raster package is extremely powerful for spatial data. It provides
very efficient data extraction and summary tools via consistent
cell-index and comprehensive set of functions for working with grids,
cells and their values.
Tabularaster provides some more helpers for working with cells and tries
to fill some of the (very few!) gaps in raster functionality. When
raster returns cell values of hierarchical objects it returns a
hierarchical (list) of cells to match the input query, while
tabularaster::cellnumbers instead returns a data frame of identifiers
and cell numbers.
Tabularaster provides these functions.
as_tibble- convert to data frame with options for value column and cell, dimension and date indexing
cellnumbers- extract of cell index numbers as a simple data frame with “object ID” and “cell index”
index_extent- create an index extent, essentially
extent(0, ncol(raster), 0, nrow(raster))
All functions that work with
sp Spatial also work with `sf simple
There is some overlap with
spex while I figure out
where things belong.
Install from CRAN,
or get the development version from Github.
Basic usage is to extract the cell numbers from an object, where object
is a a matrix of points, a
Spatial object or a
simple features sf
cells <- cellnumbers(raster, object)
The value in this approach is not for getting cell numbers per se, but for using those downstream. The cell number is an index into the raster that means the geometric hard work is done, so we can apply the index for subsequent extractions, grouping aggregations, or for determining the coordinates or other structure summaries of where the cell belongs.
## summarize by object grouping cells %>% mutate(value= extract(raster, cell_)) %>% group_by(object_) %>% summarize(mean(value)) ## summarize by cell grouping cells %>% mutate(value= extract(raster, cell_)) %>% group_by(cell_) %>% summarize(mean(value))
The utility of this is very much dependent on individual workflow, so
this in its own right is not very exciting.
provides an easier way to create your tools.
See the vignettes for more.
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