That is the total number of tags created by 168 volunteers after processing 3,909 satellite images in just five days. A quarter of a million tags in 120 hours; that’s more than 2,000 tags per hour. Wow. As mentioned in this earlier blog post, volunteers specifically tagged three different types of informal shelters to provide UNHCR with an estimate of the IDP population in the Afgooye Corridor. So what happens now?
Our colleagues at Tomnod are going to use their CrowdRank algorithm to triangulate the data. About 85% of 3,000+ images were analyzed by at least 3 volunteers. So the CrowdRank algorithm will determine which tags had the most consensus across volunteers. This built-in quality control mechanism is a distinct advantage of using micro-tasking platforms like Tomnod. The tags with the most consensus will then be pushed to a dedicated UNHCR Ushahidi platform for further analysis. This project represents an applied research & development initiative. In short, we certainly don’t have all the answers. This next phase is where the assessment and analysis begins.
In the meantime, I’ve been in touch with the EC’s Joint Research Center about running their automated shelter detection algorithm on the same set of satellite imagery. The purpose is to compare those results with the crowdsourced tags in order to improve both methodologies. Clearly, none of this would be possible without the imagery and invaluable support from our colleagues at DigitalGlobe, so huge thanks to them.
And of course, there would be no project at all were it not for our incredible volunteers, the best “Mapsters” on the planet. Indeed, none of those 200,000+ tags would exist were it not for the combined effort between the Standby Volunteer Task Force (SBTF) and students from the American Society for Photogrammetry and Remote Sensing (ASPRS); Columbia University’s New Media Task Force (NMTF) who were joined by students from the New School; the Geography Departments at the University of Wisconsin-Madison, the University of Georgia, and George Mason University, and many other volunteers including humanitarian professionals from the United Nations and beyond.
As many already know, my colleague Shadrock Roberts played a pivotal role in this project. Shadrock is my fellow co-lead on the SBTF Satellite Team and he took the important initiative to draft the feature-key and rule-sets for this mission. He also answered numerous questions from many volunteers throughout past five days. Thank you, Shadrock!
It appears that word about this innovative project has gotten back to UNHCR’s Deputy High Commissioner, Professor Alexander Aleinikoff. Shadrock and I have just been invited to meet with him in Geneva on Monday, just before the 2011 International Conference of Crisis Mappers (ICCM 2011) kicks off. We’ll be sure to share with him how incredible this volunteer network is and we’ll definitely let all volunteers know how the meeting goes. Thanks again for being the best Mapsters around!
The Standby Volunteer Task Force (SBTF) recently launched a new team called the Satellite Imagery Team. This team has been activated twice within the past few months. The first was to carry out this trial run in Somalia and the second was in partnership with AI-USA for this human rights project in Syria. We’re now back in Somalia thanks to a new and promising partnership with UNHCR, DigitalGlobe, Tomnod, SBTF and Ushahidi.
The purpose of this joint project is to crowdsource the geolocation of shelters in Somalia’s Afgooye corridor. This resembles our first trial run initiative only this time we have developed formal and more specialized rule-set and feature-key in direct collaboration with our colleagues at UNHCR. As noted in this document, “Because access to the ground is difficult in Somalia, it is hard to know how many people, exactly, are affected and in what areas. By using satellite imagery to identify different types of housing/shelters, etc., we can make a better and more rapid population estimate of the number of people that live in these shelters. These estimates are important for logistics and planning purposes but are also important for understanding how the displaced population is moving and changing over time.” Hence the purpose of this project.
We’ll be tagging three different types of shelters: (1) Large permanent structures; (2) Temporary structures with a metal roof; and (3) Temporary shelters without a metal roof. Each of these shelter types is described in more details in the rule-set along with real satellite imagery examples—the feature key. The rule-set describes the shape, color, tone and clustering of the different shelter types. As per previous SBTF Satellite Team deployments, we will be using Tomnod’s excellent microtasking platform for satellite imagery analysis.
Over 100 members of the SBTF have joined the Satellite Team to support this project. One member of this team, Jamon, is an associate lecturer in the Geography Department at the University of Wisconsin-Madison. He teaches on a broad array of technologies and applications of Geographic Information Science, including GPS and satellite imagery analysis. He got in touch today to propose offering this project for class credit to his 36 undergraduate students who he will supervise during the exercise.
In addition, my colleague and fellow Satellite Team coordinator at the SBTF, has recruited many graduate students who are members of the American Society for Photogrammetry and Remote Sensing (ASPRS) to join the SBTF team on this project. The experience that these students bring to the team will be invaluable. Shadrock has also played a pivotal role in making this project happen: thanks to his extensive expertise in remote sensing and satellite imagery, he took the lead in developing the rule-set and feature-key in collaboration with UNHCR.
The project officially launches this Friday. The triangulated results will be pushed to a dedicated UNHCR Ushahidi map for review. This will allow UNCHR to add additional contextual data to the maps for further analysis. We also hope that our colleagues at the European Commission’s Joint Research Center (JRC) will run their automated shelter tagging algorithm on the satellite imagery for comparative analysis purposes. This will help us better understand the strengths and shortcomings of both approaches and more importantly provide us with insights on how to best improve each individually and in combination.
UK Guardian: The new Google Earth layers weave together satellite maps, photos, videos and eyewitness accounts to give viewers a close-up look at the refugee crises in Iraq, Chad, Columbia and Darfur in Sudan.
They allow users to find out about UNHCR operations, locate refugee camps and discover the impact of the humanitarian crises on neighboring countries such as Sudan, Syria and Ecuador.
Users can explore the lives of those in exile by clicking on exact locations in the refugee camps to see photos of the facilities, such as health clinics, schools, water taps and sanitation. There are pop-up videos of specific operations and events, such as a visit to a Chad refugee camp by the actor and UN goodwill ambassador Angelina Jolie.
The UN deputy high commissioner for refugees, L Craig Johnstone, said: “Google Earth is a very powerful way for UNHCR to show the vital work that it is doing in some of the world’s most remote and difficult displacement situations. By showing our work in its geographical context, we can really highlight the challenges we face on the ground and how we tackle them.”
A UNHCR spokesman said the programme could soon develop further. “With the new generation of cameras with GPS, we can foresee taking photos of a place and uploading it directly to Google Earth. For our planning, mapping and communications unit, that would be an amazing tool.
“Over time, we can envision increasing the number of elements shown that will certainly increase the ‘live’ experience of the platform.”
The next step for an iRevolution is to enable refugees to access this information on a regular basis. This need not require high-technology. The information could be broadcast by radio, for example.
Patrick Philippe Meier