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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, Vol. 20, No. 3, pp. 176-192

Analysis of the influence of species composition, projective cover, and phytomass of arid landscape pasture vegetation on spectral reflectance properties based on ground measurements

S.S. Shinkarenko 1 , S.A. Bartalev 1 
1 Space Research Institute RAS, Moscow, Russia
Accepted: 15.05.2023
DOI: 10.21046/2070-7401-2023-20-3-176-192
The intensification of pasture degradation in the southern European part of Russia in recent years, caused by unfavorable hydrothermal conditions and unregulated livestock numbers, requires development of methods for determining the capacity of forage lands using remote sensing techniques. Spectral reflectance properties of vegetation are determined by its species, structural, phenological, biophysical, and biochemical characteristics. However, the influence of these indicators on spectral response has regional specificity, as soil cover plays a significant role. Therefore, it is important that studies of spectral reflectance properties cover many types of vegetation. This study is dedicated to determining the spectral reflectance properties of vegetation in natural zonal pastures in the southern European part of Russia based on geobotanical research and field spectrometry using the PSR 1100f instrument in the range of 320–1100 nm. Ground-based work was carried out in May (the period of maximum green vegetation mass) from 2020–2022 in the natural zonal pastures of the Astrakhan, Volgograd regions, Stavropol Krai, the Republics of Dagestan and Kalmykia. Significant differences were found between sod-forming grasses, semi-shrubs, and annual plants in the visible and near-ultraviolet ranges of the spectrum. Changes in projective cover under other equal conditions significantly affect spectral properties in the range of 660–670 nm, which is consistent with the results of other researchers. Vegetation indices were identified that are most suitable for determining projective cover and above-ground biomass of pasture phytocenoses dominated by different species. Further research will allow for the transition from point measurements of spectral reflectance and structural characteristics of vegetation to satellite data of various spatial resolutions.
Keywords: arid landscapes, pasture vegetation, spectrometry, vegetation indices
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