Jalisco's multiclass land cover analysis and classification using a novel lightweight convnet with real-world multispectral and relief data.
Alexander QuevedoAbraham SánchezRaul NancláresDiana P. MontoyaJuan PachoJorge MartínezEduardo Ulises Moya-SánchezPublished in: CoRR (2022)
Keyphrases
- multispectral
- land cover
- remotely sensed data
- lightweight
- multi class
- remote sensing data
- image data
- satellite images
- land cover classification
- data sets
- remote sensing
- remotely sensed
- remote sensing images
- hyperspectral data
- multiclass classification
- remotely sensed images
- image analysis
- multiple classes
- satellite data
- data analysis
- satellite imagery
- change detection
- image classification
- support vector machine
- high spatial resolution
- spatial resolution
- supervised classification
- training data
- feature space
- multispectral images
- data mining
- data streams
- pattern recognition
- geographic information systems
- model selection
- text classification
- high dimensional
- support vector
- similarity measure
- feature selection
- multiclass support vector machines