Validation of Visually Interpreted Corine Land Cover Classes with Spectral Values of Satellite Images and Machine Learning.
Orsolya Gyöngyi VargaZoltán KovácsLászló BekoPéter BuraiZsuzsanna Csatáriné SzabóImre HolbSarawut NinsawatSzilárd SzabóPublished in: Remote. Sens. (2021)
Keyphrases
- satellite images
- land cover
- geographic regions
- machine learning
- multispectral
- remote sensing
- hyperspectral
- environmental variables
- land cover classification
- change detection
- satellite imagery
- remotely sensed images
- supervised classification
- multispectral images
- hyperspectral imagery
- remote sensing images
- satellite data
- spectral bands
- remotely sensed
- landsat tm
- high resolution
- remote sensing imagery
- remote sensing data
- high resolution satellite images
- hyperspectral images
- learning algorithm
- decision trees
- remotely sensed data
- digital elevation models
- spatial resolution
- pattern recognition
- data analysis
- reinforcement learning
- image analysis
- urban areas
- high spatial resolution
- supervised learning
- computer vision
- model selection
- data mining
- data sets
- data streams
- image processing
- text classification