Hyperspectral and multispectral remote sensing for mapping grassland vegetation

Sammanfattning: Popular Abstract in English European dry extensive grasslands are biodiversity hotspots which are severely threatened by land use intensification and abandonment. In order to plan efficient conservation actions it is necessary to collect information on the current status of grasslands, their species diversity and prevailing environmental conditions. Remote sensing technology in combination with ground surveys provides an effective tool to monitor ecosystem properties continuously across the landscape with high spatial precision in a repeatable way. In this thesis, the potential of hyper-and multispectral remote sensing imagery to predict grassland ecological parameters, such as grazing continuity, plant species diversity and habitat environmental conditions was evaluated studying grassland sites on the Baltic island of Öland, Sweden. Different methods were compared on the basis of their prediction quality and practical feasibility. The findings of this thesis provide a useful guidance for the selection of prediction methods of ecological grassland parameter in future studies. Combined with ground surveys, remote sensing can serve as time-efficient decision support tool for prioritising areas of high conservation value for management actions.