Visualizations: Geographic/GIS

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--D. Thiebaut 17:58, 6 March 2013 (EST)


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This page is maintained by Dominique Thiebaut and contains various interesting visualization examples or related material gathered on the Web, and in various publications. Editing of this page by anonymous users is not enabled, but feel free to email dthiebaut-at-smith.edu with your own discoveries, which will be promptly added!

The different visualization systems shown below are organized by application domains, and by type (borrowed and adapted from Viz4All).

The application domains include:



Contents


Geographical/GIS

100%

Pinging all Devices on the Internet

HDMooreCriticalIO.png

Category: Internet/Geographic GIS
Where: HDMoore Projects.
Implementation: NA
Date: August 2014

From www.technologyreview.com: [HD] Moore’s census involved regularly sending simple, automated messages to each one of the 3.7 billion IP addresses assigned to devices connected to the Internet around the world (Google, in contrast, collects information offered publicly by websites). Many of the two terabytes (2,000 gigabytes) worth of replies Moore received from 310 million IPs indicated that they came from devices vulnerable to well-known flaws, or configured in a way that could let anyone take control of them.






24 Hours of Air Traffic from NATS

Category: GIS/Aviation
Where: NATS Aero
Implementation: NA
Date: March 2014

From Wired's Kyle VanHemert: Watch an Entire Day of Air Traffic in One Astonishing Visualization. The folks at NATS, responsible for handling much of the air traffic control in Great Britain and elsewhere, know the delicate dance better than just about anyone. To give us a sense of what keeps them busy day to day, they put together this stunning video. Running at 1,440 times regular speed, the viz is striking as pure laser light spectacle. But the closer you watch, the more fascinating details you’ll find. The clip combines UK radar data from June 21 of last year and flight plan data from the rest of the continent from July 28.









Earth: Wind Patterns displayed in Real Time

NullSchool.png

Category: GIS/scientific
Where: Cameron Beccario http://earth.nullschool.net/
Implementation: Natural Earth, D3.js, when.js, backbone.js, node.js. Source code available on github.
Date: January 2014

From earth.nullschool.net: "earth" is a project to visualize global weather conditions. The main components of the project are:
  • a script to download and process Global Forecast System weather data in GRIB2 format from the National Centers for Environmental Prediction, NOAA / National Weather Service.
  • a GRIB2 to JSON converter (see the grib2json project).
  • scripts to push site files to Amazon S3 for static hosting.
  • a browser app that interpolates the data and renders an animated wind map.

An instance of "earth" is available at http://earth.nullschool.net. It is currently hosted by Amazon S3 and fronted by CloudFlare.







Animating the Whaling Industry

Category: Geographic/GIS/Animation
Where: sappingattention.blogspot.com.es
Implementation: NA
Date: 2013

From sappingattention.blogspot.com.es: This makes use of visualization again, but as a narrative technique rather than the heuristic role it played in data selection. Narrating voyages through data visualization clarifies the unique role of the whaling industry in American shipping: it is both the primary industrial use of the sea (as opposed to commercial voyages that reach across it), and a self-exhausting process of resource depredation that gives an unlikely perspective on the movement patterns of early American capitalism. The progressive depletion of whaling grounds drives the fleet farther and farther afield each year, expanding the reach of American voyagers.







Early American Shipping Routes

EarlyAmericanShipping.png

Category: GIS/Geographic
Where: sappingAttention.blogspot.com.es
Implementation: NA
Date: 2013

From sappingattention.blogspot.com.es: To do humanistic readings of digital data, we cannot rely on either traditional humanistic competency or technical expertise from the sciences. This presents a challenge for the execution of research projects on digital sources: research-center driven models for digital humanistic resource, which are not uncommon, presume that traditional humanists can bring their interpretive skills to bear on sources presented by others.



