Wednesday, December 13, 2017

Dreaming of a White Christmas


One of NOAA's most popular interactive maps is the First Snow Map, which provides a nationwide guide to when you can expect the first snow of the winter. The map shows the date at your location when the chance of snow is at least 50%, based on historical weather records. NOAA have also created a similar looking map which shows the historical predictability of whether you can expect a white Christmas.

The Are you dreaming of a white Christmas? map uses historical weather data to provide a prediction of the chance of experiencing at least 1 inch of snow at your location on Christmas Day. The whiter the map at your location then the more chance you have of having a white Christmas. The chances of you experiencing a white Christmas are based on the last three decades of weather records at your location.

150 Years of Mountain Photography


Between 1861 and 1958 land surveyors took thousands of photographs of Canadian mountains. These photos provide a wonderful resource of Canada's environmental history. A resource which scientists can use to observe how the environment has changed since the photos were taken.

The Mountain Legacy Project (MLP) has spent the last nine years working out where each of the original land surveyor photos were taken. They have then traveled to each location to capture the exact same views with brand new photographs. By comparing the new photographs with the originals the Mountain Legacy Project can then document how the landscape and environment has changed over the years.

You can examine how Canada's mountains have changed for yourself using the MLP's Explorer. This interactive map allows you to explore the MLP collection of historical photographs by location and directly compare the historical view with the same view today, as depicted in MLP's modern photos.

While exploring the MLP collection of historical and modern photos you can use the Image Analysis Toolkit to directly compare the historical and modern photos of the same view. The Image Analysis Toolkit includes a number of visualization tools for comparing any two photos side-by-side. If you want to spot signs of global warming between the historical and modern views then you might want to look out for glacial change, changes in tree cover (tree lines creeping higher), vegetation change and retreating snowcaps.

36 Years of American Wildfire


The most common cause of wildfires in the United States is lightning. However a large number of wildfires are started by humans, both deliberately and accidentally. You can now explore the causes of wildfires in the USA on a new interactive map.

Jill Hubley has mapped every single American wildfire since 1980. Her interactive map, U.S. Wildfire Causes 1980-2016, visualizes historical wildfire data and even shows which fires were caused by humans and which had natural causes.

The U.S. Wildfire Causes map uses Federal Wildland Fire Occurrence Data from 1980 until 2016. It shows fires started by humans (like accidents or arson) in orange and natural causes in green. No base map is shown under the data when the user is zoomed out on the map. A base map is hardly needed as the wildfire data on its own creates an easily recognizable map of the United States. However a base map is added to the map when you zoom-in, so it is possible to explore the wildfire data by location.

If you click on the 'Specific Cause' button you can view the wildfires colored by the specific natural or human cause. You can also view all the causes of wildfires ranked by the number of acres burned. For most years lightning is the most common cause of wildfire, although in 1980 and 1985 pyromania was the top cause. In most years pyromania and cooking fires appear among the most common causes of wildfires.

Tuesday, December 12, 2017

How Time Can Bend Space

Showing how long it takes to travel between two different points on a map can be difficult. The most common approach is probably to use an isochrone layer, which uses color to visualize journey times geographically.

In the example above, from Mapbox, driving times from a selected point on the map are shown using different colors. In this example there is a continual gradation between the different colors. However in lots of isochrone maps lines are drawn on the map connecting points which can be reached in the same travel time. For example lines might be used to show how far you can travel in 10, 20 & 30 minute increments.

Another approach to visualizing travel time on a map is to use a time cartogram. In a time cartogram geographic distance on the map is replaced by a time attribute such as travel time (Eric Fischer has posted a few time cartograms of San Francisco to Flickr). However the problem with time cartograms (as with all cartograms) is legibility. When you distort a map by some other variable apart from distance the map can quickly become illegible, as users struggle to recognize the geography.


Nate Parrott has created an interactive time cartogram to show NYC Subway Travel Time. If you click on a subway station on Nate's map then the subway map automatically redraws itself so that the distance to all stations is based on the journey time from your selected station. This interactive time cartogram works really well as a visualization of journey times and it doesn't suffer from the usual problems of illegibility common to many time cartograms.

There are a number of reasons why the NYC Subway Travel Time Map works so well. To start with users are already familiar with the concept that transit maps distort geography and are not strictly geographically accurate. Users are also familiar with the use of colored lines to show the transit system's different lines. If you are already familiar with a line and its stations on the New York subway map then you will still be able to pick it out on a distorted time cartogram based on the line's color. Even if the NYC Subway Travel Time map confuses you then you can still mouse-over a station on the map and quickly reorient yourself with the New York subway.


If you want to make your own isochrone travel time maps then you might like this How to Make a Travel Time Map post.

Chicago Energy Consumption


The Chicago Energy Database Map is a multivariate visualization of electricity and gas consumption in Chicago neighborhoods. The map uses both color and height in order to show two different variables. Gas consumption in each neighborhood is shown on the map using color, while the height of the neighborhood reflects the amount of local electricity consumption.

