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Data and code from: Satellite-derived NDVI predicts forage availability in a wild ungulate system: ground-truthing using field-collected live vegetation biomass

Butt, Shane1; Macphie, Kirsty1; Turner, Richard1; Morris, Sean1; Morris, Alison1; Pakeman, Robin2; Kruuk, Loeske1; Pemberton, Josephine1; Froy, Hannah1

Research facility: University of Edinburgh
Published Sep 30, 2026 on Dryad. https://doi.org/10.5061/dryad.bzkh189rd

Data files

Sep 30, 2026 version files 905.37 MB

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Abstract

Satellite-derived vegetation indices provide a powerful means to quantify habitat variation in long-term ecological studies, but their reliability as proxies for forage availability in wild herbivore populations remains underexplored. We used three decades of Landsat satellite imagery (1991–2023) to generate a 30 m resolution dataset of a proxy for annual vegetation greenness – the Normalised Difference Vegetation Index (NDVI) – for the Isle of Rum, Scotland, home to a long-term study of wild red deer (Cervus elaphus). We ground-truthed the NDVI data against live vegetation biomass data collected from calcareous grassland, which is preferred by the deer, and compared it with a coarser-resolution (500 m) MODIS Enhanced Vegetation Index (EVI) metric. Landsat NDVI was positively correlated with both live biomass and EVI, supporting its ecological relevance as a measure of forage availability. All three metrics have increased over the last three decades, indicating a long-term greening trend, with the higher resolution Landsat dataset revealing variation in the rate of change among vegetation groups, including grassland habitats preferred by deer. These findings suggest an increase in forage availability over time, which may have important consequences for the red deer on Rum. Our approach provides a transferable framework for integrating satellite data with individual-based field studies, demonstrating how remote sensing can enhance ecological inference in long-term wildlife research.