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Remote sensing assessment of the impact of the 2018 and 2019 droughts on the forests in The Netherlands

Boogaard, Else Linda (2021) Remote sensing assessment of the impact of the 2018 and 2019 droughts on the forests in The Netherlands.

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Abstract:Forests play an essential role for human society by providing provisioning, regulating and cultural services. Drought is one of the most damaging natural disasters that can cause huge losses to the forest ecosystem and society. Satellite imagery has been used in many countries in boreal and Mediterranean areas for assessing drought impact on forests, but so far not in oceanic climates. In this study, Landsat 8 and Sentinel-2 time series are used for deriving various vegetation indices to evaluate their ability in measuring impacts of droughts on forests in the Netherlands. Six vegetation indices (NDVI, EVI, RVI, DVI, NDMI, and SAVI) were compared on their correlation with droughts (Standardized Precipitation Index) using 170 forest points categorised by three forest types (broadleaved, coniferous, and mixed). NDMI and NVDI were found to be the vegetation indices that correlate strongest to periods of drought. An analysis of the full dataset showed an overall decrease in NDMI and NDVI during the summer of drought-year 2018, but on a yearly scale this difference is not visible. An analysis of the variation between the forest types was inconclusive: while the forest types were found to have different yearly cycles, neither of the forest types had significantly different NDMI or NDVI values than the other forest types in 2018. Similarly, the analysis of the variation between soil types was also inconclusive, partly as a consequence of lack of available data to do an unbiased analysis to separate the forest type and soil type factor. This study shows that remotely sensed vegetation index analysis is currently not a feasible method for assessing drought impact on forests in the Netherlands, as the results are inconclusive and do not confirm the ground-based findings. Future research will require larger time series or will need to combine datasets to create a dataset of sufficient temporal and spatial resolution to understand how Dutch forest respond to periods of drought, which are predicted to increase in the coming decade as a result of climate change.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Programme:Spatial Engineering MSc (60962)
Link to this item:https://purl.utwente.nl/essays/89003
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