Adonis Diaries

Crowd-sourcing in Syria? Satellite crisis-mapping Imagery Analysis?

Posted on: September 20, 2011

Crowd-sourcing in Syria? Satellite crisis-mapping Imagery Analysis?

What if we crowdsourced satellite imagery analysis of key cities in Syria to identify evidence of mass human rights violations?

Looks like using micro-tasking, with backend triangulation to crowdsource the analysis of high resolution satellite imagery for human rights purposes, is definitely breaking new ground.

This is precisely the question that Patrick Meier and his colleagues at Amnesty International USA’s Science for Human Rights Program are being asked to follow upon.  

Patrick Meier of Crisis Mapping at Ushahid has been publishing posts on mapping Syria military concentration. The post is titled “Help Crowdsource Satellite Imagery Analysis for Syria: Building a Library of Evidence” and says:

“I coordinated this pilot project for Somalia.  AI-USA has done similar work in the past with their Eyes on Darfur project. But using micro-tasking, with backend triangulation to crowdsource the analysis of high resolution satellite imagery for human rights purposes, is definitely breaking new ground.

A staggering amount of new satellite imagery is produced every day. Millions of square kilometers’ worth of images are mapped according to one knowledgeable colleague. This is a big data problem that needs mass human intervention, until the software can catch up.

I recently spoke with Professor Ryan Engstrom, the Director of the Spatial Analysis Lab at George Washington University, and he confirmed that automated algorithms for satellite imagery analysis still have a long, long way to go. So the answer for now has to be human-driven analysis.

Professional satellite imagery experts, who have plenty of time to volunteer their skills, are far and few between.

The Satellite Sentinel Project (SSP), is composed of a very small team and a few interns. Their focus is limited to the Sudan and they are understandably very busy. My colleagues at AI-USA analyze satellite imagery for several conflicts, but this takes them far longer than they’d like and their small team is still constrained given the number of conflicts and vast amounts of imagery that could be analyzed. This explains why they’re interested in crowdsourcing.

Indeed, crowdsourcing imagery analysis has proven to be a workable solution in several other projects & sectors. The “crowd” can indeed scan and tag vast volumes of satellite imagery data when that imagery is “sliced and diced” for micro-tasking.

This is what we did for the Somalia pilot project thanks to the Tomnod platform and the imagery provided by Digital Globe. The yellow triangles below denote the “sliced images” that individual volunteers from the Standby Task Force (SBTF) analyzed and tagged one at a time.

We plan do the same with high resolution satellite imagery of three key cities in Syria selected by the AI-USA team. The specific features we will look for and tag include: ”Burnt and/or darkened building features,” “Roofs absent,” “Blocks on access roads,” “Military equipment in residential areas,” “Equipment/persons on top of buildings indicating potential sniper positions,” “Shelters composed of different materials than surrounding structures,” etc.

SBTF volunteers will be provided with examples of what these features look like from a bird’s eye view and from ground level. Like the Somalia project, only when a feature—say a missing roof—is tagged identically  by at least 3 volunteers will that location be sent to the AI-USA team for review.

In addition, if volunteers are unsure about a particular feature they’re looking at, they’ll take a screenshot of said feature and share it on a dedicated Google Doc for the AI-USA team and other satellite imagery experts from the SBTF team to review. This feedback mechanism is key to ensure accurate tagging and inter-coder reliability.

The screenshots shared will be used to build a larger library of features. For example, what a missing roof looks like as well as military equipment in residential areas, road blocks, etc. Volunteers will also be in touch with the AI-USA team via a dedicated Skype chat.

There will no doubt be a learning curve, but the sooner we climb that learning curve the better. Democratizing satellite imagery analysis is no easy task, and one or two individuals have opined that what we’re trying to do can’t be done. That may be true, but we won’t know unless we try.

This is how innovation happens. We can hypothesize and talk all we want, but concrete results are what ultimately matters. And results are what can help us climb that learning curve. My hope, of course, is that democratizing satellite imagery analysis enables AI-USA to strengthen their advocacy campaigns and makes it harder for perpetrators to commit mass human rights violations.

SBTF volunteers will be carrying out the pilot project this month in collaboration with AI-USA, Tomnod and Digital Globe. How and when the results are shared publicly will be up to the AI-USA team as this will depend on what exactly is found.

In the meantime, a big thanks to Digital Globe, Tomnod and SBTF volunteers for supporting the AI-USA team on this initiative.

If you’re interested in reading more about satellite imagery analysis, the following blog posts may also be of interest:

• Geo-Spatial Technologies for Human Rights
• Tracking Genocide by Remote Sensing
• Human Rights 2.0: Eyes on Darfur
• GIS Technology for Genocide Prevention
• Geo-Spatial Analysis for Global Security
• US Calls for UN Aerial Surveillance to Detect Preparations for Attacks
• Will Using ‘Live’ Satellite Imagery to Prevent War in the Sudan Actually Work?
• Satellite Imagery Analysis of Kenya’s Election Violence: Crisis Mapping by Fire
• Crisis Mapping Uganda: Combining Narratives and GIS to Study Genocide
• Crowdsourcing Satellite Imagery Analysis for Somalia: Results of Trial Run
• Genghis Khan, Borneo & Galaxies: Crowdsourcing Satellite Imagery Analysis
• OpenStreetMap’s New Micro-Tasking Platform for Satellite Imagery Tracing

In particular, we are looking to identify the following evidence using high-resolution satellite imagery:

  • Large military equipment
  • Large crowds
  • Checkpoints
The idea is to provide volunteers the Standby Volunteer Task Force (SBTF) Satellite Team with as much of road map as possible so they know exactly what they’re looking for in the  satellite imagery they’ll be tagging using the Tomnod system:

Here are some of the links that Chris already sent us for the above imagery:
Comment:  This a great endeavor. I suggest to Patrick Meier to start crowd sourcing on Israeli check-points, road-blocks, concentration of military centers in Jewish colonies in the Palestinian occupied territories of the West Bank and Gaza. Let us be fair and equitable in matters related to human rights, regardless of what States like to define their political systems and disseminate false images.  Palestine is an independent State, recognized by the UN.
Note 1: Patrick Meier, born and raised in Africa, is director of Crisis Mapping at Ushahidi and co-founder of the International Network of Crisis Mappers. Previously co-directed Harvard’s Program on Crisis Mapping and Early Warning.
Note 2: In one of the many articles I published related to Syria uprising in the last six months I wrote: https://adonis49.wordpress.com/2011/03/26/whats-going-on-in-syria-any-insider-pieces-of-intelligence-part-two/
Note 3: The same technique is being used for the search of the missing Malaysian airliner this March 2014.  Apparently, about 30,000 registered clients view each of the shots and report whether they have seen any party of the wreckage.  If many report on a shot, the image is sent to a specialist to decide before forwarding the shot to the proper authorities. This search has not been successful so far.
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adonis49

adonis49

adonis49

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