Recent applications of Landsat 8 Operational Land Imager (L8/OLI) and Sentinel-2
MultiSpectral Instrument (S2/MSI) data for acquiring information about land use and land …

The study of grasslands using machine learning (ML) methods combined with
proximal/remote sensing data (RS) has been steadily increasing in the last decades …

Sensors are now used by farmers and agronomists to help them improve their operations.
They use sensor data transmitted via IoT to remotely monitor their crops. Farmers today …

The livestock activity accounts for a large part of the transformations in land cover in the
world, with pasture areas being the main land use in Brazil and the main livelihood of the …

Crop classification plays a crucial role in ensuring food security, agricultural policy
development, and effective land management. Remote sensing data, particularly Sentinel-1 …

Many approaches for crop yield prediction were analyzed by countries using remote sensing
data, but the information obtained was less successful due to insufficient data gathered due …

Public domain synthetic-aperture radar (SAR) imagery, particularly from Sentinel-1, has
widened the scope of day and night vegetation monitoring, even when cloud cover limits …

The downside risk of crop production affects the entire supply chain of the agricultural
industry nationally and globally. This also has a profound impact on food security, and thus …

Timely map**, measuring and impact assessment of flood events are crucial for the
coordination of flood relief efforts and the elaboration of flood management and risk …