Mapping changes of grassland to arable land using automatic machine learning of stacked ensembles and H2O library

Author:

Šandera Jiří1ORCID,Štych Přemysl1ORCID

Affiliation:

1. Department of Applied Geoinformatics and Cartography, Charles University, Prague, Czech Republic

Funder

European Union’s Caroline Herschel Framework

Publisher

Informa UK Limited

Subject

Applied Mathematics,Atmospheric Science,Computers in Earth Sciences,General Environmental Science

Reference92 articles.

1. The carbon content of topsoil and its geographical distribution in France

2. Application of ensemble machine learning model in downscaling and projecting climate variables over different climate regions in Iran

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4. A review of vegetation indices

5. Behnamian A. Millard K. Banks S. N. White L. Richardson M. & Pasher J. 2017. A systematic approach for variable selection with random forests: Achieving stable variable importance values. Ieeexplore.Ieee.org . Retrieved June 15 2021 Ieeexplore.Ieee.org https://ieeexplore.ieee.org/abstract/document/8038868/

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