Machine learning approaches for rice crop yield predictions using time-series satellite data in Taiwan

Keyphrases

• Taiwan 100%
• Rice Yield 100%
• Machine Learning Approach 100%
• Normalized Difference Vegetation Index 100%
• Crop Yield Prediction 100%
• Time Series Satellite Data 100%
• Moderate Resolution Imaging Spectroradiometer (MODIS) 50%
• Error Value 50%
• Evaluation Model 50%
• Yield Prediction 50%
• Second Crop 50%
• First Crop 50%
• Mean Absolute Error 25%
• Support Vector Machine 25%
• Rice 25%
• Regression Analysis 25%
• Root Mean Square Error 25%
• Model Performance 25%
• Correlation Coefficient 25%
• Rice Production 25%
• Yield Statistics 25%
• Predictive Models 25%
• Machine Learning Techniques 25%
• Modeling Results 25%
• Crop Management 25%
• Boundary Effect 25%
• Random Forest 25%
• Relative Error 25%
• Data Preprocessing 25%
• Rice Yield Prediction 25%
• Government Yields 25%
• Cloud Cover 25%
• Heading Date 25%
• Food Crops 25%
• Policy Making 25%
• Mixed pixel 25%
• Agreement Index 25%

Agricultural and Biological Sciences

• Normalized Difference Vegetation Index 100%
• Moderate Resolution Imaging Spectroradiometer 50%
• Heading 50%
• Crop Management 25%
• Support Vector Machine 25%
• Food Crop 25%
• Cloud Cover 25%