Remote Sensing and Digital Image Processing with R - Lab Manual

This Lab Manual is a companion to the textbook Remote Sensing and Digital Image Processing with R. It covers examples of natural resource data analysis applications including numerous, practical problem-solving exercises, and case studies that use the free and open-source platform R. The intuitive, structural workflow helps students better understand a scientific approach to each case study in the book and learn how to replicate, transplant, and expand the workflow for further exploration with new data, models, and areas of interest. a FeaturesAims to expand theoretical approaches of remote sensing and digital image processing through multidisciplinary applications using R and R packages.Engages students in learning theory through hands-on real-life projects.All chapters are structured with solved exercises and homework and encourage readers to understand the potential and the limitations of the environments.Covers data analysis in the free and open-source R platform, which makes remote sensing accessible to anyone with a computer.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 information.Undergraduate- and graduate-level students will benefit from the exercises in this Lab Manual, because they are applicable to a variety of subjects including environmental science, agriculture engineering, as well as natural and social sciences. Students will gain a deeper understanding and first-hand experience with remote sensing and digital processing, with a learn-by-doing methodology using applicable examples in natural resources.