Investigation of Sentinel-1 Time Series for Sensitivity to Fern Vegetation in an European Temperate Forest

Abstract

Abstract. In this study, a dense Copernicus Sentinel-1 time series is analyzed to gain a better understanding of the influence of undergrowth vegetation, in particular of eagle fern (Pteridium aquilinum), on the C-band SAR signal in a temperate forest in the Free State of Thuringia, Germany. Even if signals from the ground below the canopy may not be expected at C-band, previous studies showed seasonal fluctuations of the backscatter for temperate forests without canopy closure, notably for evergreen coniferous stands. Many factors can be responsible for these observed fluctuations, but in this study, we analyze one possible factor: the presence of undergrowth vegetation, in particular, of fern. Especially, the Sentinel-1 backscatter signal is analyzed for different acquisition configurations regarding its temporal and its spatial stability at different growth stages. This time series study shows that a difference of backscattered signal of up to 0.7 dB exists between forest patches with a dense fern density in the understory and the ones with low undergrowth vegetation. This signal difference depends on the season and is remarkably strong comparing winter (no fern undergrowth) with summer (major fern undergrowth).

Sentinel-1 Backscatter Time Series for Characterization of Evapotranspiration Dynamics over Temperate Coniferous Forests

“…In the end, some degree of influence based on the incidence angle cannot be ruled out completely. As shown in previous works using time series analyses, even small differences in seasonal behavior can be observed with Sentinel-1 C-band data [45]. The different incidence angle for each relative orbit, in addition to the fact that objects are observed from a southwesterly direction in ascending overpass direction and from southeasterly direction in descending overpass direction, renders a direct comparison of backscatter behavior very complex let alone a correlation analysis of different datasets.…”

“…All scenes are pre-processed to a radiometrically terraincorrected (RTC) product through the application of orbit files, radiometric calibration to gamma0, multi-looking to 20 m pixel size, radiometric terrain flattening and geocoding by utilizing the pyroSAR code library [44]. The data collection is a continued time series of the dataset presented in a previous study [45] (see Figure 2). A summary of the Sentinel-1 dataset is presented in Table 1.…”

“…With a 20 m pixel size of the Senti-nel-1 data, this leads to a patch of six-by-six Sentinel-1 pixels for each data observation site. The spatial stability analysis in another study suggests homogenous results of the Sentinel-1 data for multiple neighboring pixels [45]. All backscatter datasets were aggregated again by spatially averaging all data observations around the respective weather station to subsequently compare.…”

Cover classifications in wetlands using Sentinel-1 data (Band C): a case study in the Parana river delta, Argentina

“…Ceibo and Willow are forest classes that have some differences in their distribution in the landscape: the Ceibo class is characterized by being an open forest with a high amount of biomass underneath, whereas the Willow class is characterized by being a closed forest (Kandus et al, 2006). Mueller et al (2021) showed a backscattered signal difference between forest patches with a dense vegetation density in the understory and those with a low vegetation density in Thuringia (Germany). In line with this study, a possible explanation is that in the case of the Ceibo forest during the winter the microwave radiation may be interacting with the stems, trunks, and, also, with the vegetation underneath, contrary to what may be happening in the Willow class.…”