Geo Environmental Hazards Using Ai Enabled Geospatial Techniques And Earth Observation Systems
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Geo-Environmental Hazards using AI-enabled Geospatial Techniques and Earth Observation Systems
Author: Tanupriya Choudhury
language: en
Publisher: Springer Nature
Release Date: 2024-05-26
This edited collection provides a comprehensive exploration of cutting-edge ideas, approaches, simulations, evaluations of risk, and systems that enhance the practicality of current geospatial technologies for reducing hazard risks. The various sections within this book delve into subjects such as the foundational principles of Earth Observation Systems (EOS) and geospatial methodologies. Additionally, the text serves as an advisory resource on the collaborative use of satellite-derived data and artificial intelligence to track and alleviate geo-environmental threats. The volume imparts extensive understanding regarding geo-environmental dangers and their analysis via EOS along with geospatial strategies. It encompasses key hazard-related themes including coastal degradation, predisposition to landslides, mapping vegetation coverages, tropical storm patterns, soil depletion due to erosion processes, vulnerability to rapid or extended flooding events, variations in oceansurface temperatures alongside chlorophyll-a levels; it also addresses assessments related to groundwater reserves and quality measures as well as sustainable management practices for watersheds that support community livelihoods—all through leveraging AI-integrated geospatial tools in conjunction with earth observation technologies. Furthermore, this work engages in discourse about systems designed for mitigating these ecological challenges sustainably. Scholars engaged in research activities; educational professionals; those involved in landscape design; engineers working at ground level; individuals responsible for policy-making—all who are concerned with geo-environmental hazards or associated domains—will find valuable insights within these pages.
Nutrition Controversies and Advances in Autoimmune Disease
Understanding the complex interplay between food safety, nutrition, bioscience, and data algorithms is crucial for effectively managing autoimmune diseases. However, the current literature often needs a comprehensive resource that integrates these disciplines, leaving researchers, clinicians, and industry professionals needing a clearer understanding of how to apply these concepts in practice. This gap in knowledge hinders the development of personalized nutrition plans and precision health interventions, ultimately limiting the effectiveness of autoimmune disease management strategies. Nutrition Controversies and Advances in Autoimmune Disease brings to the table more than a mere theoretical guide. It offers practical applications and case studies that bring to life the latest research and developments in the fields of food safety, nutrition, bioscience, and data algorithms. By integrating these disciplines, the book provides readers with the knowledge and tools to develop personalized nutrition plans and implement precision health interventions for autoimmune diseases, making it a valuable resource for anyone in the field.
Intelligent Business Analytics
This book explores the transformative role of soft computing methods in increasing business analytics, providing a comprehensive look into how these advanced methods can be applied to complex business data for meaningful insights. Through the integration of neural network, fuzzy logic, genetic algorithms, artificial intelligence, machine learning, deep learning, and other innovative approaches, Intelligent Business Analytics: Harnessing the Power of Soft Computing for Data- Driven Insights presents a roadmap for leveraging computational intelligence in diverse areas of business decision- making. Readers will venture from predictive analytics and customer segmentation to real- time decision support systems and many other applications. Soft computing’s flexibility and applicability in the handling of uncertainty, ambiguity, and dynamic data environments shine throughout the book. Each chapter is created to be a base of theory and, at the same time, provide an applied example, so the book is appropriate for students, researchers, and professionals in the field. This book also discusses where the markets are heading and new applications that are in store for intelligent analytics to create a competitive advantage that also supports sustainable growth. At the end, this book is for those who want to learn more about using data-driven approaches and those who are ready to face the changes of the fast-evolving digital world.