Vineyard water status estimation using multispectral imagery from an UAV platform and machine learning algorithms for irrigation scheduling management.
María RomeroYuchen LuoBaofeng SuSigfredo FuentesPublished in: Comput. Electron. Agric. (2018)
Keyphrases
- machine learning algorithms
- multispectral
- water resources
- digital elevation models
- image data
- remote sensing data
- water flow
- remote sensing
- benchmark data sets
- learning algorithm
- satellite images
- remote sensing images
- machine learning
- decision trees
- multispectral images
- satellite imagery
- water quality
- remotely sensed
- machine learning methods
- image analysis
- multi band
- hyperspectral
- random forests
- learning problems
- land cover
- precision agriculture
- machine learning approaches
- spectral bands
- high spatial resolution
- multispectral satellite images
- spatial resolution
- high resolution
- hyperspectral imagery
- hyperspectral data
- remotely sensed data
- learning models
- change detection
- spectral characteristics
- spectral images
- multispectral imaging
- computer vision
- real world
- data mining
- economic development
- visible spectrum
- urban areas
- infrared
- active learning
- feature space
- pattern recognition
- neural network
- standard machine learning algorithms