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Digital Agriculture Laboratory
Digital Agriculture Laboratory
College of Agricultural and Environmental Sciences | College of Engineering
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RS Data Base
1- Data Base Content
2- Overview
3- Platforms
3.1. Unmanned Aerial Systems (UAS)
3.2.Manned Aircraft
3.3. Satellite
4- Sensors
4.1. RGB
4.2. Multispectral
4.3. Hyperspectral
4.4. Thermal
4.5. Lidar
4.6. Radar
4.7. Acoustic
5- Applications
5.1. Water Status
5.2. Disease control
5.3. Yield mapping and prediction
5.4. Nutrient management
5.5. Salinity
5.6. Phenotyping
6- Data processing and analysis
6.1. Preprocessing
6.1.1. Radiometric Calibration
6.1.2. Georeferencing
6.1.3. Mosaicing
6.1.4. Point cloud and Digital Surface Models
6.2. Processing
6.2.1. Noise removal and segmentation
6.2.2. Raw Feature Extraction
6.3. Analytics
6.3.1. Multicollinearity
6.3.2. Feature engineering and feature selection
6.3.3.Data mining
6.4. Regression\classification
7- Course of Action
Decision Support Tools
Radiative transfer Modeling
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