Land Use and Land Cover Area Estimates From Class Membership Probability of a Random Forest Classification.
Marcio H. Ribeiro SalesSytze de BruinCarlos M. Souza Jr.Martin HeroldPublished in: IEEE Trans. Geosci. Remote. Sens. (2022)
Keyphrases
- class membership
- land cover
- random forest
- probability estimates
- land cover classification
- decision trees
- supervised classification
- remote sensing
- class labels
- decision boundary
- remote sensing images
- feature set
- multispectral
- probability estimation
- random forests
- change detection
- satellite images
- geographic information systems
- naive bayes
- cost sensitive
- ensemble methods
- base classifiers
- machine learning
- supervised learning
- multi label
- text classification
- support vector machine
- classification accuracy
- neural network
- training samples
- urban areas
- unsupervised learning
- feature selection
- image segmentation
- training set
- misclassification costs
- feature vectors
- knn
- machine learning algorithms
- class distribution
- image classification
- classification algorithm