Evaluating Several Vegetation Indices Derived from Sentinel-2 Imagery for Quantifying Localized Overgrazing in a Semi-Arid Region of South Africa

• Published in: Remote sensing (Basel, Switzerland) Vol. 14; no. 7; p. 1720
• Main Authors: Harmse, Christiaan J., Gerber, Hannes, van Niekerk, Adriaan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-04-2022
• Subjects: Animal behavior; animal-landscape interactions; Arid environments; Arid zones; Camps; Farming; Global positioning systems; GPS; Grazing; grazing management; Imagery; Livestock; livestock movement; NDVI; Normalized difference vegetative index; Overgrazing; Pasture management; Productivity; Rain; Rangelands; Remote sensing; Resource utilization; Semi arid areas; Semi arid environments; Semiarid environments; Semiarid lands; Sentinel-2; Sheep; Spatial analysis; Spatial discrimination; Spatial resolution; Stocking rates; Sustainable development; Vegetation; Vegetation index; South Africa; Karoo
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs14071720

Rangeland monitoring aims to determine whether grazing management strategies meet the goals of sustainable resource utilization. The development of sustainable grazing management strategies requires an understanding of the manner in which grazing animals utilize available vegetation. In this study, we made use of livestock tracking, in situ observations and Sentinel-2 imagery to make rangeland scale observations of vegetation conditions in a semi-arid environment, to better understand the spatial relationships between vegetation conditions and sheep movement patterns. We hypothesized that sheep graze more selectively under low stocking rates—resulting in localized overgrazing. We also assessed the importance of image spatial resolution, as it was assumed localized effects of grazing will be best explained by higher resolution imagery. The results showed that livestock tend to congregate along drainage lines where soils are deeper. The findings demonstrate how the spatial analysis of remotely sensed data can provide a landscape-scale overview of livestock movement patterns. This study illustrates that high-resolution normalized difference vegetation index (NDVI) data can be used as a grazing management tool to determine the spatial variability of productive areas across the semi-arid Upper Karoo rangelands and identify preferred grazing areas.