Journal article

Publication year: 2016

Pages: 56-65

Journal: Mountain Research and Development

Volume number: 36

Issue number: 1

ISSN: 0276-4741

eISSN: 1994-7151

Open access status: Gold

DOI Link: https://doi.org/10.1659/MRD-JOURNAL-D-15-00064.1

Publisher: International Mountain Society (IMS)

Abstract: 

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.

Harvard Citation style: 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 Citation style: 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