Skip to content

Instantly share code, notes, and snippets.

@andy-esch
Forked from makella/real-time.md
Last active April 4, 2016 01:54
Show Gist options
  • Save andy-esch/01a2a213db11f6da42c4 to your computer and use it in GitHub Desktop.
Save andy-esch/01a2a213db11f6da42c4 to your computer and use it in GitHub Desktop.
UC Berkeley Workshop: Introduction and Map Design

Introduction to Map Design

Andy Eschbacher, @MrEPhysics, eschbacher@cartodb.com

October 19, 2015

Web Maps

  • Before we dive into CartoDB, let's talk a little bit about web maps
  • When we talk about web maps, we are referring to a few different components:
    • the map (aka, basemap)
    • the data overlay
    • and the interface that the map sits in
  • In some ways yes, because the maps are on the web, but when we are talking about web maps, we're usually talking about a map like this

Basemap

A map that provides geographic context to help support a wide variety of overlays- typically raster tiles.

Stamen Tiles

Map tiles

The dimensions are 256x256 pixels and organized based on coordinates (x,y) and zoom levels (z).

tiles

Zoom levels

Defines the scale of the current map view. Ranges from 0 (entire world) to 21 (individual building level). zoom levels

Let's look at a tile

http://www.openstreetmap.org

Tile URL

tile url

Free or custom?

openstreetmap pintrest

Overlay

Themes of information overlaid on a basemap that help tell a story - typically vector.

basemapoverlay

How do we interact with the overlay?

Javascript/HTML/CSS for rendering on the web

With these languages you can publish your map with the basetiles loaded and your data layers appropriately geocoded; with JavaScript you can also add to the interactivity of your map, revealing metadata in the tooltips

Get started building web maps using

cartodb

Using CartoDB you can:

  • easily overlay data onto a map
  • analyze the data to reveal spatial patterns
  • tell stories by creating beautiful visualizations
  • and then share them with the world!

CartoDB combines:

  • the power of PostGIS and SQL
  • CartoCSS for map styling
  • JavaScript for overlay and interactivity
  • Mapnik for tile rendering

These technologies are all packaged into one easy-to-use online interface.

Examples

Source: The Data Visualization Catalogue.

Time Travel Map

Source: Time Travel Between Counties, CartoDB.js

DATA SEARCH TOOLS

GDELT Geographic News Search Tool

Source: GDELT Geographic News Search Tool

Journalists have used the GDELT data to track wildlife crime, and the spread of the Islamic State in the Middle East among other things.

You can fork the GDELT hourly synced data set from the CartoDB Data Library and add it as a layer on your map or use the Geographic Search Tool linked above to search for tags of interest.

CHART GRAPHICS

County Chart

Source: Geogia County Car Crash Counts, C3.js

Planning a web map

  • What is the purpose of the map?
  • Where can I get the data?
  • Will the map be queried for additional information?
  • Will the map be viewed on multiple devices?

Data Import + Sync Tables

Geospatial data is info that ids a geolocation and its characteristic features/frontiers, typically represented by points, lines, polygons, and/or complex geographic features.

Issues:

Geocoding + SQL/PostGIS The most basic SQL statement is:

SELECT * FROM table_name
  1. SELECT is what you're requesting (required)
  2. FROM is where the data is located (optional)
  3. WHERE is the filter on the data you're requesting (optional)
  4. GROUP BY and ORDER BY are optional additions, you can read more about aggregate/other functions below.

There are three special columns in CartoDB:

  1. the_geom
  2. the_geom_webmercator
  3. cartodb_id

The first of these is in the units of standard latitude/longitude, while the second is a projection based on the original Mercator projection but optimized for the web. cartodb_id is a unique number identifying row numbers and is very fast for executing queries.

If you want to run SQL commands and see your map update, make sure to SELECT the the_geom_webmercator because this is the column that's used for mapping--the other is more of a convenience column since most datasets use lat/long. If you want to keep interactivity (infowindows, etc.), you need to include cartodb_id in the query results.

Sync Tables

Sync Tables

The Editor is setup to process realtime data updates via sync tables.

You can import data that lives online via a URL, and set it to pull and update your map at regular intervals.

Check the file types supported in sync tables; keep in mind that it also works with Dropbox + Google Drive.

Notes:

  • to auto-geocode a sync table, verify that it contains the following:
    • country column, a latitude column and a separate longitude column
    • a column of IP addresses
    • postal codes
  • to edit sync tables you need to be disconnected from the data source, so during syncing, you can use SQL to manipulate the dataset on the fly
  • you can create sync tables in both the Editor and via the Import API

Customizing UI + CartoCSS

Basemaps

You have myriad customization options in the in-browser editor:

  • sql - run sql and postgis functions across your data
  • wizard - adjust the type, colors and fills in your map
  • infowindow - create hovers, tooltips with information from your datatables
  • css - customize the css and style of your map outside the wizard
  • legends - create keys for your map
  • filters - filter the data without sql

Likewise, many types of visualizations:

  • Simple -- most basic visualization
  • Cluster -- counts number of points within a certain binned region
  • Choropleth -- makes a histogram of your data and gives bins different colors depending on the color ramp chosen
  • Category -- color data based on unique category (works best for a handful of unique types)
  • Bubble -- size markers based on column values
  • Intensity -- colors by density
  • Density -- data aggregated by number of points within a hexagon
  • Torque -- temporal visualization of data
  • Heat -- more fluid map of concentration; emphasis on far over near-view
Styles
  • Marker Fill: change the size, color, and opacity of all markers
  • Marker Stroke: change the width, color, and opacity of every marker's border
  • Composite Operation: change the color of markers when they overlap
  • Label Text: Text appearing by a marker (can be from columns)
Infowindows/hovers

Infowindow options

  • Select which column data appear in infowindow by toggling column on
  • Customize further by selecting HTML-view
Basemaps

Basemap options

Check out the base CartoDB Basemaps from Stamen.

