Assessing and Predicting Changes of the Ecosystem Service Values Based on Land Use/Land Cover Changes With a Random Forest-Cellular Automata Model in Qingdao Metropolitan Region, China.
Xiaochuan QinBihong FuPublished in: IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. (2020)
Keyphrases
- cellular automata model
- urban growth
- random forest
- cellular automata
- land cover
- decision trees
- multispectral
- feature set
- ensemble methods
- environmental variables
- supervised classification
- multi label
- change detection
- remote sensing images
- remote sensing
- land cover classification
- geographic information systems
- pattern recognition
- training data
- traffic flow
- text categorization
- urban areas
- remote sensing data
- feature selection
- neural network
- data sets