Recursive Feature Elimination and Random Forest Classification of Natura 2000 Grasslands in Lowland River Valleys of Poland Based on Airborne Hyperspectral and LiDAR Data Fusion.
Luca DemarchiAdam KaniaWojciech CiezkowskiHubert PiórkowskiZuzanna Oswiecimska-PiaskoJaroslaw ChormanskiPublished in: Remote. Sens. (2020)
Keyphrases
- data fusion
- hyperspectral
- random forest
- hyperspectral data
- hyperspectral images
- decision trees
- remote sensing
- infrared
- multi sensor
- multispectral
- satellite images
- hyperspectral imagery
- fold cross validation
- feature ranking
- information fusion
- feature set
- cancer classification
- random forests
- image classification
- image data
- classification accuracy
- ensemble classifier
- image fusion
- support vector machine
- pattern recognition
- ensemble methods
- feature vectors
- base classifiers
- class labels
- feature extraction
- benchmark datasets
- high resolution
- feature selection
- classification models
- image analysis
- multi label
- ensemble learning
- text classification
- machine learning
- image segmentation
- neural network
- support vector
- fusion method
- gene expression data
- high dimensionality
- supervised learning
- naive bayes
- training samples