The 'anglr' package illustrates some generalizations of GIS-y tasks in R with a database-y approach.

The basic idea is to create toplogical objects from a variety of sources:

• simple features
• Spatial features
• rgl 3D objects
• trip objects (and general animal tracking data types)
• regular raster grids
• igraph
• Lidar

The general approach is to anglr your model and then plot it.

library(anglr)

#model <- sf::st_read("some/shapefile.shp")
#model <- raster::raster("some/gridraster.tif")

mesh <- anglr(model)
plot(mesh)

This is too simplistic for general use but these meshes can be used to merge disparate data into a single form, or used to convert standard spatial objects to rgl ready forms.

An example of merging vector and raster can be seen with this.

f <- system.file("extdata/gebco1.tif", package = "anglr")
## ad hoc scaling as x,y and  z are different units
r <- raster::raster(f)/1000

library(sf)
nc <- read_sf(system.file("shape/nc.shp", package="sf"))
library(raster)
library(anglr) ## devtools::install_github("hypertidy/anglr")

## objects
## a relief map, triangles grouped by polygon with interpolated raster elevation 
p_mesh <- anglr(nc, max_area = 0.008) ## make small triangles ( sq lon-lat degree)
#g <- anglr(graticule::graticule(-85:-74, 32:37))
p_mesh$v$z_ <- raster::extract(r, cbind(p_mesh$v$x_, p_mesh$v$y_), method = "bilinear")

## plot the scene
library(rgl)

rgl.clear()  ## rerun the cycle from clear to widget in browser contexts 
plot(p_mesh) 
#plot(g, color = "white") 
bg3d("black"); material3d(specular = "black")
rglwidget(width =  900, height = 450)  ## not needed if you have a local device

Multiple multi-part objects are decomposed to a set of related, linked tables. Object identity is maintained with attribute metadata and this is carried through to colour and other aesthetics in 3D plots.

Plot methods take those tables and generate the "indexed array" structures needed for 'rgl'. In this way we get the best of both worlds of "GIS" and "3D models".

The core work for translating spatial classes is done by the unspecialized 'silicate::PATH' function and its underlying decomposition generics.

anglr then decomposes further, from path-types to primitive-types - where "primitive" means topological primitives, vertices, line segments (edges), triangles. Crucially, polygons and lines are described by the same 1D primitives, and this is easy to do. Harder is to generate 2D primitives and for that we rely on Jonathan Richard Shewchuk's Triangle.

Triangulation is with RTriangle package using "constrained mostly-Delaunay Triangulation" from the Triangle library, but could alternatively use rgl with its ear clipping algorithm, and related work is in the laridae project to bring CGAL facilities to R.

With RTriangle we can set a max area for the triangles, so it can wrap around curves like globes and hills, and this can only be done by the addition of Steiner points. All of this takes us very far from the path-based types generally used by GIS-alikes.

Raster gridded data are decomposed to "quad" forms, essentially a 2D primitive with four corners rather than 3. This works well in rgl but is slow in the browser for some reason, but we can always break quads down to triangles if needed.

Texture mapping is possible with rgl, but it needs a local coordinate system mapped to the index space of a PNG image. It's easy enough but requires a bit of awkward preparation, not yet simplified. Some different approaches:

https://rpubs.com/cyclemumner/frink-polyogn

Deprecated use of rangl here, but shows the general texture coordinate approach required:

https://gist.github.com/mdsumner/dc80283de50bb23ff7681b14768b9367

Also required are packages 'rgl' and 'RTriangle', so first make sure you can install and use these.

install.packages("rgl")
install.packages("RTriangle")
devtools::install_github("hypertidy/anglr")

On Linux you will need at least the following installed by an administrator, here tested on Ubuntu Xenial 16.04 (note the apt/sources.list is specific to version).

## key for apt-get update, see http://cran.r-project.org/bin/linux/ubuntu/README
echo 'deb https://cloud.r-project.org/bin/linux/ubuntu xenial/' >> /etc/apt/sources.list
apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E084DAB9

## up to date GDAL and PROJ.4 and GEOS
## https://launchpad.net/~ubuntugis/+archive/ubuntu/ubuntugis-unstable
add-apt-repository ppa:ubuntugis/ubuntugis-unstable --yes

apt update 
apt upgrade --assume-yes

## Install 3rd parties
apt install libproj-dev libgdal-dev libgeos-dev  libssl-dev libgl1-mesa-dev libglu1-mesa-dev libudunits2-dev
## install R, if you need to
## apt install r-base r-base-dev 

Then in R

install.packages("devtools")
install.packages(c("dplyr", "proj4", "raster",  "rgl", "rlang", "RTriangle", "spbabel", "tibble", "viridis"))
devtools::install_github("hypertidy/anglr")

Let me know if you have problems, or are interested in this work. See the issues tab to make suggestions or report bugs.

https://github.com/hypertidy/anglr/issues

See the vignettes: https://hypertidy.github.io/anglr/articles/index.html

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.