DataAppeal

DataAppeal3DMap.png

Category: Geographic/GIS
Where: Dataappeal.com/
Implementation: Google Earth +?
Date: July 2012

From fastcoexist.com: "I was interested in the idea that 3-D data maps always get superimposed on the Google Earth platform so you can walk through data, but in the back of my head, I always had that satellite view. We were always looking for ways to superimpose much more artful and sexier types of basemaps to attract people," explains Nadia Amoroso, the co-founder of DataAppeal. "The whole idea is to introduce the artistic aspect of 3-D data modeling and still keep the analytics, the numbers side."



Wikipedia Live Updates from Hatnote

MediaWikiLiveUpdates.png

Category: GIS/Social Network
Where: hatnote.com
Implementation: d3, DataMaps, freegeoip.net, and the Wikimedia RecentChanges IRC feed, broadcast through wikimon. Source available on github.
Date: May 2013

From hatnote.com: When an unregistered user makes a contribution to Wikipedia, he or she is identified by his or her IP address. These IP addresses are translated to the contributor’s approximate geographic location. A study by Fabian Kaelin in 2011 noted that unregistered users make approximately 20% of the edits on English Wikipedia: likely closer to 15%, according to more recent statistics], so Wikipedia’s stream of recent changes includes many other edits that are not shown on this map.
You may see some users add non-productive or disruptive content to Wikipedia. A survey in 2007 indicated that unregistered users are less likely to make productive edits to the encyclopedia. Do not fear: improper edits can be removed or corrected by other users, including you!
How it works: this map listens to live feeds of Wikipedia revisions, broadcast using wikimon. We built the map using a few nice libraries and services, including d3, DataMaps, and freegeoip.net. This project was inspired by WikipediaVision’s (almost) real-time edit visualization.




MapsData

Mapsdata.png

Category: Geographical/GIS
Where: mapsdata.co.uk which is part of Inquiron, a data visualization and custom mapping company based in Dubai.
Implementation: NA
Date: NA

From mapsdata.com: How to Get Data: The data you want to visualize may be data you already have in your business or organization. If not, or as an example, you can use the data sets that are freely available online. We provide links to great free data sets in the containers to the right, listed by type of source.

Most sources provide files in common formats such as .xls or .csv. Download these files to your computer before moving on to the next step: structuring your data.



Geo-Mapping Data using Tableau

TableauStepByStep 11.png

Category: Geographical/GIS
Where: Tutorial on dftwiki
Implementation: Tableau
Date: 2013

From DFTwiki: This is a series of (quick) steps taken to generate a geographical representation of a list of countries appearing in a CSV-formatted file (comma-separated values). The Tableau software package is used to display the map. The representation associates to each country the number of lines in the file that contain that country. For example, if the country "Belgium" appears 100 times in the CSV file, the value 100 will be associated with Belgium, and the darkness of the color used to show the country will be chosen to show the intensity of 100 compared to the most cited country.



Google Charts Geo-Maps

GoogleMap3.png

Category: GIS/libraries
Where: Google Charts
Implementation: Javascript
Date: 2013

From Geo-Mapping Data using Google Charts : This [tutorial provides] a series of (quick) steps taken to generate a geographical representation of a list of countries appearing in a CSV-formatted file (comma-separated values). The Google Charts library is used to display the map. The representation associates to each country the number of lines in the file that contain that country. For example, if the country "Belgium" appears 100 times in the CSV file, the value 100 will be associated with Belgium, and the darkness of the color used to show the country will be chosen to show the intensity of 100 compared to the most cited country. Some Python code is used to generate the HTML/Javascript code.



Exhibit

ExhibitMap.png

Category:
Where: [http://www.simile-widgets.org/exhibit/ simile-widgets.org
Implementation:
Date: 2012?

From simile-widgets.org/exhibit : Exhibit 3.0 is a publishing framework for large-scale data-rich interactive Web pages.

Exhibit lets you easily create Web pages with advanced text search and filtering functionalities, with interactive maps, timelines, and other visualizations. The Exhibit 3.0 software has two separate modes: Scripted for building smaller in-browser Exhibits, and Staged for bigger server-based Exhibits.







