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- 2025
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Mark
Understanding the effects of Urban Green Spaces and Building Characteristics on Land Surface Temperature using multi-source geodata and Deep Learning
- Master (Two yrs)
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Mark
Street-level greenery mapping and urban heat modelling using deep learning and street view imagery
- Master (Two yrs)
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Mark
Environmental Drivers of Baltic Sea Fishing – A LSTM Spatio-Temporal Study
- Master (Two yrs)
- 2024
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Mark
Spatiotemporal dynamics of E-scooter sharing ridership and their associations with the built environment: A Swedish comparative study
(2024) In Master Thesis in Geographical Information Science GISM01 20242
Dept of Physical Geography and Ecosystem Science- Master (Two yrs)
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Mark
Utilizing AI to enhance monitoring of fishing activities via cooperative and non-cooperative methods
- Master (Two yrs)
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Mark
Predicting dust storm susceptibility: exploring control strategies with XGBoost models
- Master (Two yrs)
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Mark
Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods
- Master (Two yrs)
- 2023
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Mark
Multi-scale Bark Beetle Predictions Using Machine Learning
(2023) In Master Thesis in Geographical Information Science GISM01 20222
Dept of Physical Geography and Ecosystem Science- Master (Two yrs)
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Mark
A spatio-temporal graph neural network framework for predicting usage efficiency of e-scooter sharing services
- Master (Two yrs)
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Mark
Uncovering the spatial relationships between Covid-19 vaccine coverage and local politics in Sweden
(2023) In Master Thesis in Geographical Information Science GISM01 20232
Dept of Physical Geography and Ecosystem Science- Master (Two yrs)