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Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro
The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this st...
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| Autoren: | , , , , , , , , |
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| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
Philipps-Universität Marburg
2022
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| Online Zugang: | PDF-Volltext |
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PDF-Volltext| Signatur: |
urn:nbn:de:hebis:04-es2022-01589 |
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| Publikationsdatum: |
2022-09-01 |
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Erstveröffentlichung: Ziegler A, Meyer H, Otte I, Peters MK, Appelhans T, Behler C, Böhning-Gaese K, Classen A, Detsch F, Deckert J, Eardley CD, Ferger SW, Fischer M, Gebert F, Haas M, Helbig-Bonitz M, Hemp A, Hemp C, Kakengi V, Mayr AV, Ngereza C, Reudenbach C, Röder J, Rutten G, Schellenberger Costa D, Schleuning M, Ssymank A, Steffan-Dewenter I, Tardanico J, Tschapka M, Vollstädt MGR, Wöllauer S, Zhang J, Brandl R, Nauss T. Potential of Airborne LiDAR Derived Vegetation Structure for the Prediction of Animal Species Richness at Mount Kilimanjaro. Remote Sensing. 2022; 14(3):786. https://doi.org/10.3390/rs14030786 |
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28 (2024), 47 (2023), 4 (2022) |
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https://creativecommons.org/licenses/by/4.0 |
| Zugangs-URL: |
https://archiv.ub.uni-marburg.de/es/2022/0158 https://doi.org/10.3390/rs14030786 |