Orcas & AI, conda-forge, OGC API Hackathon, MODIS and more.Highlights from your favorite Earth science virtual lab. 

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Highlights from your favorite Earth science virtual lab! 
April 10, 2019
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DIRECTOR’S NOTE:  Show off your tech at the ESIP Summer Meeting. Check out this great blog post Putting the Cloud to Work for Seismology. Join the IT&I Tech Dive this Thursday on Pachyderm: Automating DevOps for Data Science
Annie Bryant Burgess, Director, ESIP Lab

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Have a question about Earth science data? technology? Ask us!  We’ll periodically feature selected questions – and the answers from our partners in the know!

What’s that sound? Using Acoustic Data & Machine Learning to Find Orcas

Killer whales, or orca, inhabit the oceans of the world but are difficult to discern due to a lack of data. A Google Summer of Code Project submitted by the Alaska Ocean Observing System (AOOS) and Axiom Data Science aims to aid orca researchers by developing a custom Convolution Neural Network classifier that will automatically identify orcas in a passive acoustic dataset.

Check out their proposed GSoC project

Lab-Funded Project Highlight: Conda-Forge Sprints at AnacondaCon

 
Core members of Conda-Forge, a community-led collection of recipes, build infrastructure and distributions for the conda package manager, got together at AnacondaCon to discuss the future of packaging, and sprint on conda-forge’s infrastructure. The sprint was supported by the ESIP Lab, Anaconda, and NVIDIA. 

Learn more aboutconda-forge’s ESIP Lab project here.

Join In: OGC API Hackathon

The Open Geospatial Consortium (OGC) is organizing a Hackathon to develop OGC Application Programming Interface (API) specifications and invites you to participate. This hackathon will test draft OpenAPI-based standards for coverages, map tiles, processes using a common template based on the OGC API for features, aka WFS3 [1].

The event will be instrumental to the evolution of the OWS standards to a modern API based approach, setting the course for open geospatial standards for the next decade. The hackathon will be organized around: Coverages, Map Tiles, Processing.
 

Learn more about the OGC API Hackathon here.

New MODIS Daily Cloud Gap-Filled Snow Product

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

MODIS data are commonly used for snow cover studies because of the available daily temporal resolution and, therefore, the potential to capture a highly dynamic environment. However, clouds pose a major problem for MODIS. This has traditionally been dealt with by temporal or spatial adjacency gap-filling but has been done largely ad hoc by researchers in post-processing.

I recently attended the American Association of Geographers (AAG) Annual Meeting and in my session at Dr. Dorothy Hall of Goddard Space Flight Center, one of the original researchers on the MODIS snow cover products, presented validation results for the newest version of the MODIS daily snow cover products, Version 6.1, which will be available around June of this year. The dataset will have a built-in ‘uncertainty band’ that allows the user to select how far back in time they want to use data to gap-fill. These data will be a welcome resource and will negate some of the diverse post-processing approaches utilized by many different researchers. 

For more information on the project, interested researchers should see: https://modis-snow-ice.gsfc.nasa.gov/

ESIP is funded with support from NASA, NOAA, and the USGS. 
Keep up on all the action on Slack – here is your INVITATION!

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