1. Innovating landscape metrics on hexagonal grids

Landscape metrics are widely used discovering patterns, changes, and trends in urban and rural landscapes. Landscape…

2. Developing remote sensing-based indicators for soil organic carbon ML modeling

Large progress has been made over the last years to develop large-scale machine-learning approaches to model and predict…

3. Towards analysis ready data cube for machine learning under FAIR open science

Data Cubes are an idealized concept of preprocessed, same resolution, aligned, and stacked raster datasets to support…

4. A data observatory to explore multi-scale geographical relationships

The aim of this thesis topic is to apply spatial statistics and machine learning to a multi-resolution data cube, into…

5. Advancing web cartography

Base maps are widely used in spatial data visualisation. However, the existing base maps for Estonia based on the…

6. What really are Story Maps?

The thesis will explore on a methodological and epistemological level what are “story maps” and what story maps aim to…

7. Forest monitoring using remote sensing and chronosequences

The aim is to develop remote sensing based method for forest growth monitoring. The work will have a practical value for…

8. Automatic Segmentation of Landscape Elements from Orthophotos Using the samgeo Deep Learning Library

This thesis aims to evaluate the accuracy of the Python package segment-geospatial (samgeo) in the automatic…

9. Remote sensing forest clear cut detection

The aim is to develop quick clear cut detection based on SAR and optical remote sensing data in Estonia.

The topic is…

10. Suitability modelling for placing new landscape elements

The aim is to identify suitable areas for placing landscape elements (e.g. tree lines, riparian buffer strips) to the…

11. Diversity analysis of Estonian agricultural landscapes

The aim of this topic is to analyze the diversity of Estonian agricultural landscapes in GIS to assess the necessity of…