. His research focuses on land and vegetation dynamics and their impacts on natural resources.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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