Big Data Analytics in Agriculture: Algorithms and Applications focuses on quantitative and qualitative assessment using state-of-the-art technology to provide practical improvements to agricultural production. The book provides a complete mapping—from data generation to storage to curation, processing and implementation/application—to produce high-quality reliable information for decision-making. It follows a logical pathway to demonstrate how data contributes to a converging flow of information towards a decision support system and how it can be transformed into actionable steps.The book develops ideas surrounding a strong integration of ICT and IoT to manage rural assets to deliver improved economic and environmental performance in a spatially and temporarily variable environment.
Vegetation Dynamics and Crop Stress: An Earth-Observation Perspective focuses on vegetation dynamics and crop stress at both the regional and country levels by using earth observation (EO) data sets. The book uniquely provides a better understanding of natural vegetation and crop failure through geo-spatial technologies. This book covers biophysical control of vegetation, deforestation, desertification, drought, and crop-water efficiency, as well as the application of satellite-derived measures from optical, thermal, and microwave domains for monitoring and modeling crop condition, agricultural drought, and crop health in contrasting monsoon/weather episodes.
Remote Sensing in Precision Agriculture: Transforming Scientific Advancement into Innovation compiles the latest applications of remote sensing in agriculture using spaceborne, airborne and drones’ geospatial data. The book presents case studies, new algorithms and the latest methods surrounding crop sown area estimation, determining crop health status, assessment of vegetation dynamics, crop diseases identification, crop yield estimation, soil properties, drone image analysis for crop damage assessment, and other issues in precision agriculture. This book is ideal for those seeking to explore and implement remote sensing in an effective and efficient manner with its compendium of scientifically and technologically sound information.
Unmanned Aerial Systems in Agriculture: Eyes Above Fields bridges the gap between knowledge of concept and real-world use and operations of UASs in agri-production. Based on a valuable combination of themes presented at the 13th European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) and supplemented by targeted invited articles of key-scientists, this book presents a full-spectrum view of the use of unmanned aerial systems (UAS) for agricultural applications. It integrates dispersed knowledge in the field, providing a holistic approach regarding UAVs and other UAS and their use in sustainable decisions. The integrated approach of the book provides a fresh look on contemporary agriculture-related issues, following precision farming approaches, by educating on a range of different issues of remote sensing and its use in agriculture. Furthermore, the operational planning aspects for UAS in agriculture focus part of the book provides information that is missing from other resources.
Precision Agriculture: Evolution, Insights and Emerging Trends presents a complete guide from foundational concepts to the economic, commercial and environmental implications of the approach. Showcasing recent research improvements, future trends, and highlighting innovative use of machine vision, artificial intelligence, UAVs, drones, IoT and data analytics to promote sustainable agriculture, the book brings the reader up-to-date with understanding and implementing this targeted practice. From the basic elements of agronomy to insights on reflectance and remote sensing indices, chapters use summary abstracts, case studies and real-world examples of implementing the tools of precision agriculture (PA) to demonstrate the latest advances. It includes explanations on the origin of the intra-plot variability of a culture (spatial and temporal), different types of existing sensors, controllers and site-specific management. The book further explores yield monitoring, weed, disease and pest control, automated irrigation systems, PA tools for variable rate application of inputs within the field, and data processing methods. By also exploring the economic profitability of precision farming approaches, and its utility for sustainable agriculture, Precision Agriculture: Evolution, Insights and Emerging Trends is a truly comprehensive view of this important approach to improving global agriculture production. Scientists, researchers, policymakers, graduate and postgraduate students, and engineers in the related fields of agriculture, computer science and engineering will benefit from this book.
AI, Edge, and IoT Smart Agriculture integrates applications of IoT, edge computing, and data analytics for sustainable agricultural development and introduces Edge of Thing-based data analytics and IoT for predictability of crop, soil, and plant disease occurrence for improved sustainability and increased profitability. The book also addresses precision irrigation, precision horticulture, greenhouse IoT, livestock monitoring, IoT ecosystem for agriculture, mobile robot for precision agriculture, energy monitoring, storage management, and smart farming. The book provides an overarching focus on sustainable environment and sustainable economic development through smart and e-agriculture. Providing a medium for the exchange of expertise and inspiration, contributions from both smart agriculture and data mining researchers around the world provide foundational insights. The book provides practical application opportunities for the resolution of real-world problems, including contributions from the data mining, data analytics, Edge of Things, and cloud research communities working in the farming production sector. The book offers broad coverage of the concepts, themes, and instruments of this important and evolving area of IOT-based agriculture, Edge of Things and cloud-based farming, Greenhouse IOT, mobile agriculture, sustainable agriculture, and big data analytics in agriculture toward smart farming. Â
Agricultural Internet of Things and Decision Support for Smart Farming reveals how a set of key enabling technologies (KET) related to agronomic management, remote and proximal sensing, data mining, decision-making and automation can be efficiently integrated in one system. Chapters cover how KETs enable real-time monitoring of soil conditions, determine real-time, site-specific requirements of crop systems, help develop a decision support system (DSS) aimed at maximizing the efficient use of resources, and provide planning for agronomic inputs differentiated in time and space. This book is ideal for researchers, academics, post-graduate students and practitioners who want to embrace new agricultural technologies.
This second edition of Working with Dynamic Crop Models is meant for self-learning by researchers or for use in graduate level courses devoted to methods for working with dynamic models in crop, agricultural, and related sciences. Each chapter focuses on a particular topic and includes an introduction, a detailed explanation of the available methods, applications of the methods to one or two simple models that are followed throughout the book, real-life examples of the methods from literature, and finally a section detailing implementation of the methods using the R programming language. The consistent use of R makes this book immediately and directly applicable to scientists seeking to develop models quickly and effectively, and the selected examples ensure broad appeal to scientists in various disciplines.