Combining Cygnss and Machine Learning for Soil Moisture and Forest Biomass Retrieval in View of the ESA Scout Hydrognss Mission.
Emanuele SantiMaria Paola ClariziaDavide ComiteL. DenteLeila GuerrieroNazzareno PierdiccaNicolas FlouryPublished in: IGARSS (2022)
Keyphrases
- machine learning
- soil moisture
- information retrieval
- pattern recognition
- information extraction
- information retrieval systems
- document retrieval
- multiresolution
- relevance feedback
- natural language processing
- text mining
- feature selection
- image retrieval
- feature vectors
- least squares
- co occurrence
- text classification
- test collection
- remote sensing
- computer vision