An application of tree species classification using high-resolution remote sensing image based on the rough set theory.
Yi ZengShuang WangTianzhong ZhaoJing WangPublished in: Multim. Tools Appl. (2017)
Keyphrases
- remote sensing
- rough set theory
- high resolution
- rough sets
- remotely sensed
- decision rules
- rough fuzzy
- multi spectral images
- rule generation
- remote sensing images
- change detection
- multispectral
- hyperspectral images
- remote sensing imagery
- land cover classification
- hyperspectral
- satellite images
- hyperspectral data
- decision table
- satellite imagery
- high spatial resolution
- image processing
- rule extraction
- remote sensing data
- attribute reduction
- remotely sensed data
- automatic image registration
- image analysis
- pattern recognition
- image classification
- land cover
- satellite data
- data reduction
- spatial resolution
- knowledge discovery
- machine learning
- rough sets theory
- remote sensed images
- databases
- earth observation
- knowledge reduction
- discernibility matrix
- hyperspectral imagery
- supervised classification
- infrared
- data analysis
- high quality
- decision trees
- remotely sensed images
- equivalence relation
- information entropy
- multispectral images
- concept lattice
- tree structure
- feature space
- feature extraction