Model Selection in Atmospheric Remote Sensing with an Application to Aerosol Retrieval from DSCOVR/EPIC, Part 1: Theory.
Sruthy SasiVijay NatrajVíctor Molina GarcíaDmitry S. EfremenkoDiego G. LoyolaAdrian DoicuPublished in: Remote. Sens. (2020)
Keyphrases
- model selection
- remote sensing
- cross validation
- change detection
- remote sensing images
- multispectral
- image analysis
- hyperspectral
- hyperparameters
- parameter estimation
- high resolution
- model selection criteria
- mixture model
- remote sensing imagery
- image processing
- satellite images
- data assimilation
- digital image analysis
- high spatial resolution
- satellite imagery
- remote sensing data
- sample size
- motion segmentation
- automatic image registration
- hyperspectral remote sensing
- bayesian information criterion
- machine learning
- data sets
- remote sensed images
- selection criterion
- feature selection
- image fusion
- unsupervised learning
- land cover
- information criterion
- satellite data
- computer vision
- gaussian process
- image segmentation
- image data
- multi spectral images
- earth observation
- learning algorithm
- infrared
- marginal likelihood
- variable selection
- hyperspectral imagery
- earth science
- hyperspectral images