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Remote Sensing for Vegetation Monitoring : Technologies, Applications and Models
Remote Sensing for Vegetation Monitoring : Technologies, Applications and Models
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ISBN No.: 9780443330766
Year: 202610
Format: Trade Paper
Price: $ 240.68
Dispatch delay: Dispatched between 7 to 15 days
Status: Available (Forthcoming)

1. Introduction to Remote Sensing for Vegetation Monitoring Section 1: Conventional and Advanced Forest Ecosystem Monitoring 2. Surveying Techniques and Sampling Techniques in Forest Ecosystems 3. Crop Canopy Stress/Chlorophyll Estimation Using Drone or Thermal Sensors 4. Biophysical And Biochemical Analysis and Monitoring of Forest Ecosystems 5. Species-Level Classification Using Pixel Based and OBIA Object Based Approaches Drones in Vegetation and Surroundings Assessment 6. Mangroves Forests - Blue Carbon Places to Help Mitigate Climate Change 7. Multi-Source and Multi-Sensor Approaches in Forest Monitoring 8.


Forest Fire Analysis, Simulation and Modelling Using Advanced Techniques 9. Biophysical/Biochemical Parameter Retrieval from An Unmanned Autonomous Vehicle (UAV) 10. Forest Ecosystem Monitoring Summary Section 2: Agriculture and Grassland Monitoring 11. Crop Stress and Water Deficit Relationship Using Remote Sensing and Field Inventory Methods 12. Crop Yield Estimation and Modelling 13. Crop Damage Assessment Using Multi-Sensors and Multi-Source Remote Sensing Data 14. Artificial Intelligence Techniques in Grassland Monitoring 15. Establishment Of Relationships Between in Situ Measured Biophysical/Biochemical Parameters and Ground-Measured Data 16.


Agriculture and Grassland Monitoring Summary Section 3: Monitoring Urban Green Space and Mangrove Forests 17. Urban Discomfort Analysis and Urban Green Space Assessment 18. Urban Heat Islands - Can This Be Mitigated by Increasing Green Spaces? 19. Monitoring Urban Green Space and Mangrove Forests Summary Section 4: Advanced Modelling for Machine Learning / Artificial Intelligence 20. Hyperspectral Data for Quantification of Vegetation 21. Multi-Source and Machine Learning in Vegetation Classification 22. Data Fusion Technique and GUI Based Model in Vegetation Mapping and Monitoring 23. Deep Learning Techniques in Mangrove Forest Monitoring 24.


ML and Modelling Summary Section 5: Future Aspects and Challenges in Remote Sensing 25. Challenges And Emerging Applications in Vegetation Monitoring 26. Future Earth Observation Space Missions Devoted to Vegetation Monitoring for Sustainable Development Goals. 27. Summary of Future Challenges.


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