University of Twente Student Theses
Deriving Data Stories from the GAEA Geospatial Tool
Braake, J. ter (2024) Deriving Data Stories from the GAEA Geospatial Tool.
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| Abstract: | This thesis describes how data from an Environmental Digital Twin of Cyprus (GAEA) can be turned into an insightful data story. By using an explorative method typical in data journalism, a subset of geospatial data was selected for study. These data were pre-processed via Python and used in QGIS to spatially align AI-derived Tree Classification data with the underlying soil, aspect, slope, and elevation. By achieving alignment between multiple data layers they could each be joined to the Tree Class data and prepared for further study. After obtaining descriptive statistics, various tests including Logistic Regression and Chi-2 were performed in order to identify and validate patterns in the data for the data story. These analyses showed highly significant result across all studied correlations, indicating that all classes of trees tended towards very distinct environmental preferences. In comparing the two types of pines prevalent on Cyprus: Brutia Pine (Pinus brutia) and Black Pine (Pinus nigra), the data story emphasizes their stark differences and points to potential implications for forestry. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 30 exact sciences in general, 38 earth sciences, 43 environmental science |
| Programme: | Creative Technology BSc (50447) |
| Link to this item: | https://purl.utwente.nl/essays/102086 |
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