2024 NASA Champions

Welcome to the 2024 NASA Champions Cohort! This is a Cohort for research teams using NASA Earthdata to learn open science practices and spend time experimenting and planning what their analytical workflows with NASA Earthdata look like in the Cloud. This is part of NASA Openscapes: https://nasa-openscapes.github.io. Learn more about Openscapes and the Champions Program: https://openscapes.org.

Cohort Agendas

We will meet as a Cohort via Zoom five times over two months for 1.5 hours each:

Agendas are accessible to Cohort participants in our Cohort Google Drive Folder; they are also an archive of our live google-docing. Please see https://openscapes.github.io/series to view blank versions of the agendas.

NASA Openscapes Mentors have iterated lessons each year. In 2024 Data Strategies for Cloud included “When to Cloud” and Coding Strategies for Cloud included parallelizing code. All previous lessons are linked from https://openscapes.github.io/series.

Date Cohort Call Topics Open science resources Teaching Leads
04/03 1. Openscapes mindset, Better science in less time mindset, better science in less time Aronne Merilli (University of Michigan & 2023 Champion), (Michele Thornton (ORNL)
04/17 2. NASA Earthdata Cloud Clinic, hands-on lesson from NASA Mentors NASA Earthdata Cloud Clinic Catalina Taglialatela (PO.DAAC) & Luis Lopez (NSIDC)
05/01 3. Team culture and data strategies for future us in the Cloud team culture, data strategies for cloud Matt Fisher (NSIDC), Alexis Hunzinger (GES DISC)
05/15 4. Open communities and coding strategies for future us in the Cloud open communities, coding strategies for cloud, Earthdata Cloud Cookbook Bri Lind (LP DAAC), Mahsa Jami (LP DAAC), Cassie Nickles (PO.DAAC)
05/29 5. Pathways share earthaccess: Smart Access, Budgeting and storing data in the cloud Luis López (NSIDC), Andy Teucher (NASA Openscapes)

Cohort Call Digests are posted as Issues in this repo.

Coworking times (optional)

Coworking sessions are where we work at the same time together. Sometimes, this means quiet work with check-ins to break up focused work and get feedback, and sometimes this involves asking questions and screensharing to learn and problem solve.

Coworking takes place in the weeks between Cohort Calls on alternating Thursdays following our second Cohort Call: April 25, May 9, 23. 10:00 - 11:30 am PT.

Participating teams

The Liu-Zhang (University of Louisiana at Lafayette & University of Southern Mississippi) team primarily uses NASA Earth Search to access datasets like EMIT and ECOSTRESS, which we then employ to create algorithms for ecosystem analysis. We have a particular interest in using hyperspectral data, such as upcoming PACE data to study vegetation and algae in water bodies. Our work involves developing deep learning models for habitat classification and analyzing water quality. Transitioning to hyperspectral imaging and deep learning significantly increases computational demands, making it challenging to execute code locally compared to leveraging cloud computing resources. Additionally, this transition enhances the accessibility of my algorithm to the public. Currently funded by EMIT and serving as early adopters of PACE, I am eager to contribute to the NASA Cookbook by offering new algorithms that apply to NASA’s latest satellite data, such as EMIT and PACE.

The Ocean Science Analytics team incorporates NASA data in our studies of coastal and offshore marine regions, specifically as it pertains to marine mammals. Combining in-situ data from hydrophones to ascertain the vocal occurrence of marine mammals with remotely sensed ocean color data, we use chlorophyll, net primary productivity, sea surface temperature, etc. to characterize the associated habitat and document changes over time. As a PACE early adopter, we are incorporating PACE data in our studies through large scale observations of photosynthesizing organisms, which will allow us to incorporate direct measurements of the presence and distributions of plankton species. This in connection with feeding behavior will provide a better understanding of the spatial use of these habitats.

