This volume reviews key advances in precision agriculture technology and applications. Chapters summarise developments in monitoring techniques, including proximal crop and soil sensors and remote sensing technologies. The book then goes on to discuss how this information is processed to identify management zones and input targets. Chapters also assesses advances in delivery mechanisms such as variable rate application and targeted spray technologies. The final part of the book surveys the wide range of applications of precision agriculture, from controlled traffic farming to site-specific nutrient and water management. With its distinguished editor and international team of subject experts, this will be a standard reference for crop scientists and agronomists as well as all those concerned with improving the efficiency and sustainability of agriculture.

MATLAB (R) is used for a wide range of applications in geosciences, such as image processing in remote sensing, the generation and processing of digital elevation models, and the analysis of time series. This book introduces methods of data analysis in geosciences using MATLAB, such as basic statistics for univariate, bivariate and multivariate datasets, jackknife and bootstrap resampling schemes, processing of digital elevation models, gridding and contouring, geostatistics and kriging, processing and georeferencing of satellite images, digitizing from the screen, linear and nonlinear time-series analysis, and the application of linear time-invariant and adaptive filters. The revised and updated Third Edition includes ten new sections and has greatly expanded on most chapters from the previous edition, including a step by step discussion of all methods before demonstrating the methods with MATLAB functions. New sections include: Data Storage and Handling, Data Structures and Classes of Objects, Generating M-Files to Regenerate Graphs, Publishing M-Files, Distribution Fitting, Nonlinear and Weighted Regression, Color-Intensity Transects of Varved Sediments, and Grain Size Analysis from Microscope Images. The text includes numerous examples demonstrating how MATLAB can be used on data sets from earth sciences. All MATLAB recipes can be easily modified in order to analyse the reader's own data sets.