On the value of sentinel-1 insar coherence time-series for vegetation classification

Synthetic aperture radar (SAR) acquisitions are mainly deemed suitable for mapping dynamic land-cover and land-use scenarios due to their timeliness and reliability. This particularly applies to Sentinel-1 imagery. Nevertheless, the accurate mapping of regions characterized by a mixture of crops and grasses can still represent a challenge....

Space-based SAR and optical remote sensing for productivity monitoring and mapping of sugarcane

In this study, research on productivity and land cover monitoring is presented, with a focus on sugarcane, based on space-based remote sensing observations that were collected by Synthetic Aperture Radar (SAR) and optical sensors. The study aims to provide new insights into techniques and methodologies that allow for cost-efficient monitoring of...

Mapping and quantifying the human-environment interactions in middle Egypt using machine learning and satellite data fusion techniques

Population growth in rural areas of Egypt is rapidly transforming the landscape. New cities are appearing in desert areas while existing cities and villages within the Nile floodplain are growing and pushing agricultural areas into the desert. To enable control and planning of the urban transformation, these rapid changes need to be mapped...