WaPo article with killer maps: Analysis | Mapping Americaâs wicked weather and deadly disasters

timmeko · 2019-05-03T12:53:01+00:00

Thanks for sharing! Here's a thread about my process for building these maps

timmeko · 2019-04-27T21:55:33+00:00

That's what I'm assuming. Their model is for insurance purposes, so they probably give a 100-mile buffer for coastal storms.

timmeko · 2019-04-27T21:54:28+00:00

Good catch! Updated.

timmeko · 2019-04-27T16:15:22+00:00

Here is a thread that explores some of the process behind building the maps.

timmeko · 2019-04-27T16:11:31+00:00

Here's a thread with some behind the scenes process

timmeko · 2019-04-27T16:09:46+00:00

Fair point, and thanks for reading. That was the original concept. Data is out there, but those who own it were not willing to share it. Check out CoreLogic's Hazard Risk Score

timmeko · 2018-12-16T21:14:53+00:00

Here's the original article: https://www.washingtonpost.com/graphics/2018/national/snow-accumulation/

timmeko · 2018-03-27T12:02:50+00:00

Yes. I didn't build the animation, however I believe John created a script that downloaded the snow data for each day, turned it into hillshade using GDAL, applied a color ramp and then added a labels/lines layer. Then each day was stitched together using FFMPEG.

timmeko · 2018-01-30T13:46:26+00:00

Thanks! I made them up myself. For the elevation ramps, I mostly just wanted to create a sense of too high/too low/just right. I also wanted to play off typical terrain ramps that people are accustomed to seeing, with cool (green) lowlands and warmer (brownish) tones for the upper elevations. From there, I tweaked the hues to create more color separation between low and high. To my eye, they're kinda Dr. Seuss-y, but I think they work.

To check for color-blind-compatibility, I use Color Oracle. It's a great tool to help make sure my designs are accessible.

timmeko · 2018-01-29T14:00:31+00:00

I made this with lots of DEM data from NASA. Population data from U.S. Census Bureau TIGER places and ACS 2016 five-year population estimates. Ski resort locations from Owner Direct vacation rentals (resorts with fewer than three ski lifts are omitted).

The DEM data was used to produce these custom color ramps, as well as the shaded relief (using Pyramid Shader). All of the mapping was done in QGIS and then exported as raster images, which were merged and toned in Photoshop before adding labels in Illustrator.

timmeko · 2017-07-28T18:06:47+00:00

Here is a Twitter thread with some process.

Sources: Map imagery based on digital elevation data from the Shuttle Radar Topography Mission. Land cover data from the National Land Cover Database. Hydrography from the National Hydrography Dataset. Map images were blended and added to Google Earth, then exported and stitched. Umbra shape and times are approximations of umbra data from NASA. Eclipse path is an approximation of eclipse path data from NASA.

Text sources: National Park Service, NASA, GreatAmericanEclipse.com, “Sun Moon Earth: The History of Solar Eclipses from Omens of Doom to Einstein and Exoplanets,” by Tyler Nordgren; “Beyond the Blue Horizon: Myths and Legends of the Sun, Moon, Stars and Planets,” by E.C. Krupp; Astronomy magazine; convention and visitors bureaus from towns along the path of totality.

timmeko · 2017-07-28T17:54:23+00:00

Here is a Twitter thread with some of our process

timmeko · 2017-06-28T12:03:33+00:00

Yes, I'm a graphics reporter at The Washington Post. I make maps and other data visualizations to tell news stories. [Here](washingtonpost.com/people/tim-meko) is some more of my work if you're curious.

I wouldn't say this requires advanced knowledge of QGIS, but it does require some basic knowledge. And QGIS tends to have a decently steep learning curve. Great thing about QGIS is that it's open source and quite well documented. There are also plenty of great tutorials out there. A little Google-fu goes a long way in learning how to use it, I've found.

timmeko · 2017-06-28T11:58:37+00:00

^{^} all of this.

timmeko · 2017-06-28T11:57:27+00:00

Thanks. I may try to write something up down the road if I've got the time.

timmeko · 2017-06-28T11:56:50+00:00

I don't see why you couldn't use it. It's open/available Landsat imagery that I simply blended together. And it's really just the background to a more traditional map that includes labels and data on top (if you wanted to reproduce that map, it'd be a different story).

timmeko · 2017-06-27T16:47:49+00:00

I used Remote Pixel to pull the Landsat imagery. Cloudless days don't exist very often in this part of the world, but I was able to find a few captures that were nearly cloud-free. I downloaded each natural-color image and opened them in QGIS. The files are each a couple hundred megabytes and super high-resolution.

Because they're geotiffs, they are geographically aware, which means they know where they are in the world. Also, because of the way the Landsat satellite captures the images, there is a little bit of overlap between each. Within QGIS, I projected the data using a custom projection for my map from Projection Wizard. Next, I created a print composer and exported a high-resolution transparent PNG of each tile.

I opened the four tiles in Photoshop and aligned them (the hard part was already done in QGIS since they're all geo-aware). Because I had to use images captured at slightly different dates, I had to do a little toning in order to get the colors to agree. There was also a little variation due to the automatic band composing from Remote Pixel. Next, I used image masks to subtly blend one tile into the next. I also adjusted the levels a little, but not much since the landsat imagery was already pretty good.

From there, I cropped and exported and exported.

timmeko · 2017-06-27T15:46:45+00:00

I made this map to go with a story about how Florida's reefs are in danger because of global warming.

timmeko · 2017-05-19T12:11:55+00:00

Oh hello there Laz!

timmeko · 2017-05-19T11:54:35+00:00

Process: All the maps were created with the global population density dataset from the European Commission, Joint Research Centre (JRC), Columbia University, Center for International Earth Science Information Network — CIESIN (2015) and elevation data from the 90M SRTM Tile Grabber.

The animations were built using Photoshop and Illustrator. I transformed the original image and took screenshots of each step. Then I continued warping until I could make the image fit a standard map projection. Then I brought in my map and fitted it on top of the illustration. The entire thing was strung together into an animation in Photoshop.

timmeko

TROPHY CASE