Chris Henrick clhenrick

Shallow

Real unit test (isolation, no children render)

Simple shallow

Calls:

constructor
render

Requires gdal2:

brew install osgeo/osgeo4mac/gdal2
export PATH="/usr/local/opt/gdal2/bin:$PATH" # or just use /usr/local/opt/gdal2/bin/gdalwarp

And a build of bleeding-edge version of proj:

brew reinstall proj.rb --HEAD

CARTO: Aggregating data on SQL and infowindows

Example on how to aggregate data using spatial SQL and then show the also attributes on CARTO BUILDER infowindow.

Based on a sample dataset with images I will first reduce the geographical precission so they collide into a grid. After that using the json_agg function we join the urls into a single field along with the counts.

WITH data as (

Geocoding 10,000 addresses a second with NYC's Geosupport library and Node FFI

Following on Chris Whong's excellent writeup of how to make calls directly to NYC's Geosupport client and this first attempt at generalizing it, here's a way that let me geocode about 10,000 addresses a second on Ubuntu using Node FFI.

Note: this assumes Ubuntu - other Linux is probably fine but may need adjustments.

First, install the basics:

# Update, install Node and unzip (if needed)

#Using NYC geospport linux shared library from Ubuntu 16.04

I have been trying to understand more about geosupport, specifically geosupport desktop edition for linux which contains a linux .so shared library. I would like to eventually write node.js bindings for it so that I can write geocoding scripts that don't require a ton of network traffic.

I am a C noob and this was my first time messing with C and gcc on linux. I was able to write and compile a simple C program that calls the Geosupport shared library with hard-coded arguments.

##What is geosupport?

"Geosupport is a data processing system originally designed to run on IBM mainframes to support geographic processing needs common to New York City agencies." Basically, it's an NYC-specific geocoder released by the NYC department of city planning. It does many things, but at its simplest it can take human-readable address fields and return a point coordinate.

Query to produce a series of rings using buffers:

First you get a generate_series with the number of rings you want to produce
Then produce the 80km buffers multiplying by the radius for a number of cities
Finally use the lag function to remove for every ring the previous one so you get the ring

	license: gpl-3.0
	height: 600
	border: no
	redirect: https://observablehq.com/@d3/d3-versor-dragging

	license: gpl-3.0
	height: 481
	redirect: https://observablehq.com/@d3/geotiff-contours