Machine learning assisted remote forestry health assessment: a comprehensive state of the art review

Keyphrases

• Machine Learning Techniques 100%
• Machine Learning 100%
• Forestry 100%
• Remote Monitoring 100%
• State-of-the-art Review 100%
• Comprehensive State 100%
• Health Assessment 100%
• Climate Change 50%
• Computational Resources 50%
• High Temperature 50%
• Late Development 50%
• Water Stress 50%
• Moisture Content Measurement 50%
• Forest Canopy 50%
• Robotic Platform 50%
• Forest Degradation 50%
• Nitrogen Estimation 50%
• Vegetation Parameters 50%
• AI Tools 50%
• Artificial Intelligence Techniques 50%
• Chlorophyll Index 50%

INIS

• forests 100%
• machine learning 100%
• assessments 100%
• reviews 100%
• forestry 100%
• monitoring 33%
• tools 16%
• water 16%
• climatic change 16%
• nitrogen 16%
• resources 16%
• chlorophyll 16%
• vegetation 16%
• canopies 16%
• data acquisition 16%
• vision 16%
• moisture 16%
• data processing 16%
• artificial intelligence 16%

Agricultural and Biological Sciences

• Forestry 100%
• Learning System 100%
• Machine Learning 100%
• Remote Sensing 66%
• Artificial Intelligence 66%
• Climate Change 33%
• Water Stress 33%
• Forest Canopy 33%
• Data Processing 33%
• Chlorophyll 33%