Make a map showing near real-time fire readings from MODIS

hotspot map

http://cdb.io/1LjqaoD

Find data in the CartoDB Data Library

  • Search for the following datasets in the CartoDB Data Library and add them to your account:
    • ne_50m_land
    • ne_50m_ocean
  • Add graticule lines from Natural Earth to CartoDB
    • New Dataset
    • Copy/paste the URL below and hit Submit
      • http://www.naturalearthdata.com/http//www.naturalearthdata.com/download/50m/physical/ne_50m_graticules_15.zip

Add near-real time MODIS active fire data

Add the layers to a map

  • New Map
    • Find the three layers from above, highlight, and click Create Map
  • Order Layers
    • Put the layers in the following order from top to bottom:
      • global_24hr
      • ne_50m_land
      • ne_50m_graticule_15
      • ne_50m_ocean

Project Layers

  • Our final map uses the Robinson Projection. One of the really powerful capabilites of CartoDB is the ability to project layers on the fly and publish that to your web map. To use the Robinson Projection, we need to add it to your list of availble projections (there is a table in your account called Spatial Ref Sys).
    • To add the Robinson Projection, copy and paste the information here into the SQL tray:
  INSERT into spatial_ref_sys (srid, auth_name, auth_srid, proj4text, srtext) values ( 54030, 'ESRI', 54030, '+proj=robin +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs ', 'PROJCS["World_Robinson",GEOGCS["GCS_WGS_1984",DATUM["WGS_1984",SPHEROID["WGS_1984",6378137,298.257223563]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Robinson"],PARAMETER["False_Easting",0],PARAMETER["False_Northing",0],PARAMETER["Central_Meridian",0],UNIT["Meter",1],AUTHORITY["EPSG","54030"]]');
  • Use ST_Transform to project each layer
    • We'll project each layer in the World Robinson projection
    • To do this we'll use ST_Transform along with the SRID for the projection
    • Expand the view for ne_50m_land, click on SQL for the SQL tray and add the following:
    SELECT 
      ST_Transform(the_geom, 54030) 
    AS 		
      the_geom_webmercator
    FROM 
      ne_50m_land
    
    • Do the same for ne_50m_ocean and ne_50m_graticule_15
  • For the global_24hr active fire readings from MODIS, we'll project, and query the data for attributes that we'll use to symbolize the overlay.
  • On our final map
    • we only want to display fires that have a confidence value of greater than or equal to 50
    • we'll symbolize the points based on their brightness
    • have the brightest points drawing on top
    • and enable interactivity on the fire point To do this, add the following to the SQL tray for global_24hr:
SELECT 
  ST_Transform(the_geom, 54030) 
AS 		
  the_geom_webmercator,
  cartodb_id,
  confidence,
  brightness
FROM 
  global_24h
WHERE
  confidence>=50
ORDER BY 
  brightness ASC

Map Styling

Change the basemap

  • Since we are styling our own simple basemap, let's remove the default basemap from Positron to a solid background
    • Click on Change Basemap in the bottom left hand corner
    • Click on the color chip, and choose white

Style each layer

  • We want our theme (active fire readings) to be highest in the visual hierarchy in our final map. In order to achieve this, we will style our land, graticule, and ocean layers using minimal colors:

ne_50m_ocean:

#ne_50m_ocean {
  polygon-fill: #9fc4dd;
  polygon-opacity: 0.7;
}

ne_50m_graticules_15:

#ne_50m_graticules_15{
  line-color: #FFFFFF;
  line-width: 0.5;
  line-opacity: 0.7; 
}

ne_50m_land:

#ne_50m_land{
  polygon-fill: #ede1d8;
  polygon-opacity: 1;
}
  • Now let's take a look at what options are available to symbolize the fire data:
    • Click on the Wizard
    • Look through the different options
      • symbolize based on choropleth points
      • choose 5 buckets and classification scheme
    • Try out some compositing operations
  • If you like, you can also change the colors of the fire points on your map
    • An easy way to test out colors is using CartoCSS variables
    • Click on the CSS tab and try assigning each class a color based on a variable:
    @1:#FFF700;
    @2:#FF7C3B;
    @3:#E03E36;
    @4:#B80D57;
    @5:#700961;
    

Here is the styling I used:

/** choropleth visualization */

  @1:#FFF700;
  @2:#FF7C3B;
  @3:#E03E36;
  @4:#B80D57;
  @5:#700961;

#global_24h{
  marker-file: url(http://com.cartodb.users-assets.production.s3.amazonaws.com/maki-icons/square-18.svg);
  marker-fill-opacity: 0.8;
  marker-line-color: #FFF;
  marker-line-width: 1;
  marker-line-opacity: 1;
  marker-width: 10;
  marker-fill: @1;
  marker-allow-overlap: true;
}
#global_24h [ brightness <= 502.71] {
   marker-fill: @5;
}
#global_24h [ brightness <= 402.2] {
   marker-fill: @4;
}
#global_24h [ brightness <= 375.7] {
   marker-fill: @3;
}
#global_24h [ brightness <= 352.7] {
   marker-fill: @2;
}
#global_24h [ brightness <= 329.8] {
   marker-fill: @1;
}

Add Popups

  • Click on the infowindow option on the global_24hr layer
  • Choose the style and information you want to show in your popup

Add a title, annotations, etc.

  • Click the option to Add Element
  • And choose Add title item
  • Change the placement, font, color, etc.

Select map elements

  • Click on options and choose which map elements you want from the list

Publish the final map

Other notes:

  • You can use this simple basemap again for different themes of information and style it accordingly
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment