Supplementary Datasets S1 and S2 for the paper “Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning”

Folberth, C. ORCID: https://orcid.org/0000-0002-6738-5238, Baklanov, A. ORCID: https://orcid.org/0000-0003-1599-3618, Balkovic, J. ORCID: https://orcid.org/0000-0003-2955-4931, Skalsky, R. ORCID: https://orcid.org/0000-0002-0983-6897, Khabarov, N. ORCID: https://orcid.org/0000-0001-5372-4668, & Obersteiner, M. ORCID: https://orcid.org/0000-0001-6981-2769 (2018). Supplementary Datasets S1 and S2 for the paper “Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning”.

	Archive Dataset_S2.zip - Published Version Available under License Creative Commons Attribution Non-commercial. Download (8kB)
	Archive Dataset_S1.zip - Published Version Available under License Creative Commons Attribution Non-commercial. Download (1GB)

Abstract

These supplementary datasets provide data and code for reproducing key results in the corresponding paper published in Agricultural and Forest Meteorology. Dataset S1 provides training data and covariates as data frames in binary R format. Dataset S2 provides R scripts for training random forests and extreme gradient boosting models to predict maize yields. The paper should be cited if the code is used. If data are used, the original databases for soil, climate, topography, and management need to be cited as well as referenced in the paper.

Item Type:	Data
Research Programs:	Ecosystems Services and Management (ESM)
Related URLs:	Publication - http://pure.iiasa.ac.at/id/eprint/15505/
Depositing User:	Luke Kirwan
Date Deposited:	02 Oct 2018 07:48
Last Modified:	27 Aug 2021 17:30
URI:	https://pure.iiasa.ac.at/15490

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