Development of a tool for automatic bare soil detection from multitemporal satellite optical imagery for digital soil mapping applications

Understanding the variability of soil attributes allows to improve the farm production efficiency, accompanied by a reduction in environmental impacts and effective usage of resources. Several studies confirmed the potential of optical remote sensing data for quantifying soil attributes, such as clay content, soil organic carbon and texture classes A challenging issue in spatial-temporal soil surveying by remote sensing data is the limited availability of cloud-free images or affected by cloud/shadow. Further, imagery with high temporal resolution is extremely important for observing terrestrial surfaces. This study investigates the use of multispectral (Sentinel-2 MSI) satellite imagery at the regional/local scale, for the automated detection of agricultural bare soil occurrence, exploiting bands covering the spectral range from visible to shortwave infrared. The study objective is to provide bare soil time series that could be subsequently exploited in digital soil mapping (DSM) approaches based on multispectral or, also in view of the next future missions, hyperspectral remote sensing data.