Prem C. Pandey, Shiv Nadar Institution of Eminence (Deemed to be University), Center for Environmental Sciences & Engineering, Greater Noida, India Paul Arellano, Michigan Technological University, College of Forest Resources and Environmental Science, Houghton, USA

• 1. Introduction to Forest Monitoring Using Advanced Remote Sensing Technology 2. Geospatial Perspectives of Sustainable Forests Management to Enhance Ecosystem Services and Livelihood Security 3. Distinguishing Carotene and Xanthophyll Contents in the Leaves of Riparian Forest Species by Applying Machine Learning Algorithms to Field Reflectance Data 4. Modelling of Abiotic Stress of Conifers with Remote Sensing Data 5. Retrieval of Mangrove Forest Properties Using Synthetic Aperture Radar 6. Photosynthetic Variables Estimation in a Mangrove Forest 7. Quantifying Carbon Stock Variability of Species within a Reforested Urban Landscape Using Texture Measures Derived from Remotely Sensed Imagery 8. Mapping Oil Palm Plantations in the Fringe of Sebangau National Park, Central Kalimantan, Indonesia 9. Forest Fire Susceptibility Mapping by Integrating Remote Sensing and Machine Learning Algorithms 10. Leveraging Google Earth Engine (GEE) and Landsat Images to Assess Bushfire Severity and Postfire Short-Term Vegetation Recovery: a Case Study of Victoria, Australia. 11. Recent Advancement and Role of Drones in Forest monitoring: Research and Practices 12. Applications of Multi-Source and Multi-Sensor Data Fusion of Remote Sensing for Forest Species Mapping 13. Challenges and Monitoring Methods of Forest Management through Geospatial Application 14. Challenges and Future Possibilities Towards Himalayan Forest Monitoring

Prem C. Pandey, Shiv Nadar Institution of Eminence (Deemed to be University), Center for Environmental Sciences & Engineering, Greater Noida, India Paul Arellano, Michigan Technological University, College of Forest Resources and Environmental Science, Houghton, USA

• 1. Introduction to Forest Monitoring Using Advanced Remote Sensing Technology 2. Geospatial Perspectives of Sustainable Forests Management to Enhance Ecosystem Services and Livelihood Security 3. Distinguishing Carotene and Xanthophyll Contents in the Leaves of Riparian Forest Species by Applying Machine Learning Algorithms to Field Reflectance Data 4. Modelling of Abiotic Stress of Conifers with Remote Sensing Data 5. Retrieval of Mangrove Forest Properties Using Synthetic Aperture Radar 6. Photosynthetic Variables Estimation in a Mangrove Forest 7. Quantifying Carbon Stock Variability of Species within a Reforested Urban Landscape Using Texture Measures Derived from Remotely Sensed Imagery 8. Mapping Oil Palm Plantations in the Fringe of Sebangau National Park, Central Kalimantan, Indonesia 9. Forest Fire Susceptibility Mapping by Integrating Remote Sensing and Machine Learning Algorithms 10. Leveraging Google Earth Engine (GEE) and Landsat Images to Assess Bushfire Severity and Postfire Short-Term Vegetation Recovery: a Case Study of Victoria, Australia. 11. Recent Advancement and Role of Drones in Forest monitoring: Research and Practices 12. Applications of Multi-Source and Multi-Sensor Data Fusion of Remote Sensing for Forest Species Mapping 13. Challenges and Monitoring Methods of Forest Management through Geospatial Application 14. Challenges and Future Possibilities Towards Himalayan Forest Monitoring

Prem C. Pandey, Shiv Nadar Institution of Eminence (Deemed to be University), Center for Environmental Sciences & Engineering, Greater Noida, India Paul Arellano, Michigan Technological University, College of Forest Resources and Environmental Science, Houghton, USA

• 1. Introduction to Forest Monitoring Using Advanced Remote Sensing Technology 2. Geospatial Perspectives of Sustainable Forests Management to Enhance Ecosystem Services and Livelihood Security 3. Distinguishing Carotene and Xanthophyll Contents in the Leaves of Riparian Forest Species by Applying Machine Learning Algorithms to Field Reflectance Data 4. Modelling of Abiotic Stress of Conifers with Remote Sensing Data 5. Retrieval of Mangrove Forest Properties Using Synthetic Aperture Radar 6. Photosynthetic Variables Estimation in a Mangrove Forest 7. Quantifying Carbon Stock Variability of Species within a Reforested Urban Landscape Using Texture Measures Derived from Remotely Sensed Imagery 8. Mapping Oil Palm Plantations in the Fringe of Sebangau National Park, Central Kalimantan, Indonesia 9. Forest Fire Susceptibility Mapping by Integrating Remote Sensing and Machine Learning Algorithms 10. Leveraging Google Earth Engine (GEE) and Landsat Images to Assess Bushfire Severity and Postfire Short-Term Vegetation Recovery: a Case Study of Victoria, Australia. 11. Recent Advancement and Role of Drones in Forest monitoring: Research and Practices 12. Applications of Multi-Source and Multi-Sensor Data Fusion of Remote Sensing for Forest Species Mapping 13. Challenges and Monitoring Methods of Forest Management through Geospatial Application 14. Challenges and Future Possibilities Towards Himalayan Forest Monitoring