Analysis of the Impact of Species Composition, Projective Cover, and Phytomass of Vegetation in Arid Pasture Landscapes on Their Spectral Reflectance Properties Based on Ground Measurements

Abstract

The intensification of pasture degradation in the southern part of European Russia, which is caused by unfavorable hydrothermal conditions and unregulated livestock numbers, requires the development of approaches to assess the capacity of forage lands using Earth remote sensing methods. The spectral reflectance properties of vegetation are determined by its taxonomic, structural, phenological, biophysical, and biochemical characteristics. However, the patterns of how these parameters affect the spectral response are region-specific and heavily influenced by soil cover. Therefore, it is essential to expand the regional scope of studies on the spectral reflectance properties of various vegetation types. This research is devoted to determining the spectral reflectance properties of natural zonal pastures in southern European Russia, based on geobotanical investigations and field spectrometry using the PSR-1100f instrument within the 320–1100 nm range. Groundwork was carried out in May (the period of maximum green mass of vegetation) 2020–2022 in the territories of natural zonal pastures in Astrakhan and Volgograd oblasts, Stavropol krai, and the Republics of Dagestan and Kalmykia. Significant differences were found between feather grasses, semishrubs, and annuals in the visible and near-ultraviolet spectral regions. Changes in the projective cover, under other equal conditions, have the most significant impact on spectral properties in the 660–670 nm range, which is consistent with the results of other researchers. Vegetation indices were identified that are best suited for determining projective cover and above-ground biomass of pastures with various dominant species. Further research will enable transitioning from point measurements of spectral reflectance and structural vegetation characteristics to satellite data with different spatial resolutions.