1. 2021 SWEDEN
- 1.1. Calculating landcover distribution & vegetation extraction
- 1.2. Compiling OTB from source
- 1.3. Observed and simulated internal variability climate feedbacks comparison.
- 1.4. Statistical comparison global gridded climate datasets and their influence on LPJ-GUESS model outputs
- 1.5. Emulating FLEXPART with a Multi-Layer Perceptron
- 1.6. Processing Elmer/Ice output
- 1.7. pan-Arctic classified slope and aspect maps (Geo computation only)
- 1.8. Seasonal Analisis of discharges in the Mälaren catchement.
- 1.9. Mapping of soil organic carbon stocks with Random Forest
- 1.10. NDVI Computation
- 1.11. Phase Change Analysis
- 1.12. Relationship between continental-scale patterns of fire activity and modes of climate variability
2. 2022 MATERA
- 2.1. Janusz Godziek: Damaged vs undamaged trees - Random Forest classification
- 2.2. Alonso Gonzalez: Stream Network Abstraction
- 2.3. Sebastian Walter: Images shadow removal
- 2.4. Jaime García: Modelling freshwater biodiversity: setting the scene, from geo-data to text-data
- 2.5. Maria Üblacker: Spectral clustering of freshwater habitats
- 2.6. Afroditi Grigoropoulou: Species Distribution Model with Random Forest
- 2.7. Gidske L. Andersen: Topographic and hydrological influence on vegetation in an arid environment
- 2.8. Yusdiel Torres-Cambas: Distribution of freshwater biodiversity across Cuba
- 2.9. Txomin Bornaetxea: Modeling debris flow source areas
- 2.10. Ritwika Mukhopadhyay: Comparative Analysis of the prediction of AGB using Random Forest Regression, Support Vector Machine for Regression & FeedForward Neural Network
- 2.11. Hyeyoung Sim: Clustering Electric Vehicle Charging Pattern with DTW and EV Charging energy demand Prediction with LSTM
- 2.12. Hemalatha Velappan: Classification of different tree species plantations using deep learning
- 2.13. Myriam Marending: Ships and economic activity: a starter
- 2.14. Florian Ellsäßer: Using a LSTM network and SHAP to determine the impact of drought and season on winter wheat