Journalartikel
Autorenliste: Wiesmair, M; Feilhauer, H; Magiera, A; Otte, A; Waldhardt, R
Jahr der Veröffentlichung: 2016
Seiten: 56-65
Zeitschrift: Mountain Research and Development
Bandnummer: 36
Heftnummer: 1
ISSN: 0276-4741
eISSN: 1994-7151
Open Access Status: Gold
DOI Link: https://doi.org/10.1659/MRD-JOURNAL-D-15-00064.1
Verlag: International Mountain Society (IMS)
In the Georgian Caucasus, unregulated grazing has damaged grassland vegetation cover and caused erosion. Methods for monitoring and control of affected territories are urgently needed. Focusing on the high-montane and subalpine grasslands of the upper Aragvi Valley, we sampled grassland for soil, rock, and vegetation cover to test the applicability of a site-specific remote-sensing approach to observing grassland degradation. We used random-forest regression to separately estimate vegetation cover from 2 vegetation indices, the Normalized Difference Vegetation Index (NDVI) and the Modified Soil Adjusted Vegetation Index (MSAVI(2)), derived from multispectral WorldView-2 data (1.8 m). The good model fit of R-2 = 0.79 indicates the great potential of a remote-sensing approach for the observation of grassland cover. We used the modeled relationship to produce a vegetation cover map, which showed large areas of grassland degradation.
Abstract:
Zitierstile
Harvard-Zitierstil: Wiesmair, M., Feilhauer, H., Magiera, A., Otte, A. and Waldhardt, R. (2016) Estimating Vegetation Cover from High-Resolution Satellite Data to Assess Grassland Degradation in the Georgian Caucasus, Mountain Research and Development, 36(1), pp. 56-65. https://doi.org/10.1659/MRD-JOURNAL-D-15-00064.1
APA-Zitierstil: Wiesmair, M., Feilhauer, H., Magiera, A., Otte, A., & Waldhardt, R. (2016). Estimating Vegetation Cover from High-Resolution Satellite Data to Assess Grassland Degradation in the Georgian Caucasus. Mountain Research and Development. 36(1), 56-65. https://doi.org/10.1659/MRD-JOURNAL-D-15-00064.1