ModestMaps

ModestMaps.png

Category: GIS/Library
Where: ModestMaps.com
Implementation: Javascript
Date: 2012

From ModestMaps.com: odest Maps is a small, extensible, and free library for designers and developers who want to use interactive maps in their own projects. It provides a core set of features in a tight, clean package with plenty of hooks for additional functionality.

It doesn't try to include every possible map control or layer type. It's designed to be a simple platform to build upon. The code is well-designed, tested and deployed widely - thousands of maps already use the toolkit. And while we aim for the highest performance and compatibility with new technology, it is tested against older browsers, including Internet Explorer.








Top 20 visualization tools

Top20GISTools.jpg

Category: GIS/Geographic/libraries
Where: Brian Suda, at netmagazine.com
Implementation: NA
Date: Sept. 2012

From netmagazine.com: From simple charts to complex maps and infographics, Brian Suda's round-up of the best – and mostly free – tools has everything you need to bring your data to life.

One of the most common questions I get asked is how to get started with data visualisations. Beyond following blogs, you need to practise – and to practise, you need to understand the tools available. In this article, I want to introduce you to 20 different tools for creating visualisations: from simple charts to complex graphs, maps and infographics. Almost everything here is available for free, and some you have probably installed already.




Leaflet

Leafletjs.png

Category: Software/Libraries/GIS/Algorithms
Where: leafletjs.com
Implementation: Javascript
Date: 2010

From leafletjs.com: Leaflet is a modern open-source JavaScript library for mobile-friendly interactive maps. It is developed by Vladimir Agafonkin with a team of dedicated contributors. Weighing just about 28 KB of JS code, it has all the features most developers ever need for online maps.

Leaflet is designed with simplicity, performance and usability in mind. It works efficiently across all major desktop and mobile platforms out of the box, taking advantage of HTML5 and CSS3 on modern browsers while still being accessible on older ones. It can be extended with many plugins, has a beautiful, easy to use and well-documented API and a simple, readable source code that is a joy to contribute to.






NASA:Salt Concentration Levels in the Sea

NasaSeaSalt.jpg

Category: Geographic/Scientific
Where: NASA.gov
Implementation: NA
Date: Feb. 2013

From NASA.gov/News : The colorful images chronicle the seasonal stirrings of our salty world: Pulses of freshwater gush from the Amazon River's mouth; an invisible seam divides the salty Arabian Sea from the fresher waters of the Bay of Bengal; a large patch of freshwater appears in the eastern tropical Pacific in the winter. These and other changes in ocean salinity patterns are revealed by the first full year of surface salinity data captured by NASA's Aquarius instrument.







Wind Map

Windmap.jpg

Category: Geographic/GIS
Where:Viegas and Wattenberg, http://hint.fm
Implementation: HTML & Javascript
Date: 2012?

From hint.fm: The map was created in the cold winter months when wind was much on our minds. It conveys the movement of the air in the most basic way: with visual motion. As an artwork that reflects the real-world, its emotional meaning changes from day to day. On calm days it can be a soothing meditation on the environment; during hurricanes it can become ominous and frightening.

About the technique: The general technique of using comet-like trails to show motion goes back to Edmund Halley in 1686 (see Fowler & Ware). Many scientists (Fowler & Ware, Jones & Saito, van Wijk, etc.) have described variations during the past few decades. Our map is designed to provide a dense, easily readable field and to highlight areas of high wind speed. It's implemented entirely in HTML and JavaScript.




Data-Vis of Wikipedia Meta-Data

WikipediaAuthorsByLocation.jpg

Category: Geographic/SocialNetwork
Where: Olivier H. Beauchesne at olihb.com
Implementation: Python and Java
Date: Jan 2013

From olihb.com ( first reported by fastCodesign.com): A large number of Wikipedia articles are geocoded. This means that when an article pertains to a location, its latitude and longitude are linked to the article. As you can imagine, this can be useful to generate insightful and eye-catching infographics. A while ago, a team at Oxford built this magnificent tool to illustrate the language boundaries in Wikipedia articles. This led me to wonder if it would be possible to extract the different topics in Wikipedia.