The PACE Hackweek team supports the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission launched in February 2024 and is collecting unprecedented data from our global oceans, atmosphere, and land. PACE data will be hosted in the cloud; therefore, we are interested in learning more about cloud-based workflows to access and analyze PACE data and contribute our efforts and outcomes to our community of end-users.

The NOAA CoastWatch team is motivated by rising ocean temperatures, higher sea levels, melting ice, and increasing ocean acidity are changing the way marine life and ecosystems function in our world’s oceans. This affects everything from how we manage fisheries and protect communities that depend on fishing to how we protect important habitats and species. The ocean is expected to continue changing and changes are expected to become more extreme. A lot is at stake. Improving how we use of earth data in our workflows is essential. We have much we can learn about migrating to the cloud by connecting with other earth science teams at NASA and with the NASA Openscapes mentors.

The Wimberly Lab (University of Oklahoma) team explores the impacts of changing climate and landscapes on ecosystems and human health, with an emphasis on developing spatial decision support tools to support public health decisions, land use planning, and natural resource management. We address these topics through landscape, regional, and global analyses using satellite remote sensing and other sources of environmental monitoring data. Specific research areas include the effects of environmental change on vector-borne disease outbreaks, the influences of human land use and wildfires on forest landscape dynamics, the impacts of agricultural expansion and intensification on native ecosystems, and the development of computer software for disease outbreak forecasting and landscape change modeling. We conduct our research in locations throughout the world including North America, West Africa, Ethiopia, and India.

The NOAA Integrated Ecosystem Assessment (IEA) team’s approach provides cross-disciplinary science to support ecosystem-based management in the Gulf of Mexico. For example, we conduct research on climate-fisheries interactions, changes in species ranges and distributions, and environmental impacts on fisheries such as those driven by harmful algal blooms. We use data from earth system modeling and remotely sensed data, including sea surface temperature, sea surface height, ocean currents, wind, ocean color, salinity, dissolved oxygen, and primary production indices. We are particularly interested in integrating modern open-science techniques to automate our core deliverables, called Ecosystem Status Reports, and other data products related to NOAA surveys. We’re beginning to test some of these approaches in ongoing projects. For example, the ongoing IEA-Wind project aims to develop data baselines to track the impacts of forthcoming offshore wind energy infrastructure development. The project has been conceptualized and executed thus far with an open-data approach. We believe that a deeper understanding of the concepts and approaches offered by this Cohort would allow for more holistic application across GoM-IEA efforts.

The NASA SERVIR Central America team are representatives of Costa Rica’s National System of Conservation Areas (SINAC, in Spanish), the Forest Research and Services Institute of the National University of Costa Rica, and the Central America Aerospace Network (RAC, in Spanish). The NASA / USAID SERVIR program is helping to connect the Costa Rican researchers with OpenScapes. The team is responsible for generating Costa Rica’s official national forest cover maps, in the context of its national forest monitoring system. Therefore, involving the team will have a significant national impact in terms of their reporting to international commitments (e.g. UN CBD, UNCCD, UNFCCC, and SDG 15.2). The team is currently using Google Earth Engine (GEE) to access and process data from Sentinel-1 (SAR) and Sentinel-2 (optical). They combine these datasets and perform a supervised classification to generate land cover maps.While the team’s workflow is already in the cloud (via Google Earth Engine), they are interested in exploring additional computational capabilities that may be available via AWS for processing big data, including the inclusion of other datasets like that of the Landsat archive.

The POSTECH (University South Korea) team is actively engaged in climate modeling research, utilizing both Python and NCL scripts to analyze climate data. I am eager to expand my knowledge and skills by collaborating with experts in the field, and I am keen to explore new methodologies and insights. Joining your team presents an exciting opportunity for me to enhance my expertise and broaden my exposure to cutting-edge techniques in climate science.

NASA Openscapes Team

Julie Lowndes (@jules32), Erin Robinson (@erinmr), Andy Teucher (@ateucher), NASA Openscapes Mentors

More about Openscapes and the Champions program: