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Department of Physical Geography and Ecosystem Science, Sölvegatan 12, 223 62 Lund, Sweden
Sölvegatan 12, room 462c
Aim of my project is to test applicability of hyper-spectral remote sensing to detect species composition and trait diversity in semi-natural grasslands. Therefore I collected species information from 117 semi-natural grasslands plots in the Jordtorp area on the Baltic Island of Öland. And because age of these grasslands is a main driver for increasing species richness I spread the plots in grassland with different age (5-15a, 15-50a, >50a). During the same period hyper-spectral and multi-spectral data was collected from different resources (satellites, airborne, field spectrometer). Furthermore I got a compiled trait data database which covers 99% of all 240 found plant species.
- Möckel, T., Dalmayne, J., Prentice, H. C., Purschke, O., Schmidtlein, S. & Hall, K. (2014). Classification of grassland successional stages using airborne hyperspectral imagery. Remote Sensing, 6, 7732-7761. Multidisciplinary Digital Publishing Institute, MDPI.
- Dalmayne, J., Möckel, T., Prentice, H. C., Schmid, B. & Hall, K. (2013). Assessment of fine-scale plant species beta diversity using WorldView-2 satellite spectral dissimilarity. Ecological Informatics, 18, 1-9. Elsevier B.V.
Conference papers (2)
- Dalmayne, J., Möckel, T., Hall, K. & Prentice, H. C. (2012). High spatial resolution satellite data for monitoring fine-scale plant species spatial turnover in semi-natural grasslands. In Drees, C. & von Oheimb, G. (Eds.) (pp. 269-270), 42. Ecological Society of Germany, Austria and Switzerland.
- Möckel, T., Dalmayne, J., Purschke, O., Prentice, H. C. & Hall, K. (2012). Can hyperspectral remote sensing data be related to fine‐scale plant trait diversity in grasslands? . In Claudia, D. & Goddert, v. O. (Eds.) (pp. 270-270), 42. Ecological Society of Germany, Austria and Switzerland.
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Last update: 1/1/2000