Evaluation of Feature Selection Methods for Object-Based Land Cover Mapping of Unmanned Aerial Vehicle Imagery Using Random Forest and Support Vector Machine Classifiers.
Lei MaTengyu FuThomas BlaschkeManchun LiDirk TiedeZhenjin ZhouXiaoxue MaDeliang ChenPublished in: ISPRS Int. J. Geo Inf. (2017)
Keyphrases
- random forest
- land cover
- support vector machine classifiers
- unmanned aerial vehicles
- remote sensing data
- decision trees
- multispectral
- remote sensing
- remote sensing images
- feature set
- satellite images
- support vector machine
- change detection
- image data
- high resolution
- path planning
- image processing
- geographic information systems
- dynamic environments
- data sets
- multi label
- image analysis
- learning algorithm
- ensemble methods
- semi supervised