Smart farming in Europe

V Moysiadis, P Sarigiannidis, V Vitsas, A Khelifi - Computer science review, 2021 - Elsevier
Smart Farming is the new term in the agriculture sector, aiming to transform the traditional
techniques to innovative solutions based on Information Communication Technologies …

Seasonal crop yield forecast: Methods, applications, and accuracies

B Basso, L Liu - advances in agronomy, 2019 - Elsevier
The perfect knowledge of yield before harvest has been a wish puzzling human being since
the beginning of agriculture because seasonal forecast of crop yield plays a critical role in …

Coupling machine learning and crop modeling improves crop yield prediction in the US Corn Belt

M Shahhosseini, G Hu, I Huber, SV Archontoulis - Scientific reports, 2021 - nature.com
This study investigates whether coupling crop modeling and machine learning (ML)
improves corn yield predictions in the US Corn Belt. The main objectives are to explore …

Forecasting corn yield with machine learning ensembles

M Shahhosseini, G Hu, SV Archontoulis - Frontiers in Plant Science, 2020 - frontiersin.org
The emergence of new technologies to synthesize and analyze big data with high-
performance computing has increased our capacity to more accurately predict crop yields …

Rice crop detection using LSTM, Bi-LSTM, and machine learning models from Sentinel-1 time series

H Crisóstomo de Castro Filho… - Remote Sensing, 2020 - mdpi.com
The Synthetic Aperture Radar (SAR) time series allows describing the rice phenological
cycle by the backscattering time signature. Therefore, the advent of the Copernicus Sentinel …

“sen2r”: An R toolbox for automatically downloading and preprocessing Sentinel-2 satellite data

L Ranghetti, M Boschetti, F Nutini, L Busetto - Computers & Geosciences, 2020 - Elsevier
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 …

Estimating rice production in the Mekong Delta, Vietnam, utilizing time series of Sentinel-1 SAR data

K Clauss, M Ottinger, P Leinenkugel… - International journal of …, 2018 - Elsevier
Rice is the most important food crop in Asia and rice exports can significantly contribute to a
country's GDP. Vietnam is the third largest exporter and fifth largest producer of rice, the …

Mapping paddy rice fields by applying machine learning algorithms to multi-temporal Sentinel-1A and Landsat data

AO Onojeghuo, GA Blackburn, Q Wang… - … journal of remote …, 2018 - Taylor & Francis
Sentinel-1A synthetic aperture radar (SAR) data present an opportunity for acquiring crop
information without restrictions caused by weather and illumination conditions, at a spatial …

Corn yield prediction with ensemble CNN-DNN

M Shahhosseini, G Hu, S Khaki… - Frontiers in plant …, 2021 - frontiersin.org
We investigate the predictive performance of two novel CNN-DNN machine learning
ensemble models in predicting county-level corn yields across the US Corn Belt (12 states) …

Development of an open sensorized platform in a smart agriculture context: A vineyard support system for monitoring mildew disease

S Trilles, J Torres-Sospedra, Ó Belmonte… - … Informatics and Systems, 2020 - Elsevier
In recent years, some official reports, to produce best products regarding quality, quantity
and economic conditions, recommend that the farming sector should benefit with new tools …