This is exactly what I managed to do in the past few days. I downloaded all of Wikipedia, extracted 300 different topics using a powerful clustering algorithm, projected all the geocoded articles on a map and highlighted the different clusters (or topics) in red. The results were much more interesting than I thought. For example, the map on the left shows all the articles related to mountains, peaks, summits, etc. in red on a blue base map. The highlighted articles from this topic match the main mountain ranges exactly.

The author also shares some of the tools that he used to gather the data, and parse it. Among them are:




WebGL Globe

WebGLGlobe.png

Category: GIS
Where: Google Data Arts Team
Implementation: NA
Date: 11/21/12

From WebGL Globe (Google) : The WebGL Globe is an open platform for geographic data visualization. We encourage you to copy the code, add your own data, and create your own.

If you do create your own globe, please share it with us. We will post our favorite links below.

Features:
Latitude / longitude data spikes
Color gradients, based on data value or type
Mouse wheel to zoom
More features are under development...





Population Density

Dwtkns wordPopDensity.png

Category: Geographical
Where: dwtkns.com
Implementation: Processing?
Date: April 2012

From dwtkns.com: [This was done by] Derek Watkins 2012 / @dwtkns. Data generalized from CIESIN Gridded Population of the World, 2010. Concept stolen from Bill Bunge's "Islands of Mankind" at John Krygier's blog.














IndieMapper

IndieMapper.png

Category: Geographic/GIS
Where: indiemapper.com
Implementation: NA
Date: Jan 2012

From indiemapper.com: Indiemapper is a free online application from Axis Maps. It helps you make static, thematic maps from geographic data by bringing the best of traditional cartographic design to internet map-making.











Mapnificent

Category: GIS/Geographical
Where: http://stefanwehrmeyer.com/, author of mapnificent.net, Germany
Implementation: NA
Date: August 2011

From mapnificent.net: Mapnificent shows you the area you can reach with public transport from any point in a given time. It is available for major cities in the US and world wide.

You may be interested to watch a video about what Mapnificent can do, read a blog post about how Mapnificent works or jump to the Mapnificent API Documentation.

Mapnificent was originally inspired by MySociety's Mapumental which is sadly still in private beta.

Mapnificent was created by StefanWehrmeyer.




11 million deaths in Just-Cause 2

Category: Goegraphic/GIS
Where: flowingdata.com
Implementation: NA
Date: June 2011

From flowingdata.com : Sometimes visualizing everything can turn out beautiful results. It seems to work especially well when the data is geographic, as we saw with All Streets, OpenStreetMap edits, and tourist maps. It turns out the everything method works for fictional worlds, too. The above and the video below are nothing but 11.3 million deaths by impact with object or terrain in the game Just Cause 2.











Atlas of the Habitual

AtlasOfTheHabitual.png

Category: Geographic/GIS
Where: tlclark.com
Implementation: HTML
Date: May 2011

From [1]: For this atlas, categories were generated based on different aspects of my life and public data I found about the location. The dataset was used to recount memories, actions and interactions I had in my current residence of Bennington, Vermont, USA. This data can be presented in a virtually unlimited number of ways, depending on what one wanted to do with the data. Although the information holds great value to the individual, it could also be seen as a commodity.
With this dataset an auto insurance company would be able to see how often, and at what speed I drove based on the time between latitude and longitude positions in the dataset. The company could then cross-reference this to the speed limits on the roads I was on and prorate my policy to that information. If a loved one in another location had access, they could see how I spent my time. The information could also be seen as a travel journal or even a location-based check in service. Knowing this information could help or hurt a relationship with others due to one's location, activity or what company they kept.




World Population in 2100?

