Machine Learning Classification of Endangered Tree Species in a Tropical Submontane Forest Using WorldView-2 Multispectral Satellite Imagery and Imbalanced Dataset.
Colbert M. JacksonElhadi AdamPublished in: Remote. Sens. (2021)
Keyphrases
- multispectral
- satellite imagery
- remote sensing
- satellite images
- machine learning
- remotely sensed
- high spatial resolution
- land cover
- imbalanced datasets
- remote sensing images
- hyperspectral
- hyperspectral data
- change detection
- decision trees
- multispectral images
- hyperspectral images
- support vector machine
- machine learning methods
- pattern recognition
- spatial resolution
- image analysis
- remotely sensed images
- image data
- machine learning algorithms
- cost sensitive learning
- text classification
- rare class
- learning algorithm
- model selection
- feature selection
- supervised classification
- high resolution
- image classification
- support vector
- image processing
- active learning
- supervised learning
- feature vectors
- cost sensitive
- class imbalance
- training samples
- benchmark datasets
- classification trees
- classification accuracy
- urban areas
- classification models
- computer vision
- spatial databases