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...

Fuld beskrivelse

Gespeichert in:
Bibliografiske detaljer
Autoren: Ziegler, Alice, Meyer, Hanna, Otte, Insa, Peters, Marcell K., Appelhans, Tim, Detsch, Florian, Reudenbach, Christoph, Wöllauer, Stephan, Nauss, Thomas
Format: Artikel
Sprog:engelsk
Udgivet: Philipps-Universität Marburg 2022
Fag:
Online adgang:PDF-Volltext
Tags: Tilføj Tag
Ingen Tags, Vær først til at tagge denne postø!

Internet

PDF-Volltext

Detaljer om beholdninger fra
Klassifikationsnummer: urn:nbn:de:hebis:04-es2022-01589
Publikationsdatum: 2022-09-01
Quelle: 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
Downloads: 35 (2024), 47 (2023), 4 (2022)
Lizenz: https://creativecommons.org/licenses/by/4.0
Zugangs-URL: https://archiv.ub.uni-marburg.de/es/2022/0158
https://doi.org/10.3390/rs14030786