Convert between different types of spatial objects.

Description

Facilities for converting between different types of spatial objects, including an in-place method to modify the underlying geometry of 'Spatial' classes using data frame idioms.The spbabel package provides functions to round-trip a Spatial object to a single table and back.

Details

Individual geometries as tibbles.

Description

Individual geometries as tibbles.

Usage

## S3 method for class 'sfg'
as_tibble(
  x,
  ...,
  .rows = NULL,
  .name_repair = c("check_unique", "unique", "universal", "minimal"),
  rownames = pkgconfig::get_config("tibble::rownames", NULL)
)

Arguments

Value

tibble

Normal form for sf

Description

A 'feature_table' is a normal form for simple features, where all branches are recorded in one table with attributes object_, branch_, type_, parent_. All instances of parent_ are NA except for the holes in multipolygon.

Usage

feature_table(x, ...)

Arguments

Details

There is wasted information stored this way, but that's because this is intended as a lowest common denominator format.

There are three tables, objects (the feature attributes and ID), branches (the parts), coordinates (the X, Y, Z, M values).

Multi-part, multi-holed, neighbouring, not completely topological polygons.

Description

Created in /data-raw/ from a manual drawing built in Manifold GIS.

A decomposition of 'vector' map data structures to tables.

Description

Creates a set of related tables to store the appropriate entities in spatial map data.

Usage

map_table(x, ...)

Arguments

Details

The basic entities behind spatial data, and hence the "map tables" are:

vertices

the positions in geometric space, e.g. x, y, z, time, long, lat, salinity etc.

branches

a single connected chain of vertices, or "parts"

objects

a collection of branches aligned to a row of metadata

This is the basic "topology" of traditional GIS vector data, for points, lines, polygons and their multi-counterparts. By default map_tables will produce these tables and also de-duplicated the input vertices, adding a fourth table to link vertices to branches.

Other topology types such as triangle or quad meshes can extend this four-entity model, or exist without the branches at all. See "mesh_table" ??

These are currently classed as object_table, branch_table, branch_link_vertex_table, and vertex_table. But there are no methods.

Value

list of tibbles

MultiPointsDataFrame data set

Description

MultiPointsDataFrame data set

"South-east" map data.

Description

Created in /data-raw/ semap is the sptable version of some of maptools 'wrld_simpl' and seatt is the matching attribute data, linked by 'object_'.

Created in /data-raw/.

Examples

# recreate as sp object
mp <- sp(semap, attr_tab = seatt, crs = "+proj=longlat +ellps=WGS84")

TBD Convert from dplyr tbl form to simple features.

Description

Not yet implemented.

Usage

sf(x, ...)

## S3 method for class 'data.frame'
sf(x, attr_tab = NULL, crs, ...)

Arguments

Value

sf

sp methods

Description

Sp methods

Usage

## S4 method for signature 'SpatialPolygonsDataFrame'
show(object)

## S4 method for signature 'SpatialLinesDataFrame'
show(object)

## S4 method for signature 'SpatialPointsDataFrame'
show(object)

## S4 method for signature 'Spatial'
print(x, ...)

Arguments

Convert from dplyr tbl form to Spatial*DataFrame.

Description

Convert from dplyr tbl form to Spatial*DataFrame.

Usage

sp(x, ...)

## S3 method for class 'data.frame'
sp(x, attr_tab = NULL, crs, ...)

Arguments

Value

Spatial*

Examples

library(dplyr)
semap1 <- semap  %>% dplyr::filter(y_ > -89.9999)
sp_obj <- sp(semap1, attr_tab = seatt, crs = "+proj=longlat +ellps=WGS84")
## look, seamless Antarctica!
## library(rgdal); plot(spTransform(sp_obj, "+proj=laea +lat_0=-70"))

Convert from various forms to a table.

Description

Decompose a Spatial or sf object to a single table structured as a row for every coordinate in all the sub-geometries, including duplicated coordinates that close polygonal rings, close lines and shared vertices between objects.

Usage

## S3 method for class 'SpatialPolygons'
sptable(x, ...)

## S3 method for class 'SpatialLines'
sptable(x, ...)

## S3 method for class 'SpatialPointsDataFrame'
sptable(x, ...)

## S3 method for class 'SpatialMultiPointsDataFrame'
sptable(x, ...)

sptable(object) <- value

sptable(x, ...)

## S3 method for class 'trip'
map_table(x, ...)

Arguments

Details

Input can be a of type sf or SpatialPolygonsDataFrame, SpatialLinesDataFrame, SpatialMultiPointsDataFrame or a SpatialPointsDataFrame. For simplicity sptable and its inverses sp and sf assume that all geometry can be encoded with object, branch, island, order, x and y. and that the type of topology is identified by which of these are present.

For simple features objects with mixed types of topology the result is consistent, but probably not useful. Columns that aren't present in one type will be present, padded with NA. (This is work in progress).

Value

Spatial object

tibble with columns

• SpatialPolygonsDataFrame "object_" "branch_" "island_" "order_" "x" "y_"

• SpatialLinesDataFrame "object_" "branch_" "order_" "x_" "y_"

• SpatialPointsDataFrame "object_" x_" "y_"

• SpatialMultiPointsDataFrame "object_" "branch_" "x_" "y_"

• sf some combination of the above

Examples

## holey is a decomposed SpatialPolygonsDataFrame
spdata <- sp(holey)
library(sp)
plot(spdata, col = rainbow(nrow(spdata), alpha = 0.4))
points(holey$x_, holey$y_, cex = 4)
holes <- subset(holey, !island_)
## add the points that only belong to holes
points(holes$x_, holes$y_, pch = "+", cex = 2)

## manipulate based on topology
## convert to not-holes
notahole <- holes
notahole$island_ <- TRUE
#also convert to singular objects - note that this now means we have an overlapping pair of polys
#because the door had a hole filled by another object
notahole$object_ <- notahole$branch_
plot(sp(notahole), add = TRUE, col = "red")

Multi-object track with x, y, z, and time.

Description

Created in /data-raw/track.r