WorldPopulationBestiaro.png

Category: Scientific/Geographic
Where: Bestiaro.org
Implementation: Flash
Date: May 2011

From www.guardian.co.uk: What will happen to the world's population by 2100? Spanish design house Bestiaro has produced this visualisation of the UN population data for us using its Impure design language. Explore the data by sliding through the years below - all figures in thousands



















6 Months of Telephone Data

6MonthsOfTelephoneData.png

Category:
Where: zeit.de, Germany
Implementation: NA
Date: March 2011

From zeit.de: Green party politician Malte Spitz sued to have German telecoms giant Deutsche Telekom hand over six months of his phone data that he then made available to ZEIT ONLINE. We combined this geolocation data with information relating to his life as a politician, such as Twitter feeds, blog entries and websites, all of which is all freely available on the internet.







Old and New Maps of NYC

OldNewMapNYC.png

Category: Geographical/GIS/Maps
Where: The New York Times
Implementation: Interactive
Date: March 20, 2011

From 200th Birthday for the Map That Made New York, NYT: Two hundred years ago on Tuesday, the city’s street commissioners certified the no-frills street matrix that heralded New York’s transformation into the City of Angles — the rigid 90-degree grid that spurred unprecedented development, gave birth to vehicular gridlock and defiant jaywalking, and spawned a new breed of entrepreneurs who would exponentially raise the value of Manhattan’s real estate.







Android Activations World-Wide

Category: Geographic/GIS
Where: Google, reported by engadget.com
Implementation: NA
Date: Feb 2011

From engadget.com : Do you ever wish for an easier way to show your uninitiated friends what you mean when you say Android is growing? Well, here's the video for you: a Google-produced map of the world that throbs with Android activations over time, highlighted by some truly eye-opening flourishes in the immediate aftermath of marquee handset launches.











A Day in the Life of the MBTA

ADayInTheLifeOfTheMBTA.jpg

Category: GIS/Geographic/Transportation
Where: toddvanderlin.com
Implementation: NA
Date: Nov. 2009

From toddvanderlin.com : This project was a collaboration between Ryan Habbyshaw, Brad Simpson, and Todd Vanderlin. We began the project seven days ago when we learned of the competition and developed it from initial ideas to the final foldable posters within the week. Below is a brief description of the process of parsing, sorting, visualizing, and composing the final posters.

The subway data from August 12, 2009 was parsed in openFrameworks and Matlab using custom applications. Statistical analysis was performed in Matlab for subway loading (temporal and geographical including the entire MBTA, individual lines, and individual stations), rate of subway activity, and associated data. openFrameworks was used to generate the central visualizations for the project. Programs were written to interpret data that was processed into several arrangements to emphasize different trends within the data. Linear charts were used to display the activity of stations on a given line to show the geographic relation of activity throughout the course of the day. Circular 24-hour clocks for individual lines and stations were made in order to see the relative activity throughout the day. Pie charts were used to visualize rush hour commutes on each line, showing the contrast of activity during morning and evening rush hours. Histograms were used to show the breakdown of daily activity in a linear fashion. Layouts were done in Illustrator and visualizations were combined in order to create the five individual MBTA line posters and overall MBTA poster. Individual print posters are 33in x 23 in.




Lisbon traffic as living organism

Category: GIS/Greographic/Art
Where: mondeguinho.com
Implementation: NA
Date: Feb 2011

From mondeguinho.com : In this work the traffic of Lisbon is portrayed exploring metaphors of living organisms with circulatory problems. Rather than being an aesthetic essay or a set of decorative artifacts, my approach focuses on synthesizing and conveying meaning through data portrayal. This portrayal is embodied in the visualization: The Blood Vessels in the traffic of Lisbon. I use an adaptive physics system to build and manipulate the road network – the thickness, the color and the length of the vessels are excited by the number of vehicles and average velocity in each road. With this system I try to bypass the strictness of contemporary visualizations that depict data accurately through direct mappings.









Map of Collaboration between Researchers

MapOfCollaborationsInResearch.png

Category: Geographic/GIS
Where: science-metrix.com Olivier H. Beauchesne
Implementation: NA
Date: Jan 2011

From Beauchesne's blog: My employer, Science-Metrix, is bibliometric consulting firm. In other words, we engineer ways to measure the impact and growth of scientific discovery (and publications) in the world. To accomplish this, we license data from scientific journal aggregators like Elsevier’s Scopus and Thomson Reuter’s Web of Science. The data we have is bibliographic in nature. We don’t have the full text of the articles but rather citation networks, authors and their affiliations, abstracts, etc.

