How to Scale/Choose D3 Projection Settings from .shp File

Question

I'm following along Mike Bostock's example for creating a geoJSON projection by downloading and converting shapefiles to geoJSON. I've downloaded the files correctly, and they're online here:

https://bl.ocks.org/KingOfCramers/2c5ceb2e7526a8370d6926958654cf21

This works fine (obviously in the future I'll simplify the shape file to get it to run faster on a browser). Right now, I want to be able to replicate this process quickly for other shapefiles. I've downloaded many from Natural Earth and have converted them successfully into JSON files for use in geoJSON and topoJSON, but I am unsure how to determine which projection to use on them.

Is there a way to quickly examine a .shp file (or after it's been converted JSON) to determine which D3 projection to use, which "translate" values to use, and any other presets for my projection? Or, if I'm going to use geoproject prior to even mapping the file, how I do I find the values to plug in? Here's Mike Bostock's example:

geoproject 'd3.geoConicEqualArea().parallels([34, 40.5]).rotate([120, 0]).fitSize([960, 960], d)' < ca.json > ca-albers.json

How does he know the rotate value? How does he know which parameters to feed into this function?

For an un-finished example, here's my bl.ock of the current earth, but the projection breaks the JSON, because obviously my projection settings are not right:

http://blockbuilder.org/KingOfCramers/16be1bf014683572086511c6a8bd7470

-- or --

https://bl.ocks.org/KingOfCramers/16be1bf014683572086511c6a8bd7470

I can drop this JSON file into mapshaper, which projects it quickly and flawlessly. I want to be able to do this in D3, or at the very least convert the file before mapping it. I'm assuming that information is stored somewhere in the JSON file? Or can be accessed somehow using the JSON projection converter that Mike Bostock recommends, geoproject? Thanks for any help you can provide!

Answer 1

Key Issue

D3 assumes the file to be projected requires projection - that is to say, it assumes the file has not already been projected. This applies if pre-projecting your files from the command lie so that you can display them without a d3 projection. If using projected features, you will not get the results you want - you must unproject your features first.

If using a standard d3 projection such as d3.geoAlbers, data must be unprojected and contain latitude longitude pairs.

Unprojected vs Projected

Unprojected features are those which have latitude and longitude coordinates, they are points located on a three dimensional globe. To display these we need a projection function (most simply: lat = y, long = x, a plate carree projection).

Projected features are those which have Cartesian x,y coordinates. They are the product of some projection function which as a consequence introduces distortion of some or all of: shape, area, distance, or direction.

Signs of Using Projected Data

Upside Down Features

Upside down features are an easy indicator that your features are already projected. Projected geographic data generally features and origin at the bottom left of the features, as one moves north, y values increase. SVG coordinate space is the opposite, as one moves south y values increase.

When displaying your data in mapshaper if you include a shapefiles .prj file, mapshaper will project your data according to this. This will ensure that north is true. When displaying this data with d3, there is no flip on the y axis unless you bake that into the projection function.

Projection File

Secondly, the prj file that comes with every shapefile (or the vast majority) will tell you if features are projected or not. If your prj file lists anything like Albers, Conic, etc, then you have projected data. You need to have your data "projected" using the WGS84 datum or unprojected (also using WGS84). Data using this coordinate space has the EPSG number of 4326, and the prj file should look something like:

GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]]

Coordinate Domain

Lastly, if in mapshaper (or any other GIS utility that handles geojson) you were to export the data as geojson, if you see coordinates in excess of [+/-180,+/-90] you are probably dealing with projected data, which often uses a unit of measure like meters.

If you include a file and a projection function I can provide some more specific signs rather than these generalizations.

Easy Solution

If you don't want to modify the projection the data came in, you can use an identity projection:

d3.geoIdentity().reflectY(true).fitSize([w, h], geojson)

This will not modify the input projection, essentially it is only scaling and flipping the input features to match your intended svg/canvas dimensions.

The downside is you can't take features that are already projected as an Albers Equal Area and convert it straight into a Azimuthal Equidistant projection. Also, this approach may make it difficult to overlay locations with geographic coordinates on top of your pre-projected features - for that you will need to re-create the projection the features originally came in.

The upside is the simplicity, it is fine for choropleths or visualizations where nothing geographic is overlain on the projected features.

More Flexible Solution

Unproject your data first, in mapshaper you can do this, assuming you imported the prj files by using the console window and typing:

proj wgs84

Now you can reproject or preproject for d3. Other tools exist for the command line, while programs like QGIS can help convert data quickly too.

The advantage to this is that you can easily re-apply the projection you used on the command line to any points you want to overlay on top, and of course you can modify the projection easily.

What Project Parameters To Choose

If following the 2nd approach or overlaying geographic coordinates on top of features displayed using the 1st approach, the question of what projection parameters to choose becomes relevant again.

The projection parameters chosen are chosen very specifically and often taken straight from standard projections. The .prj file of a shapefile contains everything you need to re-create the projection used in the shapefile. This answer goes into how to emulate a prj file with a d3 projection.

SpatialReference.org is a great reference for finding parameters to different projections. There is a good chance that the California Albers example was based on a standard projection that you can find on this site, probably this one. Of course though, when Mike Bostock used this projection, he applied it to unprojected data.