Digital mapping of soil landscape parameters : geospatial analyses using machine learning and geomatics This book addresses the mapping of soil landscape parameters in the geospatial domain. It begins by discussing the fundamental concepts and then explains how machine learning and geomatics can be applied for more efficient mapping and to improve our understanding and management of ‘soil’. The judicious utilization of a piece of land is one of the biggest and most important current challenges especially in light of the rapid global urbanization which requires continuous monitoring of resource consumption. The book provides a clear overview of how machine learning can be used to analyze remote sensing data to monitor the key parameters below at and above the surface. It not only offers insights into the approaches but also allows readers to learn about the challenges and issues associated with the digital mapping of these parameters and to gain a better understanding of the selection of data to represent soil landscape relationships as well as the complex and interconnected links between soil landscape parameters under a range of soil and climatic conditions. Lastly the book sheds light on using the network of satellite based Earth observations to provide solutions toward smart farming and smart land management. . Chapter 1. Concept of Digital Mapping Chapter 2. Different Approaches on Digital Mapping of Soil Chapter 3. Selection of Suitable Variables and Their Development Chapter 4. Digital Soil Mapping: Implementation and Assessment Chapter 5. Prediction Modelsfor Crop Mapping Chapter 6. Spatial Soil Moisture Prediction Model over an Agricultural Land.