Abstract:
The Tibetan Plateau suffers from progressive degradation caused by over-grazing due to improper live-
stock management, global climate change and herbivory from small mammals. Therefore, a robust
indicator system for rangeland degradation has to be developed and tested. This paper investigates local
patterns of degradation at two sites (Lake Namco and Mt. Kailash) in Xizang province (China) that are cov-
ered by vegetation types typical of a large portion of the plateau. The suitability of a two-indicator system
is analysed using hyperspectral field measurements, and its transferability to spaceborne data is tested.
The indicators are (1) land-cover fractions derived from linear spectral unmixing and (2) chlorophyll
content as a proxy for nutrient and water availability calculated using hyperspectral vegetation indices
and partial least squares regression. Because cattle remain near settlements overnight in the local semi-
nomadic pastoral system, it can be expected that grazing intensity is highest near the settlement and
declines with increasing distance. Therefore, we tested the effect of distance on both indicators using a
Spearman correlation analysis. The predicted chlorophyll content and land cover fractions of the indica-
tor system were in good agreement with field observations (correlation coefficients between 0.70 and
0.98). High correlations between distance from settlements and land-cover fractions at both study sites
demonstrated that the land-cover fraction is a reliable indicator for degradation. A positive correlation
between distance from settlements and photosynthetically active vegetation (PV) revealed over-grazing
patterns at the first site. Furthermore, the chlorophyll indicator was proven suitable because chlorophyll
concentration declined with increasing distance from settlements. This underlines the over-grazing pat-
tern because cattle excrement was the only external source of nutrients in the ecosystem and it was
positively correlated with grazing intensity. However, at the second site, we found a significant positive
effect of distance on the amount of photosynthetically non-active vegetation; no effect of distance on PV
and chlorophyll content was found. Therefore, no evidence of pasture degradation was detected at the
second site. Regarding the potential use of satellite data for degradation monitoring, we found that (1) the
land-cover indicator derived from multispectral data was more robust than using noise-filtered hyper-
spectral information and (2) the chlorophyll amount indicator was estimated from simulated EnMAP
data with low error rates. Because the proposed two-indicator system can be derived from multi- and
hyperspectral satellite data and combines site conditions and local plant cover, it provides a time-saving
and robust method to measure pasture degradation across large areas, assuming that respective satellite
data are available.
