Applicability of different vegetation indices for pasture biomass estimation in the north-central region of Mongolia

A dependable pasture biomass estimation is critical to prevent the pasture shortages for decision-makers at all levels in Mongolia. Remote sensing technology is expected to be capable of deriving such estimates. Therefore, in this study, we produced and compared linear regression models between above-ground pasture biomass and seven vegetation indices using close-range spectral measurements in the forest-steppe zone, which is one of six vegetation zones of Mongolia. The results indicated that the atmospherically resistant vegetation index (ARVI) (R-2 = 0.62; p < 0.001) showed the highest fit with above-ground biomass in this particular landscape. The dominant perennial grasses in the sampled areas were Stipa krylovii Roshev. and Artemisia frigida Willd., which are commonly grazed in the summer and winter. Therefore, we concluded that the ARVI is the most suitable candidate for estimating pasture biomass in a landscape similar to that widely found in north-central Mongolia. This research will be applicable for pasture monitoring and natural resource studies in Mongolia.

Automated summary

In this study, linear regression models between above-ground pasture biomass and seven vegetation indices were used, with the atmospherically resistant vegetation index (ARVI) showing the highest fit with above-ground biomass in the specific landscape of Mongolia. It was concluded that ARVI is the most suitable candidate for estimating pasture biomass in a landscape similar to that widely found in north-central Mongolia, which will be applicable for pasture monitoring and natural resource studies in Mongolia.