Using the Random Forest Classification for Land Cover Interpretation of Landsat Images in the Prykarpattya Region of Ukraine.
Olha TokarOlena VovkLubov KolyasaSerhii HavryliukMykola KorolPublished in: CSIT (1) (2018)
Keyphrases
- random forest
- decision trees
- land cover
- feature set
- fold cross validation
- random forests
- land cover classification
- supervised classification
- classification accuracy
- multispectral
- decision tree learning algorithms
- feature extraction
- ensemble methods
- support vector
- feature vectors
- feature selection
- support vector machine svm
- feature space
- pattern recognition
- support vector machine
- image classification
- multi label
- change detection
- image data
- remote sensing images
- classification models
- benchmark datasets
- unsupervised learning
- remotely sensed data
- machine learning algorithms
- ensemble classifier
- machine learning methods
- machine learning
- supervised learning
- learning algorithm