Measuring the Impact of Humanitarian Mapping in Nepal
On April 25, I awoke in Seattle to learn that Nepal had been hit by a magnitude-7.8 quake, the largest seen in 81 years.
I thought of my friends in Nepal, in particular a family who’d once hosted my husband. I wanted to know if they were okay. I wanted to help. But like many others, I had little information.
I realized then that even when you can’t see an earthquake's damage, you can still feel its impact.
Mapping to Help First Responders
First responders often say the first and most vital need in a crisis is information. Maps of roads in particular help drive targeted relief efforts.
Just hours after the earthquake, volunteers from Tableau joined the Humanitarian OpenStreetMap Team (HOT) to help map Nepal. We worked alongside more than 4,000 volunteer cartographers to focus on items most critical to first-response efforts, roads and buildings.
Within 48 hours of the quake, volunteers had added more than 13,199 miles of new roads and 110,681 new buildings in remote, previously-unmapped regions of Nepal. Several Tableau employees also volunteered at a mapathon hosted by OpenStreetMap Seattle and Maptime Seattle.
This snapshot shows the OpenStreetMaps roads and features added or edited right after the quake. Yellow indicates the most recent additions at the time this snapshot was taken.
A Surprising Find: The Power of Many!
On May 13—18 days after the main quake and two days after a 7.3-magnitude aftershock—the Tableau team queried OpenStreetMap’s road segments to analyze the volunteers’ work.
Using Tableau, we discovered that 107,401 (approximately 70 percent) of the 152,192 road segments had been added and/or edited since the April 25 quake. Interestingly, the bulk of these edits had been accomplished by a high percentage of mappers making a relatively small number of edits.
Our analysis showed that a few volunteers had been particularly active, editing between 1,000 and 16,000 road segments apiece. However, the majority of edits were done by a group of volunteers with a median edit of five road segments. Altogether, these editors contributed up to 65 percent of the changes in the roads data, whereas the top 20 editors only contributed 35 percent.
The Long Tail and Its Impact
Visualizing the results in Tableau, the distribution clearly resembled the often-referenced marketing concept of the "long tail." The impact of those who only made a few edits (and resided in the long part of the tail) were more influential than individuals who made many edits (and resided in the head of the tail).
As Nepal’s situation evolves, so does the need for the most up-to-date maps. As more post-earthquake and landslide imagery becomes available to the OpenStreetMap community, the need to keep volunteers engaged in the project increases.
My family was immensely grateful to hear, several days later, that our friends survived the quake. However, their losses are still great, and it’s clear that Nepal will need assistance for months to come.
All too often, the problem with trying to make a difference is not knowing whether we are making a difference at all. As a data engineer who works with OpenStreetMap data and contributes to the project, the most rewarding part of making my edits is knowing exactly what type of benefits these edits create.
Even if I make only a handful of changes each day, I know the value of my contribution lies in my continued participation, not in the volume of edits. For a recovering landscape like Nepal, it is this type of continuous volunteering that is particularly impactful.
After all, in OSM, it takes millions of small changes to build the map that we all need.