RFmerge: Merging of Satellite Datasets with Ground Observations using Random Forests

S3 implementation of the Random Forest MErging Procedure (RF-MEP), which combines two or more satellite-based datasets (e.g., precipitation products, topography) with ground observations to produce a new dataset with improved spatio-temporal distribution of the target field. In particular, this package was developed to merge different Satellite-based Rainfall Estimates (SREs) with measurements from rain gauges, in order to obtain a new precipitation dataset where the time series in the rain gauges are used to correct different types of errors present in the SREs. However, this package might be used to merge other hydrological/environmental satellite fields with point observations. For details, see Baez-Villanueva et al. (2020) <doi:10.1016/j.rse.2019.111606>. Bugs / comments / questions / collaboration of any kind are very welcomed.

Version:	0.1-10
Depends:	R (≥ 3.5.0)
Imports:	raster, sp, sf, randomForest, zoo, parallel, methods, stats, utils, pbapply
Suggests:	knitr, rmarkdown, rgdal
Published:	2020-05-22
Author:	Mauricio Zambrano-Bigiarini [aut, cre, cph], Oscar M. Baez-Villanueva [aut, cph], Juan Giraldo-Osorio [ctb]
Maintainer:	Mauricio Zambrano-Bigiarini <mzb.devel at gmail.com>
BugReports:	https://github.com/hzambran/RFmerge/issues
License:	GPL (≥ 3)
URL:	https://github.com/hzambran/RFmerge
NeedsCompilation:	no
Citation:	RFmerge citation info
Materials:	NEWS
CRAN checks:	RFmerge results

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