The increasing availability of satellite data at higher spatial, temporal and spectral
resolutions is enabling new applications in agriculture and economic development …

Reliable estimation of region-wide rice yield is vital for food security and agricultural
management. Field-scale models have increased our understanding of rice yield and its …

Crop yield forecasting at national level relies on predictors aggregated from smaller spatial
units to larger ones according to harvested crop areas. Such crop areas come from land …

Abstract sen2r is a scalable and flexible R package to enable downloading and
preprocessing of Sentinel-2 satellite imagery via an accessible and easy to install interface …

Yield forecast is essential to agriculture stakeholders and can be obtained with the use of
machine learning models and data coming from multiple sources. Most solutions for yield …

Going beyond previous work, this paper presents a systematic literature review that explores
the deployment of satellites, drones, and ground-based sensors for yield prediction in …

Background In this study, we compared four models for predicting rice blast disease, two
operational process-based models (Yoshino and Water Accounting Rice Model (WARM)) …

The increasing frequency and intensity of severe droughts over recent decades have led to
substantial crop yield losses in the Pannonian Basin in southeastern Europe. Their …

The accuracy prediction for the crop yield is conducive to the food security in regions and/or
nations. To some extent, the prediction model for crop yields combining the crop mechanism …

BACKGROUND The simultaneous prediction of yield and maturity date has an important
impact on ensuring food security. However, few studies have focused on simultaneous …