Description Usage Arguments Value
Given a data table with columns for latitude, longitude and some time dimensions, this function extracts values at the intersection of points (denoted by latitude and longitude) from raster-like objects. From time varying rasters, the function matches the appropriate time using time_var. extract_covariates accepts either a list of raster-like objects or a raster-like object itself. Time varying covariates/rasters are infered from the names of the raster like objects by matching the suffix of names(raster_obj) with the defined time scale. For example, if a raster brick with layer names evi.1, evi.2, evi.3 and evi.4 is passed and the time scale is 2000,2001,2002, and 2003, the function takes evi.2 to represent 2001.
1 2 | extract_covariates(xyt, covariate_list, centre_scale = T, time_var = "year",
time_scale = c(2000, 2005, 2010, 2015))
|
xyt |
data.table. A data frame containing columns for latitude, longitude and some time element (defined by time_var) where raster values should be extracted. |
covariate_list |
list or raster-like. A list (or single raster-like object) of raster-like objects. These normally represent covariates. |
centre_scale |
Logical. Should the covariate values be centered/normalized? Binary variables are excluded. Binary variables are excluded. Factor variables should be converted into individual rasters using raster::layerize. This is due to computational friendly-ness and that downstream processes don't always play well with factor variables. |
time_var |
Character. Column in the dataset representing the time variable. |
time_scale |
Numeric Vector. Denotes the full range of times under analysis. For example, if we are analyzing yearly from 2000-2015, the the vector should be 2000:2015. if specified, this will be used to translate between actual time and the suffixes of the covariates. E.g. 2004 would be translated into 5 (as its the fifth position) |
A data table with columns of the extracted values from covariate list reconciled by time. If centre_scale is T, returns the extracted values after centre-scaling (normalizing) as well as the centre_scale data frame for later use.
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