Modelling of Vegetation Dynamics from Satellite Time Series to Determine Proglacial Primary Succession in the Course of Global Warming—A Case Study in the Upper Martell Valley (Eastern Italian Alps)

Abstract

Satellite-based long-term observations of vegetation cover development in combination with recent in-situ observations provide a basis to better understand the spatio-temporal changes of vegetation patterns, their sensitivity to climate drivers and thus climatic impact on proglacial landscape development. In this study we combined field investigations in the glacier forelands of Fürkele-, Zufall- and Langenferner (Ortles-Cevedale group/Eastern Italian Alps) with four different Vegetation Indices (VI) from Landsat scenes in order to test the suitability for modelling an area-wide vegetation cover map by using a Bayesian beta regression model (RStan). Since the model with the Normalized Difference Vegetation Index (NDVI) as predictor showed the best results, it was used to calculate a vegetation cover time series (1986–2019). The alteration of the proglacial areas since the end of the Little Ice Age (LIA) was analyzed from digital elevation models based on Airborne Laser Scanning (ALS) data and areal images, orthophotos, historical maps and field mapping campaigns. Our results show that a massive glacier retreat with an area loss of 8.1 km2 (56.9%; LIA–2019) resulted in a constant enlargement of the glacier forelands, which has a statistically significant impact on the degree of vegetation cover. The area covered by vegetation increased from 0.25 km2 (5.6%) in 1986 to 0.90 km2 (11.2%) in 2019 with a significant acceleration of the mean annual changing rate. As patterns of both densification processes and plant colonization at higher elevations can be reflected by the model results, we consider in-situ observations combined with NDVI time series to be powerful tools for monitoring vegetation cover changes in alpine proglacial areas.

Automated streamflow measurements in high‐elevation Alpine catchments

“…The main differences between the three monitored catchments are the size of the drained area, the extent of the glaciated area (Buckel & Otto, 2018; Knoflach et al, 2021), the streambed slope, and the background EC T (Table 1). While the drained area in Martelltal just before the inflow of the Plima into the Zufritt/Gioveretto reservoir is about 50 km 2 , the site in Kaunertal at the Rifflerbach drains 20 km 2 and in Horlachtal is a very small side valley (Finstertal) that drains about 6 km 2 .…”

Local environmental context drives heterogeneity of early succession dynamics in alpine glacier forefields

“…Relationships between NDVI and certain biophysical properties of vegetation canopies, such as leaf area index (LAI), vegetation cover and biomass have been widely studied (Ormsby et al, 1987, Wittich andHansing, 1995), including in the context of glacier forefields (Bayle et al, 2021, Knoflach et al, 2021 and in sparsely vegetated sites in the Antarctic (Fretwell et al, 2011). Further testing of relationships between NDVI and plant canopy properties in the context of glacier forefields remains necessary, however, to better understand the effects of specific conditions unrelated to vegetation that can alter reflectance, such as low organic content in soil (Todd et al, 1998), coarse granulometry and complex angular effects due to micro-topography (Bayle et al, 2021).…”

“…Overall, it has been shown that NDVI increases near-linearly with fractional vegetation cover (horizontal density) until values reach between 80% and 90% at which point it tends to saturate and increases slowly with increasing Leaf Area Index (vertical density). Remote sensing approaches have already been used efficiently in the context of glacier forefields (Klaar et al, 2015, Fischer et al, 2019, Bayle, 2020, Knoflach et al, 2021 and high sensitivity of Landsat-based NDVI to low plant cover has been demonstrated in glacier forefields (Bayle et al, 2021) and in Antarctica (Fretwell et al, 2011).…”

Remote Sensing of Land Change: A Multifaceted Perspective

“…Primary succession is the process that plants and animals colonize a barren habitat for the first time, which could take hundreds of years, while secondary succession begins after a major disturbance that transformed the original landscape. As remote sensing has a relatively short history, and the longest earth observation satellite, such as Landsat, only has a half-century record (Wulder et al, 2022), it is not ideal to quantify primary succession, and there are only limited studies on this topic (e.g., Knoflach et al, 2021;Lawrence, 2005). However, remote sensing data have been frequently used for quantifying secondary succession after disturbance with regards to its recovery rate or succession stages.…”