Soil Degradation, Desertification and Restoration

The book illustrates a Geospatial technology approach to data mining techniques, data analysis, modelling, risk assessment and visualization, and management strategies in many elements of soil degradation induced land degradation and desertification. This book delves into cutting-edge techniques based on open-source software and R statistical programming, Google Earth Engine, and modelling in modern artificial intelligence techniques, with a particular emphasis on recent trends in data mining techniques and robust modelling in land degradation crisis-related extreme event. This book will compile a collection of recent developments and rigorous applications of geospatial, geostatistical techniques and its application in the field of soil degradation induced land degradation and desertification. Techniques covered includes analytic hierarchy process (AHP), Multi-criteria decision making (MCDM), Logistic regression (LR), Evidential Belief function (EBF), supervised and unsupervised classification algorithms, artificial neural networks,(ANN) machine learning algorithms (MLA), support vector machines (SVM), fuzzy logic (FZ), radial basis function (RBF) networks, general regression neural networks (GRNN), probabilistic neural networks (PNN), mixture density networks (MDN), self-organizing maps (SOM), hybrid methods and computing.