remote sensing

Estimating yield using satellite data

Yield estimations are of great interest to support interventions from governmental policies and to increase global food security. We deplyed the model described here in Google Earth Engine. Check out the corn yield variability in the US Midwest along the years: Satellite derived yield maps

Mid-season county-level corn yield forecast for US Corn Belt integrating satellite imagery and weather variables

Yield estimations are of great interest to support interventions from governmental policies and to increase global food security. This study presents a novel model to perform in-season corn yield predictions at the US-county level, providing robust …

Pre‐planting weed detection based on ground field spectral data

Background: Site-specific weed management (SSWM) demands higher resolution data for mapping weeds in fields, but the success of this tool relies on the efficiency of optical sensors to discriminate weeds relative to other targets (soils, and …

Satellite-based soybean yield forecast Integrating machine learning and weather data for improving crop yield

Soybean yield predictions in Brazil are of great interest for market behavior, to drive governmental policies and to increase global food security. In Brazil soybean yield data generally demand various revisions through the following months after …

Fine‑tuning of wheat (Triticum aestivum, L.) variable nitrogen rate by combining crop sensing and management zones approaches in southern Brazi

The integration of crop sensors and management zones aiming at fine-tuning variable nitrogen rate (VNR) is a technological alternative to increase nitrogen use efficiency (NUE). The main objective of this study was to delimit management zones with …

Forecasting maize yield at field scale based on high-resolution satellite imagery

Estimating maize (Zea mays L.) yields at the field level is of great interest to farmers, service dealers, and policy-makers. The main objectives of this study were to: i) provide guidelines on data selection for building yield forecasting models …