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Data Science in Agriculture and Natural Resource Management
This book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.
Soft Computing: Theories and Applications
The book focuses on soft computing and its applications to solve real-world problems in different domains, ranging from medicine and health care, to supply chain management, image processing and cryptanalysis. It includes high-quality papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2018), organized by Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India. Offering significant insights into soft computing for teachers and researchers alike, the book inspires more researchers to work in the field of soft computing.
Spatial Modeling in Forest Resources Management
This book demonstrates the measurement, monitoring, mapping, and modeling of forest resources. It explores state-of-the-art techniques based on open-source software & R statistical programming and modeling specifically, with a focus on the recent trends in data mining/machine learning techniques and robust modeling in forest resources. Discusses major topics such as forest health assessment, estimating forest biomass & carbon stock, land use forest cover (LUFC), dynamic vegetation modeling (DVM) approaches, forest-based rural livelihood, habitat suitability analysis, biodiversity and ecology, and biodiversity, the book presents novel advances and applications of RS-GIS and R in a precise and clear manner. By offering insights into various concepts and their importance for real-world applications, it equips researchers, professionals, and policy-makers with the knowledge and skills to tackle a wide range of issues related to geographic data, including those with scientific, societal, and environmental implications.
Land Cover and Land Use Change on Islands
Globalization is not a new phenomenon, but it is posing new challenges to humans and natural ecosystems in the 21st century. From climate change to increasingly mobile human populations to the global economy, the relationship between humans and their environment is being modified in ways that will have long-term impacts on ecological health, biodiversity, ecosystem goods and services, population vulnerability, and sustainability. These changes and challenges are perhaps nowhere more evident than in island ecosystems. Buffeted by rising ocean temperatures, extreme weather events, sea-level rise, climate change, tourism, population migration, invasive species, and resource limitations, islands...
Remote Sensing of Land Use and Land Cover
Filling the need for a comprehensive book that covers both theory and application, Remote Sensing of Land Use and Land Cover: Principles and Applications provides a synopsis of how remote sensing can be used for land-cover characterization, mapping, and monitoring from the local to the global scale. With contributions by leading scientists from aro
Pattern Recognition and Computer Vision
The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biom...
Landscape Dynamics of Drylands across Greater Central Asia: People, Societies and Ecosystems
This volume is a compilation of studies on interactions of changes in land cover, land use and climate with people, societies and ecosystems in drylands of Greater Central Asia. It explores the effects of collapse of socialist governance and management systems on land use in various parts of Central Asia, including former Soviet Union republics, Mongolia and northern drylands of China. Often, regional land-atmosphere feedbacks may have large global importance. Remote sensing is a primary tool in studying vast dryland territories where in situ observations are sporadic. State-of-the-art methods of satellite remote sensing combined with GIS and models are used to tackle science questions and p...
Google Earth Engine Applications
In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google E...
