anglr

The anglr package aims to provide direct access to generic 3D tools.

… geospatial is cool … 3D is cool … putting them together is challenging …

The anglr package provides a full suite of mesh-creation and 3D plotting functions, extending the rgl package functions as.mesh3d(), plot3d(), persp3d(), wire3d(), and dot3d().

Key working examples are in ?anglr::as.mesh3d and ?anglr::plot3d.

Features

• Convert geospatial objects to 3D with as.mesh3d() - works for matrix, raster, sf-polygons, sp-polygons, silicate-triangles

• Plot geospatial objects with plot3d() - works for matrix, raster, sf (any type), sp, trip, silicate

• Merge raster and vector with as.mesh3d - elevate polygons or lines with a raster dem

• Drape imagery onto raster or polygon surfaces with as.mesh3d - image_texture argument

• Copy Z values from a raster, polygon/line field value, or constant onto mesh vertices

• Create any mesh above and reproject to any projection, including geocentric

• Use shade3d() or plot3d() or wire3d() from the rgl package to plot any mesh3d object created. (plot3d() also calls the converters for non-mesh types, so we can quickly get a 3D scene from any spatial data)

Why anglr, isn’t this all done?

The rgl package has long supported powerful interactive 3D visualizations for points, lines, and surfaces. Surfaces can be of any form, triangles or quad primitives wrapped around a bunny, a globe, or platonic shapes such as cubes and octahedrons. There is support for textures, which is essentially imagery draped onto a surface at native resolution - there is no loss of image quality at all.

But, rgl is hard to use, and there are very few helpers for converting existing formats into the right form. There are some, for example as.mesh3d() methods for commonly used triangulation packages. It also was harder to use in the past, but recently has been improved a great deal for taking generic data and converting it.

There has been little support in rgl for geo-spatial data structures, such as spatial rasters, polygons and lines that are common in GIS workflows. The anglr package aims to fill this gap, and gives total control over conversion of spatial and other data into mesh forms - even if visualization is not the end goal.

There are packages that convert matrices and imagery to compelling animated 3D scenes, but these are targetted at presentation rather than generality and development. The scenes are targetted towards presentation, and adding general extra data to a given scene requires a lot of workarounds. There are also only few well-known packages that use the rgl mesh3d format (Rvcg, …). Many examples use rgl::surface3d() which is limited to the model that provides for an input matrix and overlaid colours or textures. These cannot be wrapped arbitrarily around curves in any 3D coordinate system.

Installation

Install from CRAN with

install.packages("anglr")

To install the development version use

## install.packages("remotes")  ## if required
remotes::install_github("hypertidy/anglr")

Feel free to contact me via the Issues if you have problems, or these notes don’t make sense.

Ubuntu/Debian

On Linux you will need at least the following installed.

libproj-dev \
 libgl1-mesa-dev \
 libglu1-mesa-dev

Get involved!

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

Examples

These examples are a bit out of date, anglr visualization works best interactively and with your own data, but these demo pages give a flavour for what is possible.

Demo 01 - merge vector and raster data

An example of merging vector and raster, with a continuous interpretation applied to the polygon mesh and underlying elevation.

## a global DEM
data("gebco", package = "anglr")
library(sf)
## North Carolina, the sf boilerplate polygon layer
nc <- read_sf(system.file("shape/nc.shp", package="sf"))


library(raster)
library(anglr) 
library(silicate)

p_mesh <- DEL(nc, max_area = 0.002)
## a relief map, composed of triangles grouped by polygon with ##  interpolated raster elevation 
p_mesh <- copy_down(p_mesh, z = gebco)


## plot the scene
library(rgl)

rgl.clear()  ## rerun the cycle from clear to widget in browser contexts 
plot3d(p_mesh) 
bg3d("black"); material3d(specular = "black")
aspect3d(1, 1, .1)

Follow this link to see the result:

Demo01

Here the z argument to copy_down() is a raster, and so the z_ coordinate of the mesh is updated by extracting values from the raster using bilinear interpolation.

Demo 02 - copy discrete values to polygon elevation

An example of elevating polygons with constant attribute values, a discrete interpretation that requires separating the (until-now) continuous mesh of polygon features.

With argument z set to a column in the layer or a specific vector of values this is used as a constant offset for the z_ value, and the mesh is separated by feature.

(The simpler TRI model is used here because we only need poor quality triangles for planar geometry. )

## either form works
#c_mesh <- copy_down(TRI(nc), z = p_mesh$object$BIR74)
c_mesh <- copy_down(TRI(nc), z = "BIR74")
open3d()
a <- plot3d(c_mesh) 
bg3d("black"); material3d(specular = "black")
aspect3d(1, 1, .2)

Follow this link to see the result:

Demo02

In the silicate models, complex 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.

Plot (3D) methods take those tables and generate the “indexed array” structures needed for ‘rgl’. (plot3d will return the rgl-model form). This gets us part of the way towards having the best of both worlds of GIS and 3D graphics.

Another example shows this approach applied to a 3D multipatch shapefile, with a few easy steps we can plot a wiremesh or roof/floor polygons from a civic building footprint.

http://rpubs.com/cyclemumner/367010

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.