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Project properties |
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| Title | A soil-landscape modelling approach for understanding seasonal trends and anomalies in vegetation activity |
| Group | Soil Geography and Landscape |
| Project type | thesis |
| Credits | 30 |
| Supervisor(s) | Titia Mulder |
| Examiner(s) | Titia Mulder |
| Contact info | titia.mulder@wur.nl |
| Begin date | 2022/01/03 |
| End date | |
| Description | In this MSc thesis project, you aim to provide a more comprehensive understanding of the ecosystem drivers in relation to observed trends in vegetation activity over large extents, while taking into account local-scale variability within ecosystems. This can be done by modelling the mean annual cycle (MAC) of the normalized difference vegetation index (NDVI) using continuous data of local climate, soil and landscape properties. The model output can be used for attributing climate conditions and landscape characteristics to the MAC of NDVI, in a spatially explicit context. The modelled trends in time and space can also be used next to evaluate the relationship between the extreme warm and dry conditions reported in a specific year, vegetation anomalies and help to better understand ecosystem sensitivity.
For this research project we are looking for an ambitious and independent student who has affinity with soil-landscape modelling and is able to combine knowledge about soil properties, environmental conditions, climate and plant growth. The analysis will be done at a regional to continental scale and thus the student is expected to be able to work with and analyse large data sets. |
| Used skills | ArcGIS, R, spatial and temporal analysis |
| Requirements | |