Crisis Mapping in the Philippines: Efforts and Resources

Typhoon Haiyan/Yolanda in the Philippines has resulted in catastrophic loss of life and deprivation and our hearts go out the people and towns affected. Response to this crisis (as in the case of Hurricane Katrina, the Haitian Earthquake and Hurricane Sandy) includes a range of efforts that leverage user-generated data and the volunteer mapping efforts of individuals and organizations. We thought it useful to highlight some of these unfolding efforts here as resource for our readers and ourselves. At present this is just a listing of some of the things we've seen in our feeds, please add additional ones to the comments.

MANY of these Maps are actively seeking volunteers so please join in. 

A Variety of Crisis Maps for the Philippines:

• Open Street Map  
• Google  
• Rappler 
• SBTF, GISCorps and ESRI
• MicroMappers Human Analysis of Tweets 

News Articles about Current Crisis Mapping Responses:

• National Geographic 
• Wired 
• The Atlantic

Previous academic work on crowd-sourced crisis mapping responses:

• Goodchild, Michael F., and J. Alan Glennon. "Crowdsourcing geographic information for disaster response: a research frontier." International Journal of Digital Earth 3.3 (2010): 231-241.
• Liu, Sophia B., and Leysia Palen. "The new cartographers: Crisis map mashups and the emergence of neogeographic practice." Cartography and Geographic Information Science 37.1 (2010): 69-90.
• Roche, Stephane, Eliane Propeck-Zimmermann, and Boris Mericskay. "GeoWeb and crisis management: Issues and perspectives of volunteered geographic information." GeoJournal 78.1 (2013): 21-40.
• Zook, Matthew, Mark Graham, Taylor Shelton, and Sean Gorman. "Volunteered geographic information and crowdsourcing disaster relief: a case study of the Haitian earthquake."World Medical and Health Policy 2.2 (2010): 7-33.

Announcing "Iron Sheep": Map and Hack Day, February 26th @ AAG

Announcing "Iron Sheep"

Pack up your laptop, grab your data and head to New York for the first annual "lightning mapping of user generated information" event. Dubbed Iron Sheep (at least until someone objects) the event seeks to mimic the format of the “Iron Chef” television series. This workshop challenges participants (grouped into teams with members from diverse backgrounds and skill sets) to produce meaningful analysis and fun, evocative mash-ups from the same sets of user-generated, geo-coded data within a four hour time frame. The goal is to provide a semi-structured environment where participants can socialize and work in a fun yet socially meaningful project. Participants will be drawn from academic, industry and artistic communities from around the world.

Teams will be assigned a targeted question (e.g., What is the most “out of shape” location in the U.S.? or How can we visualize the Occupy Wall Street movement? or Where is the most likely place for the zombie apocalypse to start? or Where is the origin and destination of Super PAC money?) and use crowdsourced data to create a new geo-visualization. Teams can also choose their own questions. The exact questions and datasets depends on the participants who join (see below).

When: Sunday February 26th 2012, 5 pm to 9 pm; Happy Hour(s) to follow
(During the Association of American Geographers Meeting in NYC)

A panel discussion of the event will take place at the AAG conference at 8 am on Tuesday (Feb 28th) in Conference Room E, Lower Level, Sheraton Hotel

Where: New York City, exact location to be announced (depending upon number of attendees)

Organizers

• the Floating Sheep collective
• the Oxford Internet Institute
• GeoIQ
• the New Mappings Collaboratory at the University of Kentucky
• Vizzuality
  

Confirmed Attendees

• Jeremy Crampton, University of Kentucky
• Mike Goodchild*, University of California, Santa Barbara
• Sean Gorman, GeoIQ
• Mark Graham, FloatingSheep and Oxford Internet Institute
• Muki Haklay, University College London
• Lize Mogel, Editor, An Atlas of Radical Cartography
• Stéphane Roche, Laval University
• Taylor Shelton, FloatingSheep and Clark University
• Monica Stephens, FloatingSheep and University of Arizona
• Javier de la Torre, Vizzuality
• Andrew Turner, GeoIQ
• Sarah Williams, Spatial Information Design Lab, Columbia University
• Matt Wilson, University of Kentucky
• Matthew Zook, FloatingSheep and University of Kentucky

* Will attend the panel on Tuesday but not the "lighting mapping" event on Sunday

How to attend
This event is open (register here) although the price of entry is that each participants contributes a dataset that is not commonly available (ideally crowdsourced) or one that has been enhanced in a meaningful and useful way. Data that is relatively comprehensive for the U.S. or world would work best, although something focused specifically on New York City would be appropriate as well. The goal is to have enough commonality between datasets that it is possible to do mashups. There will also likely be a "secret sauce" dataset (again borrowing from the Iron Chef idea) that all mappers would be challenged to include.

The organizers will likely be contributing the following data sets:

• The retail cost of marijuana at the city, county and state level (based on PriceofWeed.com reports);
• Busted meth labs;
• Some slice of geo-coded tweets;

Serious or offbeat datasets are both extremely welcome as we are hoping for the serendipity that comes from the new mashing of data – such as the Beer Belly of America. For example, we'd love to end up with a combination of data sets that includes things like:

• Super-PAC contributions;
• Flickr photos tagged with the word "cat";
• Precinct level voting records;
• VW bug ownerships;
• Sales of Twinkies and/or iPhones;
• Foursquare check ins at bars versus grocery stores;
• Spending on political ads.
• Grindr.com and/or BarebackRT.com check-ins;
• OK Cupid dating information

Mapping Male Enhancement: Distorting Size the Old Fashioned Way

As we feature various maps made by other folks from time to time, we thought the recent maps showing the average size of men's (and women's), ahem... private parts, were pretty interesting. Below is a static image of the map of average penis sizes, with a link to the original, dynamic map provided. These maps have been circulated around the interwebs for the last week or so, largely without a critical eye.

