{ "_id": "6a105e03acfb0bcc41ca54ba", "Package": "RFmerge", "Type": "Package", "Title": "Merging of Satellite Datasets with Ground Observations using\nRandom Forests", "Version": "0.3-3", "Authors@R": "c(person(\"Mauricio Zambrano-Bigiarini\", email = \"mzb.devel@gmail.com\", role=c(\"aut\", \"cre\", \"cph\"), comment=c(ORCID = \"0000-0002-9536-643X\")), person(\"Oscar M. Baez-Villanueva\", email = \"oscar.baezvillanueva@ugent.be\", role=c(\"aut\", \"cph\"), comment=c(ORCID = \"0000-0002-2262-1698\")), person(\"Juan Giraldo-Osorio\", email = \"j.giraldoo@javeriana.edu.co\", role=c(\"ctb\"), comment=c(ORCID = \"0000-0001-6205-3341\")) )", "Maintainer": "Mauricio Zambrano-Bigiarini ", "Description": "S3 implementation of the Random Forest MErging Procedure\n(RF-MEP), which combines two or more satellite-based datasets\n(e.g., precipitation products, topography) with ground\nobservations to produce a new dataset with improved\nspatio-temporal distribution of the target field. In\nparticular, this package was developed to merge different\nSatellite-based Rainfall Estimates (SREs) with measurements\nfrom rain gauges, in order to obtain a new precipitation\ndataset where the time series in the rain gauges are used to\ncorrect different types of errors present in the SREs. However,\nthis package might be used to merge other\nhydrological/environmental gridded datasets with point\nobservations. For details, see Baez-Villanueva et al. (2020)\n. 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