Remote Sensing and Digital Image Processing with R - Lab Manual

<p>This Lab Manual is a companion to the textbook <i>Remote Sensing and Digital Image Processing with R</i>. 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. </p><p><strong>Features</strong></p><ul> <li>Aims to expand theoretical approaches of remote sensing and digital image processing through multidisciplinary applications using R and R packages.</li> <li>Engages students in learning theory through hands-on real-life projects.</li> <li>All chapters are structured with solved exercises and homework and encourage readers to understand the potential and the limitations of the environments.</li> <li>Covers data analysis in the free and open-source R platform which makes remote sensing accessible to anyone with a computer.</li> <li>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.</li> </ul><p>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.</p>