This new textbook and lab manual on remote sensing and digital image processing of natural resources includes numerous practical problem-solving exercises and case studies that use the free and open-source platform R. It explains the basic concepts of remote sensing and its multidisciplinary applications using R language and R packages and engages students in learning theory through hands-on real-life projects. Features 1. Aims to expand theoretical approaches of remote sensing and digital image processing through multidisciplinary applications using R and R packages. 2. Engages students in learning theory through hands-on real-life projects. 3. All chapters are structured with solved exercises and homework and encourages readers to understand the potential and the limitations of the environments. 4. Covers data analysis in free and open-source (FOSS) R platform which makes remote sensing accessible to anyone with a computer. 5. 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. Students in upper-level undergraduate or graduate programs taking courses in Remote Sensing and Geoprocessing civil and environmental engineering geosciences and environmental sciences electrical engineering biology hydrology agricultural engineering as well as professionals in different areas who use remote sensing and image processing 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. . |Remote Sensing and Digital Image Processing with R - Textbook and Lab Manual | Environmental Engineering
