Hyperspectral Remote Sensing for Sustainable Agriculture explores how artificial intelligence and machine learning are transforming Earth Observation and remote sensing. The book focuses on improving the analysis of satellite and hyperspectral imagery through automated, accurate, and scalable methods for environmental and agricultural applications.
It introduces key concepts in Earth Observation and AI, followed by techniques for image preprocessing, classification, feature extraction, and change detection. Application-driven chapters highlight real-world uses in agriculture, forest monitoring, climate studies, disaster management, and environmental assessment. The book combines theoretical understanding with practical workflows, making complex concepts accessible and applicable.
Key Features:
-Introduces AI applications in remote sensing and Earth Observation
-Covers hyperspectral and multispectral image analysis techniques
-Provides practical workflows for classification, feature extraction, and change detection
-Real-world applications in agriculture, climate studies, and environmental monitoring
-Insights into emerging trends such as automated EO pipelines and New Space data
eBook - ePub
Hyperspectral Remote Sensing for Sustainable Agriculture
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Hyperspectral Remote Sensing for Sustainable Agriculture
About this book
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Table of contents
- Welcome
- Table of Contents
- Title
- BENTHAM SCIENCE PUBLISHERS LTD.
- PREFACE
- List of Contributors
- Advancing Smart Irrigation Practices in Small-Scale Agriculture by Combining Hyperspectral Remote Sensing with IoT Solutions
- Land Cover Classification Using Hyperion EO-1 Data: A Case Study in Uttar Pradesh, India
- Emerging Trends and Challenges in Remote Sensing for Irrigation of Horticultural Crops
- Role of Remote Sensing and Geographic Information System (GIS) in Integrated Pest Management (IPM)
- A Smart IOT-Based Framework for Predictive Crop Health Monitoring and Precision Farming
- Precision Agriculture Practices for Crop Yield Management with AI Models
- Land Cover Classification in Bhatinda and Comparative Analysis of Machine Learning Algorithms Using Google Earth Engine
- Significance of Remote Sensing in Optimizing Fertilizer Use for Nutrient Mapping
- Study on Harnessing Remote Sensing for Advanced Wildlife Monitoring and Conservation
- Advancement in Remote Sensing and GIS for Sustainable Groundwater Monitoring
- Precision Agriculture, Irrigation Management, and Monitoring using Hyperspectral Remote Sensing and AI
- Evaluation of Soil Fertility Using Deep Learning and Machine Learning Algorithms
- Advanced Remote Sensing Techniques for Monitoring Agricultural Changes
- Remote Sensing for Precision Agriculture: Optimizing Fertilizer Use through Nutrient Mapping
- Smart Irrigation Systems: A Review of Current Trends and Future Prospects
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Yes, you can access Hyperspectral Remote Sensing for Sustainable Agriculture by Sartajvir Singh,Neelam Dahiya,Maged Mohammed in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Vision & Pattern Recognition. We have over 1.5 million books available in our catalogue for you to explore.