Evaluation of limiting factors for SAR backscatter based cut detection of alpine grasslands

Abstract

Several studies utilized C-band Synthetic Aperture Radar (SAR) backscatter time series to detect cut events of grasslands. They identified several potential factors hindering the detection: Vegetation characteristics, precipitation, and the timing of salvage of the harvested grass. This study uses a comprehensive in situ database to assess the impact of those factors on the detection rate of cut events by performing a cut detection based on Sentinel-1 backscatter time series and relating the accuracy to the potentially limiting factors. The results can be summarized in the following key findings: (i) The detection rate decreases significantly with grass heights below 35 cm and a biomass of less than 2100 kg/ha. As the grass of the first growth is typically characterized by greater height and higher biomass, first cuts achieved a higher accuracy with 85% compared to re-growth cuts with 65%. (ii) False positive cut events were related to higher precipitation amounts, but adding precipitation data to the model led only to a slight increase of the accuracy of re-growth cuts, but a decrease of the overall accuracy. (iii) No relation was found between the timing of salvage and the backscatter behaviour. These insights contribute to a better utilization of C-band backscatter for vegetation analysis and agricultural applications, including cut detection. Further research with dense in situ measurements, including Vegetation Water Content (VWC) is required to fully understand the behaviour of C-band backscatter over managed grasslands.