This conference has ended. See the latest ➔

USGS Crowdsourcing for Emergency Response – Transcription

Hello, thank you for coming to my talk. We are going to talk about USGS crowd sourcing for emergency response, a follow-up last year. FEMA asked us to collect data in response to the flooding in Louisiana last September.

The national map corpus is similar to OSM in a limited scope. So volunteers can use our online application, which updates structures data, which point features and building features in the U.S., Puerto Rico, and the Virgin Islands. They are public domain, free, available products we provide.

Initially, we started this project seven years ago. We started working with OpenStreetMap, we contracted the OpenStreetMap folks. And ultimately, we were not able to work directly with OpenStreetMap because of license conflicts. Since we have a public domain license, we cannot provide OpenStreetMap data.

However, at that time, we did customize a version of pot latch two. We downloaded the OSM software stack, and a version of hot latch two for our project. This was amazing, that would not have happened if it was not available to us.

And so, we have since moved just about a year ago to an internally-developed editor. But for this project, when FEMA contacted us, we just retired our customized version of hot latch two, which was a dinosaur by that point. I’m sure you all are like, what, Hot Latch two, what are you doing? So the reason we were able to help FEMA with this project is we could retire it, and prop it back up and customize it again for this project.

So that’s a background.

And so again, in August 2016, FEMA contacted us. They were responsible for the flooding in Louisiana, they did not have parcel data for a number of parishes. And so what they needed this data for was to speed disaster relief to citizens.

And so what they did is figured out where homes were that may have been damaged.

So we determined if we were able to do this. And they contacted us because they were aware of our volunteer program, the national map corps. And we determined that we could move forward and try to help them with this process.

So again, they requested that we solicit our volunteers to select building data over six parishes that lack data. And the data collection was for planning, future mitigation, and speed relief to citizens, locate where people need financial assistance from FEMA.

So I already talked about this, but again, what we did is we set up our recently retired version of Hot Latch two, that was cloned from OpenStreetMap from 2010 to 2011, this was the framework that we were using, Ruby on Rails three, using leaflet, and the Hot Latch Two editor.

So NASA said we could do it, and in a couple days, a small team of us created user documentation. We invited our – an experienced group of our volunteers we knew we would need to train to participate in this process of placing points on buildings by type.

And daily, we provided that data to FEMA.

So this is just a few of what the editor looked like. Hot Latch two, customized, we were selecting all buildings by types: Residential, commercial, or other, across these six parishes.

I mentioned this, we created a quick user guide, and we only invited a limited subset.

That was with good results. We know our community well, we looked into the quality of the data, we published that, and they provided really high-quality data. So that was something that we needed to turn around quickly and provide to FEMA as soon as possible.

These were the features we collected. This was the timeline, Greg, do you want to go over this? All right.

Greg Matthews: So this took a week to discuss internally, and FEMA and the staff decided we could pull this off in their spare time. And so after that, we initiated the implementation, this shelved piece of software. We spent the next weeks collecting data in this community. We didn’t know what to expect, we had been doing this for years, bought not with this kind of data collection.

So we didn’t know exactly what to expect.

And so, this was an exercise for us to find out how to make it work, across government agencies with FEMA and objects like this within the government.

And we had a very rapid iteration, we pulled in a year’s worth of data to determine if it was successful.

And this is the histogram, showing the data that was collected over time, and very quickly it began to taper off.

And areas that were hard to contribute were – (speaker far from mic) – over a period of months. It was tapering off towards the end of the project, and it gave us time to – (speaker far from mic) – and we had a hard deadline as well.

It was interesting, for some reason, we don’t know the exact profile, but – (speaker far from mic).

So, for whatever reason, we were finding most of the data was collected earlier in the week.

And this is just a slide, a window into how we were determining the data. We got it off the ground really fast, this was an after-thought. We decided to implement an online spreadsheet, so we can help re-task the other – (speaker far from mic).

And this is the visual display of that tracking. So the orange areas are areas that are not as complete. These parishes are not complete.

Okay, so some of the results from the cooperation, the USGS helped in this distributed effort, and it is successful in what it generates.

Staff estimates that it takes 30 seconds to a minute to collect.

And so the result was between 65 and 131 million data points.

We successfully brought in data – (speaker far from mic). It supported FEMA to provide disaster assistance, and improving USGS collaboration and to respond to this emergency.

So the map that you are looking at, it shows these counter points.

So the lessons learned, the USGS was rolled out in crowd sourcing and capabilities. And so these results were consistent with their other results, on a non-emergency basis.

And the response to the national volunteers is very isolated. We had the ability to deploy this rapidly, but we were not able to respond – (speaker far from mic).

And so it was a lot to do in a short amount of time. I think the USGS collected this in the future, the stage – (speaker far from mic).

That is something that has proven to be successful.

(Speaker far from mic).

I think was a good lesson for us, and it shows a great way for government to work with other government agencies in the public at the same time – (speaker far from mic).

And then, with that, that is it. Questions? Comments?

(Applause).

So, who would be hired to build – to pre-build for the next event?

It wouldn’t take a long time to roll up the application that is part of the source.

And it is really just an issue of capacity for us. We have 89 percent of the submissions in place now. We have a lot of great ideas and a lot of work to do.

We had to plan a year ahead, too. It wouldn’t take a lot of work.

Any other questions or comments?

How does one become a member, or contributor?

Oh, I – if you want to do this in OpenStreetMap, I encourage you.

So if you go to nationalmap.gov, you will see a national map on the home page. So sign up, email, with the user name and start contributing. The scope is limited, but the data we collected is public domain, and it updates our products. It is an important resource, at this time we only collect buildings with simple attribution and point features. But check it out.

I brought some bookmarks and forgot them at home. Sorry.

Quick question, is anybody – (speaker far from mic).

Just a quick reminder, thank you for your presentation, if you did not see my comments this morning, we are doing our group photo now. We are all going to congregate on the terrace over there, where the Birds Of a Feather are. We are doing a group photo and satellite photo, at precisely 12:28. I will try to yell at everyone and tell you what direction to look.

So please start heading over there, in an orderly and safe manner.

And we will look directly at the satellites –

But not the sun.

Don’t look at the sun.

Do we line up by height?

For the satellite photo, it will not matter. For the group photo, we are doing tall people on the back, and then people on their knees or something.

But Justin will give us the instruction, Justin our photographer. Thank you!