Quoc Bao Pham – författare

Machine Learning and AI Technology in Agricultural Applications offers a comprehensive overview of how artificial intelligence and machine learning are transforming the agricultural industry. By delving into image processing and advanced data analysis, the book demonstrates how technology addresses modern agricultural challenges, including climate change, urbanization, and increasing global populations. It emphasizes the importance of integrating sensors and data collection methods to generate vast pools of information, which can be efficiently analyzed through AI-driven solutions. The text lays a strong foundation for understanding the role of technological innovation in supporting sustainable and secure food production.Beyond introducing core machine learning models such as random forest, support vector machines, logistic regression, and decision trees, the book highlights the centralization of critical agricultural data in the cloud. This resource benefits both students and seasoned agricultural scientists, providing practical insights for optimizing crop yields, monitoring soil and weather conditions, and managing resources like fertilizers and pesticides. The book also explores the rapid analysis of complex datasets, empowering users to make informed, timely decisions in real-world agricultural scenarios.Connects core concepts of AI and ML to real-world application practices in agricultureExplores applications in crop scouting and optimizing variable rate crop inputDemonstrates the value in real or near real-time crop monitoring, yield estimation, and predictionHighlights SAR/optical data applications and analysis in agriculture

As climate change accelerates, so does the urgency to understand and address its unequal impacts. This book explores the uneven impacts of climate change and how it affects the lives and livelihoods of climate-disadvantaged communities by highlighting the specific challenges they face, such as heatwaves, droughts, flooding, health issues, and economic losses. It explains why vulnerable populations are more at risk due to factors such as lack of infrastructure, poverty, and limited access to resources. This book offers insights on conceptual frameworks to help vulnerable communities adapt and become more resilient to climate impacts. Real-life examples with challenges and actionable suggestions aim to inform policymakers and the public about the urgent need for targeted initiatives.Features:Provides a comprehensive examination of how marginalized groups, from indigenous populations in the Niyamgiri Hills to urban slum dwellers in Asia, are disproportionately affected by climate change and what can be done to mitigate these impacts.Includes practical examples from different countries to help understand the intersection between climate change and social inequality.Utilizes advanced technologies and provides cutting-edge tools such as geospatial maps and diagrams for modelling climate threats and predicting climate-related challenges.Provides a roadmap for more resilient and inclusive future strategies.Highlights interdisciplinary discussions and contributions by various stakeholders to reach different audiences and offer regional problem-solving opportunities.This book serves as a valuable resource for a wide audience, including climate scientists, geographers, ecologists, geologists, urban planners, environmentalists, research scholars, and policymakers engaged in the fields of environmental management, climate justice, and sustainable development. By featuring the voices and experiences of disadvantaged communities, this book contributes meaningfully to the ongoing debates of climate justice, sustainable development, and equitable adaptation pathways.

This book on the climate change, natural resources, landscape and agricultural ecosystems describes the contributing challenges related to natural resources, soil erosion, irrigation planning, water, landscape, sustainable crop yield agriculture and biomass estimation.

This book on the climate change, natural resources, landscape and agricultural ecosystems describes the contributing challenges related to natural resources, soil erosion, irrigation planning, water, landscape, sustainable crop yield agriculture and biomass estimation.