Average Penis Sizes Worldwide

But as has been pointed out since then, the data used in these maps is fairly dubious. The source of the data, Andromedical, is a company that provides solutions to all one's, ahem... enhancement needs. But the link to a company that profits from making men and women feel inadequate is not the only thing that calls this data into question. In the data presented by Andromedical there is no uniform source or method of standardization. In short, there's basically no way whatsoever of verifying the data these maps display.

So why in the world did we feel it necessary to mention this? Well, in addition to participating in the latest Internet meme, we thought it important to highlight the ongoing concerns of accuracy when it comes to neogeography and/or volunteered geographic information (we're looking at you, Goodchild). When anyone can produce and disseminate maps like these online, how are we to tell those that are legitimate from those that are not?

Obviously, not every map mashup or amateur cartographer should be written off automatically, nor even compared to a dubious medical company with intentions to profit off of people's lack of sexual self esteem. But the fact that this map was passed around the web so quickly -- if nothing else than for it's "oh, wow" factor -- points to the ease with which misinformation about any topic can be spread, so long as it's through the means of a colorful choropleth map mashup (not, as Time Magazine called it, a cartogram).

So in the end, these maps are simply another example of how maps distort size. But rather than area distortion based on map projections, it is simply the old standby of using questionable data.

Autocomplete Part II: Crowdsourcing the Geography of Autocomplete

We encourage all of you to help us continue to flesh out our Autocomplete map of the world by contributing your own search results using Autocomplete. If you follow the link you will find an open spreadsheet to record the results. But before you do, please follow the steps below to make sure that your results are not being affected by your own search patterns.

It's important that your searches not be tailored to you as an individual, but be reflective of your general location, the time at which you searched and Google's suggested search results. In order to control for these factors (and a whole host of others), please follow these directions if you want to contribute:

• Be sure to be signed out of your Google Account while you search on Google. If you are signed in to your Google Account, your search experience may be customized based on your own personal past searches (which would no doubt be fascinating to your friends and family) but is NOT what we're after. Learn how to turn off these customizations.
• Remove particular searches from your Web History at www.google.com/history, or by clicking the "Remove" links that appear beside personalized predictions.
• Remove Web History from your Google Account.
• Type the country name without a space at the end. If you're curious, compare how "Australia" and "Australia " (notice the space) give different results.
• Copy the FIRST search term that comes up in to the online spreadsheet.
• There are 250 or so countries names in total. If you can't do all of those, we've prioritized the top 150 for you to complete.
• We're primarily interested in people outside of the US and the UK but we'll take anyone's help, no matter where they are. Also we're limiting ourselves to the English name of countries for now.

Good luck!

Crowdsourcing the price of Weed

In the last few years, we've seen how crowdsourcing has been employed for a range of important tasks including disaster relief in Haiti, monitoring the recent Kenyan elections, and now mapping the price of weed. This is a great example of how crowdsourcing can produce information that is simply unavailable otherwise. After all, there are no official price data on marijuana markets given its illegality.

Map from the PriceOfWeed.com Website
(Green = < $300 per oz; Yellow = $3oo-400 per oz; Red = > $400 per oz

Quite an interesting distribution with cost rising as one moves west from the Pacific coast (with Oregon being the cheapest). Florida shows up as a low spot as well. Both patterns are consistent with what is known about the geographies of production and distribution. Of course given the overall much lower reported prices for weed in Canada (is it subsidized?), one has to wonder if this site will only serve to further increase the US trade deficit.

We have previously done some analysis on the geographies of marijuana, if anyone wants to compare.

New Paper: Volunteered Geographic Information and the Haitian Earthquake

Our paper on the use of volunteered geographic information in response to the Haitian earthquake, co-authored with Sean Gorman of FortiusOne, has just been published in World Medical and Health Policy.

Be warned. This is an educational moment. You might learn something. After all it can't be all fun and correlations. The abstract and links to the paper are below.

Volunteered Geographic Information and Crowdsourcing Disaster Relief: A Case Study of the Haitian Earthquake
by Matthew Zook, Mark Graham, Taylor Shelton and Sean Gorman
World Medical & Health Policy Vol. 2: Iss. 2, Article 2.
Available at: http://www.psocommons.org/wmhp/vol2/iss2/art2

This paper outlines the ways in which information technologies (ITs) were used in the Haiti relief effort, especially with respect to web-based mapping services. Although there were numerous ways in which this took place, this paper focuses on four in particular: CrisisCamp Haiti, OpenStreetMap, Ushahidi, and GeoCommons. This analysis demonstrates that ITs were a key means through which individuals could make a tangible difference in the work of relief and aid agencies without actually being physically present in Haiti. While not without problems, this effort nevertheless represents a remarkable example of the power and crowdsourced online mapping and the potential for new avenues of interaction between physically distant places that vary tremendously.

Or, if you don't have institutional access, you can find our paper here.

Also two Floatingsheep-style maps before and after the earthquake are below (and are in the paper). By the way, Haiti is on the western portion of the island of Hispaniola, the Dominican Republic is on the eastern side.

Cyberscape Before the Earthquake

Cyberscape After the Earthquake