Using 3d towers and color allows the map to show two different variables at the same time. The result is an effective visualization of energy consumption in Chicago, as users can clearly see that both gas & electricity consumption is lower in the city center than in the surrounding neighborhoods.

The Chicago Energy Database Map does have some problems as a multivariate visualization but these problems are largely due its age.The map is a few years old now and appears to have been designed in Leaflet using some trickery to provide the oblique bird's eye view of the city map. The result is that the user can't tilt the map and can only rotate the map in 90 degree stages. This can make it a little difficult to view all of the neighborhoods on the map, as the taller neighborhoods in the foreground can obscure any shorter neighborhoods behind them.

Today the map could be created using a modern vector map library, such as Mapbox GL - which supports pitch & bearing. If the map was recreated in Mapbox GL the user would be able to tilt and rotate the map at will and would be able to explore the data more easily. You can view some examples of 3d towers being used to visualize two or more variables in this post on Mapping Population in 3D. You can view a few other methods of mapping more than one variable in Jim Vallandingham's Multivariate Map Collection.

Monday, December 11, 2017

Guns Across State Lines


New Jersey has some of the most restrictive firearm laws in the country. Unfortunately for New Jersey most of the other 49 states aren't so fussy about selling guns. That might be why 79% of guns in New Jersey recovered and traced by the Bureau of Alcohol, Tobacco, Firearms and Explosives were bought out of state.

Axios has mapped the ATF's Firearms Trace Data - 2016 to show the top ten out of state sources for firearms for each U.S. state. The interactive flow map in How guns move across state lines visualizes the top ten out of state sources for recovered and traced guns in each state. If you hover over a state you can see how many guns were traced by the ATF in that state in 2016. You can also see the percentage which were originally purchased out of state and the ten states where the most guns were originally purchased.

If you want to make your own interactive flow map then you might be interested in Sarah Bellum's Canvas Flowmap Layer for ArcGIS or the Leaflet.Canvas-Flowmap-Layer.

The Geography of Long Life


Female babies born in the UK this year can expect to live until they are 85.8 years old. If they are male then they can hope to live until they are 82.3 years old. However a new born's life expectancy can vary a lot depending on where they live in the country.

The UK's Office for National Statistics has released information on the Health State Life Expectancies 2014 to 2016, which examines life expectancy in each area of the UK. This ONS report includes two interactive maps; one visualizing life expectancy in each local area in the UK and the other showing the gain in life expectancy in each local area since 2001-2003.

Healthy life expectancy at birth can vary across local areas of the UK by 18 years. The best places to live if you want a long healthy life is Richmond upon Thames if you are male (69.9 years) and the Orkney Islands if you are female (73.0 years). The worst places to live are Dundee City for males (54.3 years) and Manchester for females (54.6 years).

Sunday, December 10, 2017

The First #uksnow of Winter


It's snowing! There's nothing quite like the excitement of waking to the first snow of winter, grabbing your phone and visiting the #uksnow Map.

The #uksnow Map maps the location of snow in the UK based on the number of tweets that mention snow. To add snow to the map you just need to include the hashtag '#uksnow' in a Twitter message and a UK postcode. You should also rank the amount of snow out out of ten (where 0/10 = no snow and 10/10 = a blizzard).

The #uksnow Map includes an option to view all the photos of snow that have been posted on Twitter. Just click on the photo icon attached to the Twitter sidebar and thumbnails of the photos will appear in the sidebar. Just click on any of the thumbnails to view the image in full-size.

Now where did I put put my sledge?

Saturday, December 09, 2017

Trees of Edinburgh


The Edinburgh Tree Map uses data from a number of sources to map Edinburgh's trees. The map uses colored map markers to show the locations of the city's trees by species.

Using the map menu it is possible to view individual tree species separately on the map or to view all species at once. If you select a tree on the map you can view its Google Maps' Street View image and details about the tree's height and age. Each tree also has its own unique URL (click on a tree to get its link), which means you can share a link to any tree on the map.

The Edinburgh Tree Map was built using Leaflet.js and the Carto Maps API. If you don't want to build your own map and database then you can create a tree map with OpenTreeMap, a paid service which was used to create the Los Angeles and San Francisco tree maps (linked below)

Other Tree Maps:

San Francisco
New York
Los Angeles
London
Melbourne
Madison, Wisconsin

Friday, December 08, 2017

The Most Fragile Cities Around the World


Three of the most at risk cities in the world, Mogadishu, Kismaayo, and Merca, are in Somalia. At the opposite end of the scale Canada, Japan and Australia are home to some of the least at risk cities.

Fragile Cities is an interactive map which allows you to explore the fragility of 2,100 cities around the world. The Fragile Cities project ranks cities using 11 different metrics, which consider areas such as income inequality, natural & man-made risks and access to services.

If you select a city on the map you can view its Fragile Cities fragility rank. You can also view how it ranks under all 11 of the fragility metrics. The map includes a number of themed map visualizations which provide a closer view of the fragility hot-spots around the world. The slide control at the bottom of the map also allows you to view the cities' fragility ranks for every year since 2000.