This new textbook on remote sensing and digital image processing of natural resources includes numerous practical, problem-solving exercises, applications of sensors and satellite systems using remote sensing data collection resources, and emphasizes the free and open-source platform R. It explains basic concepts of remote sensing and multidisciplinary applications using R language and R packages, by engaging students in learning theory through hands-on, real-life projects. All chapters are structured with learning objectives, computation, questions, solved exercises, resources, and research suggestions.
Features
- Explains the theory of passive and active remote sensing and its applications in water, soil, vegetation, and atmosphere.
- Covers data analysis in the free and open-source R platform, which makes remote sensing accessible to anyone with a computer.
- Includes case studies from different environments with free software algorithms and an R toolset for active learning and a learn-by-doing approach.
- Provides hands-on exercises at the end of each chapter and encourages readers to understand the potential and the limitations of the environments, remote sensing targets, and process.
- Explores current trends and developments in remote sensing in homework assignments with data to further explore the use of free multispectral remote sensing data, including very high spatial resolution data sources for target recognition with image processing techniques.
While the focus of the book is on environmental and agriculture engineering, it can be applied widely to a variety of subjects such as physical, natural, and social sciences. Students in upper-level undergraduate or graduate programs, taking courses in remote sensing, geoprocessing, civil and environmental engineering, geosciences, environmental sciences, electrical engineering, biology, and hydrology will also benefit from the learning objectives in the book. Professionals who use remote sensing and digital processing will also find this text enlightening.
About the Author: Marcelo dr Carvalho Alves Dr. Alves is associate professor at the Federal University de Lavras, Brazil. His education includes master's, doctoral, and post-doctoral degrees in Agricultural Engineering at Federal University of Lavras, Brazil. He has varied research interests and has published on surveying, remote sensing, geocomputation and agriculture applications. He has over 20 years of extensive experience in data science, digital image processing and modeling using multiscale, multidisciplinary, multispectral and multitemporal concepts applied to different environments. Experimental field-sites included a tropical forest, savanna, wetland and agricultural fields in Brazil. His research has been pre- dominantly funded by CNPq, CAPES, FAPEMIG and FAPEMAT. Over the years, he has built up a large portfolio of research grants mostly relating to applied and theoretical remote sensing, broadly in the context of vegetation cover, plant diseases and related impacts of climate changes.
Luciana Sanches Dr. Sanches graduated with a degree in Sanitary Engineering from the Federal University of Mato Grosso, Brazil, a master's degree in Sanitation, Environment and Water Resources from the Federal University of Minas Gerais, a PhD in Road Engineering, Hydraulic Channels and Ports from Universidad de Cantabria, Spain, a post-doctorate degree in Environmental Physics, Brazil, and a post-doctorate degree in Environmental Sciences from the University of Reading, United Kingdom. She specialized in workplace safety engineering and in project development and management for the Municipal Water Resources Management by the National Water Agency. She is currently associate professor at the Federal University of Mato Grosso, and worked for more than 20 years in research on atmosphere-biosphere interaction, hydrometeorology in meant temporal-spatial scales with interpretation based in environmental modeling and remote sensing. She has been applying geomatics in teaching and research activities to support the interpretation of environmental dynamics.
