Classifiers vs. input variables - The drivers in image classification for land cover mapping.
Michael HeinlJanette F. WaldeGottfried TappeinerUlrike TappeinerPublished in: Int. J. Appl. Earth Obs. Geoinformation (2009)
Keyphrases
- input variables
- land cover
- image classification
- remotely sensed data
- supervised classification
- variable selection
- remote sensing
- artificial neural networks
- multispectral
- change detection
- remote sensing images
- remote sensing data
- satellite images
- fuzzy rules
- neural network model
- geographic information systems
- membership functions
- image representation
- bag of words
- support vector
- feature extraction
- image features
- feature selection
- training data
- number of input variables
- cross validation
- decision trees
- training set
- neural network
- unsupervised learning
- high resolution
- high dimensional
- pairwise
- data sets
- high dimensional data
- hyperspectral
- fuzzy sets
- supervised learning
- image analysis
- urban areas
- clustering algorithm
- image processing