Wrapper that computes cell halfwidth for a given beta value, and then
builds a grid of hexagonal cells (call to MAPI_GridHexagonal).
If coordinates are in angular units (eg. longitude/latitude) MAPI will try to build a worldwide
"discrete global grid system" using package 'dggridR'.
As the 'dggridR' package is no more available on CRAN, this feature have been removed
and an error is thrown in this case.
See https://github.com/r-barnes/dggridR for more informations.
As an alternative, grids (levels 1 to 11) are downloadable from MAPI website.
MAPI_GridAuto(samples, crs, beta = 0.25, buf = 0)a spatial object of class 'sf' including the x and y coordinates of cell centers, cell geometry (polygons) and cell id (gid).
a data.frame with names and geographical coordinates of samples. Column names must be: 'ind', 'x', 'y'. If coordinates are angular (ie. latitude/longitude), note that x stands for the longitude and y for the latitude. Optional column 'errRad' with an error radius for sample locations (eg. GPS uncertainty).
coordinate reference system: integer with the EPSG code, or character with proj4string. When using dummy coordinates (eg. simulation output) you may use EPSG:3857 (pseudo-Mercator) for example. This allows computation but, of course, has no geographical meaning.
A value depending on sampling regularity: 0.5 for regular sampling, 0.25 for random sampling (Hengl, 2006).
optional. This parameter allows to expand or shrink the grid by a number of units in the same reference system as the sample geographical coordinates (0 by default).
The halfwidth cell value used to build the grid is computed as
\(h_w = \frac{\beta \sqrt{A/N}}{\sqrt{2.5980}}\),
where A is the study area (convex hull of sampling points) and N the number of samples.
Parameter beta allows to respect the Nyquist-Shannon sampling theorem depending on sampling regularity
(call to MAPI_EstimateHalfwidth).
If coordinates are provided as longitude/latitude (eg. crs=4326) MAPI will try to build a worldwide grid.
See MAPI_EstimateHalfwidth and MAPI_GridHexagonal for more information.
data("samples")
grid <- MAPI_GridAuto(samples, crs=3857, beta=0.5)
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