Download data from the observation ("observacao") table of one or more datasets contained in the Free
Brazilian Repository for Open Soil Data – febr, http://www.ufsm.br/febr. This includes spatial
coordinates, observation date, and variables such as geology, land use and vegetation, local topography, and
much more. Use
header if you want to check what are the variables contained in the
observation table of a dataset before downloading it.
1 2 3 4 5
Character vector indicating one or more datasets. Identification codes should be as recorded
in http://www.ufsm.br/febr/catalog/. Use
(optional) Character vector indicating one or more variables. Accepts only general
identification codes, e.g. '"ferro"' and '"carbono"'. If missing, then a set of standard identification
variables is downloaded. Use
(optional) Logical value indicating if tables from different datasets should be stacked on a
single table for output. Requires 'standardization = list(units = TRUE)' – see below. Defaults to
(optional) List with named sub-arguments indicating what should be done with an observation
missing spatial coordinates,
(optional) List with named sub-arguments indicating how to perform data standardization.
(optional) List with named sub-arguments indicating if and how to perform data harmonization.
(optional) Logical value indicating if a download progress bar should be displayed.
(optional) Logical value indicating if informative messages should be displayed. Generally useful to identify datasets with inconsistent data. Please report to [email protected] if you find any issue.
Standard identification variables and their content are as follows:
dataset_id. Identification code of the dataset in febr to which an observation belongs.
observacao_id. Identification code of an observation in febr.
sisb_id. Identification code of an observation in the Brazilian Soil Information System
maintained by the Brazilian Agricultural Research Corporation (EMBRAPA) at
ibge_id. Identification code of an observation in the database of the Brazilian Institute
of Geography and Statistics (IBGE) at http://www.downloads.ibge.gov.br/downloads_geociencias.htm#.
observacao_data. Date (dd-mm-yyyy) in which an observation was made.
coord_sistema. EPSG code of the coordinate reference system.
coord_x. Longitude (°) or easting (m).
coord_y. Latitude (°) or northing (m).
coord_precisao. Precision with which x- and y-coordinates were determined (m).
coord_fonte. Source of the x- and y-coordinates.
pais_id. Country code (ISO 3166-1 alpha-2).
estado_id. Code of the Brazilian federative unit where an observation was made.
municipio_id. Name of the Brazilian county where as observation was made.
amostra_tipo. Type of sample taken.
amostra_quanti. Number of samples taken.
amostra_area. Sampling area.
Further details about the content of the standard identification variables can be found in http://www.ufsm.br/febr/book/ (in Portuguese).
Data harmonization consists of converting the values of a variable determined using some method B so that they are (approximately) equivalent to the values that would have been obtained if the standard method A had been used instead. For example, converting carbon content values obtained using a wet digestion method to the standard dry combustion method is data harmonization.
A heuristic data harmonization procedure is implemented in the febr package. It consists of grouping
based on a chosen number of levels of their identification code. For example, consider a variable with an
identification code composed of four levels,
aaa is the first level and
ddd is the fourth level. Now consider a related variable,
aaa_bbb_eee_fff. If the harmonization
is to consider all four coding levels (
level = 4), then these two variables will remain coded as
separate variables. But if
level = 2, then both variables will be re-coded as
aaa_bbb, thus becoming the
A list of data frames or a data frame with data on the chosen variable(s) of the chosen dataset(s).
Alessandro Samuel-Rosa [email protected]
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