Sensitivity of Landsat NDVI to subpixel vegetation and topographic components in glacier forefields: assessment from high-resolution multispectral UAV imagery

Recently, deglaciated landscapes are ideal natural arenas to investigate ecological succession processes. However, ground data acquisition remains complicated as glacier forefields are often difficult to access and fieldwork possibilities remain limited. Remote sensing offers an opportunity to bypass this issue and increase spatial and temporal coverage of ecological parameters. The Landsat satellites (5 to 8) provide reflectance data for the past 40 years, which align with recent phenomena of glacier retreat and related ecological and geomorphological dynamics in glacier forefields. Difficulties remain as information retrieved from 30-m Landsat pixels are the result of a mixture of objects influencing reflectance signals. Here, we used a submeter multispectral unmanned aerial vehicle (UAV) image of the Glacier noir foreland, France, to assess the sensitivity of Landsat normalized difference vegetation index (NDVI) to subpixel vegetation and topographic components. We found a twofold linear relationship (a = 0.456) and high sensitivity between fractional vegetation cover (FVC) and Landsat NDVI with detection of low vegetation changes (FVC > 5%) at low NDVI values (<0.1) (F-score = 0.75). We also showed that vegetation height and subpixel topographic heterogeneity leads to misestimation of vegetation cover as quantified by Landsat NDVI. Overall, our comparative analysis using very-high resolution UAV imagery provides support for the use of widely available Landsat imagery for investigating vegetation dynamics in glacier forefields. (C) 2021 Society of Photo Optical Instrumentation Engineers (SPIE)

Automated summary

Scientists utilized UAV imagery in the Glacier noir foreland in France to evaluate the sensitivity of Landsat NDVI to subpixel vegetation and topographic components. They found a linear relationship between fractional vegetation cover and Landsat NDVI, but noted that vegetation height and subpixel topographic heterogeneity could lead to misestimation of vegetation cover.