Develop Reference

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

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!

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.

How to draw a polygon on BingMap based on pushpins?

I have a number of Pushpins on a BingMap v8. I'd like to draw a polygon around these pins.
I see a lot of examples of how to draw polygons manually, but see nothing about using Pushpins as a guide.
I am looking for something like below. Does this functionality exist in BingMaps v8?

There are two ways to do this. The most common is to use a Convex Hull which generates a polygon that is similar to stretching an elastic around the pushpins. The second option is a Concave Hull which tries to create a tighter fitting polygon around the data set. The Bing Maps V8 web control has built in calculations for both of these in the spatial math module. Here is a code sample that shows how to do both of these: http://bingmapsv8samples.azurewebsites.net/#Concave%20and%20Convex%20Hulls
Here is documentation on the Spatial Math module: https://msdn.microsoft.com/en-us/library/mt712834.aspx

Classify lon/lat coordinate into geojson polygon using Javascript

I have a geojson object defining Neighborhoods in Los Angeles using lon/lat polygons. In my web application, the client has to process a live stream of spatial events, basically a list of lon/lat coordinates. How can I classify these coordinates into neighborhoods using Javascript on the client (in the browser)?
I am willing to assume neighborhoods are exclusive. So once a coordinate as been classified as neighborhood X, there is no need to further test it for other neighborhoods.

There's a great set of answers here on how to solve the general problem of determining whether a point is contained by a polygon. The two options there that sound the most interesting in your case:
As #Bubbles mentioned, do a bounding box check first. This is very fast, and I believe should work fine with either projected or unprotected coordinates. If you have SVG paths for the neighborhoods, you can use the native .getBBox() method to quickly get the bounding box.
the next thing I'd try for complex polygons, especially if you can use D3 v3, is rendering to an off-screen canvas and checking pixel color. D3 v3 offers a geo path helper that can produce canvas paths as well as SVG paths, and I suspect if you can pre-render the neighborhoods this could be very fast indeed.
Update: I thought this was an interesting problem, so I came up with a generalized raster-based plugin here: http://bl.ocks.org/4246925
This works with D3 and a canvas element to do raster-based geocoding. Once the features are drawn to the canvas, the actual geocoding is O(1), so it should be very fast - a quick in-browser test could geocode 1000 points in ~0.5 sec. If you were using this in practice, you'd need to deal with edge-cases better than I do here.
If you're not working in a browser, you may still be able to do this with node-canvas.

I've seen a few libraries out there that do this, but most of them are canvas libraries that may rely on approximations more than you'd want, and might be hard to adapt to a project which has no direct need to rely on them for intersections.
The only other half-decent option I can think of is implementing ray casting in javascript. This algorithm isn't technically perfect since it's for Euclidean geometry and lat/long coordinates are not (as they denote points on a curved surface), but for areas as small as a neighbourhood in a city I doubt this will matter.
Here's a google maps extension that essentially does this algorithm. You'd have to adapt it a bit, but the principles are quite similar. The big thing is you'd have to preprocess your coordinates into paths of just two coordinates, but that should be doable.*
This is by no means cheap - for every point you have to classify, you must test every line segment in the neighborhood polygons. If you expect a user to be reusing the same coordinates over and over between sessions, I'd be tempted to store their neighborhood as part of it's data. Otherwise, if you are testing against many, many neighborhoods, there are a few simple timesavers you can implement. For example, you can preprocess every neighborhoods extreme coordinates (get their northmost, eastmost, southmost, and westmost points), and use these to define a rectangle that inscribes the town. Then, you can first check the points for candidate neighborhoods by checking if it lies inside the rectangle, then run the full ray casting algorithm.
*If you decide to go this route and have any trouble adapting this code, I'd be happy to help

Javascript Canvas Lat Lng Plotting

I want to create a data visualization similar to this:
...but for the entire globe. The canvas size will be arbitrary but won't need to resize with the browser (I will set the width and height before I start plotting points). I need to figure out a way of converting latitude and longitude coordinates to points on the canvas. Does anyone know how to do it?

First of all you need to choose projection. Then you can use proper formula. Or you can just use existent solution like proj4js for example. This is JS port of well-known proj utility for working with various projections.
I would recommend to use Miller Projection for the visualizations on the whole globe. You can find formulas here.

MapboxGL extruding lines/circles

I'm trying to implement a LineString extrusion depending on timestamp. As mentioned on github it is supposed to be implemented, but it isn't. It is supposed to look something like the screenshot below.
So far I could find out that it is possible to use extrusion for polygons but then i would have to somehow create polygons from my LineStrings and circles. Is there another way to implement this? My plan is to show human movement in association with there timestamps (smallest z-axis heigth/altitude would represent the oldest timestamp).
Maybe there is another framework where this is possible but so far i m very pleased with MapboxGl JS. Thanks for anyhelp.

You can only extrude polygon. You could use turf buffer to create polygon features from your linestring segments.

UPDATE:
I ended up using fill-extrusion. I created Polygons between my geo points and extruded the or as mention it works perfectly with turf as well.