Testing the Contribution of Multi-Source Remote Sensing Features for Random Forest Classification of the Greater Amanzule Tropical Peatland.
Alex O. AmoakohPaul AplinKwame T. AwuahIrene Delgado-FernandezCherith MosesCarolina Peña AlonsoStephen KankamJustice C. MensahPublished in: Sensors (2021)
Keyphrases
- random forest
- remote sensing
- feature set
- multi source
- classification accuracy
- feature vectors
- decision trees
- change detection
- remote sensing images
- feature extraction
- feature selection
- remotely sensed
- multispectral
- feature space
- hyperspectral images
- hyperspectral
- image processing
- satellite images
- class labels
- ensemble classifier
- high resolution
- image analysis
- satellite imagery
- svm classifier
- image fusion
- feature subset
- support vector machine
- land cover
- information fusion
- image classification
- image features
- training set
- support vector
- machine learning
- multi label
- data fusion
- naive bayes
- pattern recognition
- machine learning methods
- unsupervised learning
- text classification
- semi supervised
- knowledge discovery
- artificial neural networks
- learning algorithm
- databases