From this data, I extracted and aggregated scientific collaboration between cities all over the world. For example, if a UCLA researcher published a paper with a colleague at the University of Tokyo, this would create an instance of collaboration between Los Angeles and Tokyo. The result of this process is a very long list of city pairs, like Los Angeles-Tokyo, and the number of instances of scientific collaboration between them. Following that, I used the geoname.org database to convert the cities’ names to geographical coordinates.




Psst! Pass it On

Category: Geographical/GIS
Where: StayHonest
Implementation: Google-Maps + Flash?
Date: Feb. 2010

A short film using Google-Maps Satellite view to show a car chase in New York City.














Wanderword: German words adoption around the world

Wanderwort.jpg

Category: Geographical/Art
Where: Golden Section Graphics
Implementation: NA
Date: 2008

From GoldenSectionGraphics.com: For the Goethe Institut, we designed a version in DIN A0 size (33.1 in × 46.8 in) of our graphic »German spoken«. But, instead of using the 700 words we processed in the earlier version for Vanity Fair (issue 11/2007), we used about 2,000 of 2,500 terms in this new king-sized »emigrated words« poster. The Institute collected them in an initiative from all over the world.








Google Earth Tour of Belo Monte Dam

Category: Geographical/GIS/Animation
Where: Brent Millikan, InternationalRivers.org
Implementation: Google Earth
Date: 2010

From The Huffington Post, Patrick McCully writes: Deep in the Amazon rainforest, the Brazilian government wants to build a massive, nasty dam called Belo Monte. The hydropower plant has long been at the center of a lopsided battle between Brazil's powerful hydro-industrial complex -- with full backing from President Lula and his government -- and the country's indigenous people and environmental and social activists. [...]









GPX Animation

GPXAnimationTheNotch.png

Category: Geographical/GIS/Animation

Where
Provided by Jon Caris, GIS Specialist, Smith College

Implementation: GPX
Date: 2010

Download movie













Visualizing BP's Oil Spill: SVG Animation

BPOilSpillMap.png

Category: Geographical/Animation
Where: Ruth Lang, uismedia, www.mappetizer.de

Implementation
Mappetizer, SVG Animation

Date: 3. August 2010

From mappetizer.de:

Source
Background-Image: MODIS-Terra, USA7 Subset - Aqua 1km True Color image for 2010/129 (05/09/10)
Shape-Files
NOAA Satellite and Information Service
OpenStreetMap
under CC-by-sa License.
Wikipedia.
All texts under the GNU Free Documentation License.
GeoNames under CC-License.


















New KML Extensions in Earth 5.2

Category: Georgraphical/GIS/Animation
Where: GoogleGeoDevelopers.com
Implementation: GoogleEarth API + Track
Date: July 2010

From GoogleGeoDevelopers.com: We wanted a better way to represent movement on and above the globe. Time animation works well, but from a KML standpoint it required very bulky files. In order to “move” a <Point>, you created a new <Placemark> for each time segment. Your <Point> didn’t actually move, it merely was replicated at a different place. This made animating your path rather cumbersome. Instead, we wanted a smoother experience, and one that allowed you to truly animate a <Geometry>. So, we created <Track>. To get a real sense of the power of <Track>, check out this video.

Also of interest is the Tips and Tricks for Google Earth session at Google I/O



Weeplaces maps foursquare locations

Category: Geographical location
Where: WeePlaces
Implementation: NA
Date: 2010

from weeplaces.com: WeePlaces helps users organize and share their geolocation content. Users can create personal “geo-profiles” where users have the flexibility to share their checkins content how they want.















Flight Patterns

Category: Animation/Geographical-GIS
Where: Aaron Koblin
Implementation:
Date:

From the New York Times: The animations, and a series of equally hypnotic still images, were created by Aaron Koblin, a young “data driven” graphic artist and game designer, originally as part of a broader “Celestial Mechanics” project at the University of California, Los Angeles.

