October Update: Ignite @AGU Submission Deadline, AWS Cloud Credits, Visualizing a Change in Seasonal Snow Cover, and More…

1. Ignite @AGU
2. ESIP Lab Receives Second Round of AWS Cloud Research Credits
3. Challenge Highlight: Computer Vision for Building Damage Assessment
4. Visualizing a Change in Seasonal Snow Cover Persistence

Ignite at the 2019 AGU Fall Meeting

The popular science storytelling event Ignite@AGU is returning to the 2019 American Geophysical Union Fall Meeting in San Francisco, CA. Sponsored by NASA’s Applied Sciences Program and held in partnership with the Earth Science Information Partners, Ignite@AGU enables scientists to showcase their professional and personal interests through fast-moving, creative presentations.

This year's event will be hosted by Planet at their San Francisco headquarters.

When: Wednesday, December 11th from 6-8:30 pm
Format: 5-minute talk with 20 auto-advancing slides
Submission Deadline: October 18th
Announcement of Selected Talks: November 1st

Be bold – it’s the best stage all week!

Learn more at: https://www.esipfed.org/igniteAGU2019

ESIP Lab Recieves Second Round of AWS Cloud Research Credits 

We are excited to announce the ESIP Lab has received a second round of AWS cloud research credits to support the Lab's Small Grants program. As showcased recently (talk and blogpost), AWS credits have lowered the barrier to entry for Lab projects to use cloud services. In preparation for the next Lab RFP, think about how your project could utilize cloud credits to put Earth science data to work! 

Challenge Highlight: Computer Vision for Building Damage Assessment 

When a disaster strikes, quick and accurate situational information is critical to an effective response. Before responders can act in the affected area, they need to know the location, cause and severity of the damage. But disasters can strike anywhere, disrupting local communication and transportation infrastructure, making the process of assessing specific local damage difficult, dangerous, and slow.

Solving a Common Problem

Recognizing an opportunity to solve a key analytical bottleneck, the Defense Innovation Unit, together with other Humanitarian Assistance and Disaster Recovery (HADR) organizations, is releasing a new labeled, high-resolution satellite dataset and a challenge to the computer vision community.

Learn more here.

Visualizing a Change in Seasonal Snow Cover Persistence

Lab Fellow Ben Roberts-Pierel highlights one of his favorite data exploration tools

I have covered several different tools and packages in the last few lab updates and I wanted to draw a few of those together in an example figure as we progress rapidly towards the end of the year. As anybody who follows this section will know, I am fascinated by snow and my work focuses on ways that snow cover is changing in the Pacific Northwest. What I have included here is a simple visualization of some initial results showing NRCS SNOTEL stations that have likely experienced a change in seasonal snow cover persistence since the mid-1980’s. Although the figure itself is fairly rudimentary, the background processing is likely more interesting. A few months ago I covered the Climata package which is what is running in the background to pull these data from an API. The data are then pickled and then processed using a combination of mostly Pandas, Geopandas and Scipy. One other small package used here is contextily which is a very simple package for adding a basic basemap under a matplotlib/geopandas plot. This could also be accomplished using Cartopy but this provides a very easy alternative. This process has also been automated to enable testing of different proxies for snow persistence and then visualization of station locations.