Statistical modelling of crop yield in Central Europe using climate data and remote sensing vegetation indices-Reference-Cited by-同舟云学术

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Statistical modelling of crop yield in Central Europe using climate data and remote sensing vegetation indices

Published:2018-10 Issue: Volume:260-261 Page:300-320
ISSN:0168-1923
Container-title:Agricultural and Forest Meteorology
language:en
Short-container-title:Agricultural and Forest Meteorology

Author:

Kern Anikó,Barcza Zoltán^ORCID,Marjanović Hrvoje,Árendás Tamás,Fodor Nándor,Bónis Péter,Bognár Péter,Lichtenberger János

Funder

the Széchenyi 2020 programme

European Regional Development Fund and the Hungarian Government

Hungarian Scientific Research Fund

Croatian Science Foundation

Advanced research supporting the forestry and wood-processing sector’s adaptation to global change and the 4th industrial revolution

OP RDE

Publisher

Elsevier BV

Subject

Atmospheric Science,Agronomy and Crop Science,Global and Planetary Change,Forestry

Reference131 articles.

1. Fertiliser responses of maize and winter wheat as a function of year and forecrop;Árendás;Acta Agron. Hun.,2010

2. Uncertainties in simulating wheat yields under climate change;Asseng;Nat. Clim. Change,2013

3. Towards fine resolution global maps of crop yields: testing multiple methods and satellites in three countries;Azzari;Remote Sens. Environ.,2017

4. Empirical regression models using NDVI, rainfall and temperature data for the early prediction of wheat grain yields in Morocco;Balaghi;Int. J. Appl. Earth Obs. Geoinf.,2008

5. A revised hydrology for the ECMWF model: verification from field site to terrestrial water storage and impact in the Integrated Forecast System;Balsamo;J. Hydrometeorol.,2009

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