Aaron Koblin is Technology Lead of Google’s Creative Lab where he helped to launch Chrome Experiments, a website showcasing JavaScript work by designers from around the world.










Cab-Spotting in San Francisco

Cabspotting.png

Category: Geographic
Where: cabspotting.org and Stamen Design
Implementation: NA
Date: Launched 04/06/06

From cabspotting.org: Cabspotting traces San Francisco's taxi cabs as they travel throughout the Bay Area. The patterns traced by each cab create a living and always-changing map of city life. This map hints at economic, social, and cultural trends that are otherwise invisible. The Exploratorium has invited artists and researchers to use this information to reveal these "Invisible Dynamics."










Bus Traffic in San Francisco

EricFischerBusTraffic.png

Category: Geographic
Where: Eric Fischer, San Francisco
Implementation: NA
Date: 2010

The animation (visible on Flickr) shows a whole month of bus traffic in San Francisco. The data points are shown by themselves, without any superposition of a map of the city, but the pattern of traffic quickly highlights the geography of the city.

See the animation on FlowingData.com.

















Polymaps

Polymaps.png

Category: Algorithms, Geographic
Where: SimpleGeo and Stamen
Implementation: SVG + Javascript, open-source
Date: 2010

from Polymaps.org: Polymaps provides speedy display of multi-zoom datasets over maps, and supports a variety of visual presentations for tiled vector data, in addition to the usual cartography from OpenStreetMap, CloudMade, Bing, and other providers of image-based web maps.







Visualizing air and water

AirAndWaterOnEarth.jpg

Category: Geographical/Scientific
Where: Adam Nieman
Implemenation: 3D
Date: 2003

From the New York Times: In 2003 Adam Nieman created the image above, illustrating the volume of the world’s oceans and atmosphere (if the air were all at sea-level density) by rendering them as spheres sitting next to the Earth instead of spread out over its surface.









USGSWaterOnEarth.jpg

And from the USGS Web site, this interesting picture showing just the water.























Map of Paris

MapOfParis.png

Category: Geographic
Where: MIT
Implementation: 2D/Geographic
Date: 2010

From Xiaoji Chen's page: What is your mental map of a city? I bet it’s not measured in miles. This project is part of my work in the SENSEable City’s workshop this semester. In these distorted maps of Paris, the distance between a spot and the city center is not proportional to their geographical distance, but the cost taken to get there.

Standard map vs. driving time map of Paris: the city center expands from congestion, and the edge is denser.








Google Maps API

GoogleMapApi.png

Category: Geographic
Where: Google
Implementation: 2D
Date: Current

The answer for creating geographical maps with augmented data: Google Map API and Google Map Mashup.

Google allows one to include its maps in a Web site, and to superimpose on the map information that is user specific.

It can be programmed in Javascript. The application pulls the map from Google, pulls the data from the database, and puts dots (and possibly images) on the map, at the right place, including a popup tool-tip showing extra information.

Some examples:

  • Here’s a good example for a campus
  • There are plenty of other sites using Google Maps: a list of examples is available here
  • One can also embed videos in the tooltips, as examplified here



Visualizing the medals at the Olympics

NYTBejingMedals.png

Category: Newsprint, Geographic
Where: NYT
Implementation: 2D
Date:


This is a dynamic display of the number of medals obtained at various olympics. This is nicely done, and uses some form of circle packing.












CityMurmur.org

CityMurmure.org.png

Category: Geographic
Where: Politecnico di Milano
Implementation: geographic
Date: NA

CityMurmur is a Web application that periodically scans a pool of news sources, blogs, and online newspapers searching for references to local streets, points of interest and areas of the city. using this information the application is then able to plot topographical and semantic maps of the city according to the topic discussed by the news source( culture, society,...), the source's topology (blogs, online newspapers), and its scale (local media, regional media).



CCByNc.png You can remix, tweak, and build upon this page non-commercially. Your work must acknowledge Dominique Thiebaut as its author and be non-commercial.