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ESIP Lab Past Projects
The ESIP Lab funds a cohort of projects each year. Here are previously funded projects.
Photo by NASA
Small grants make big impact.
Microfunding opens the door to bigger projects. And it’s necessary in today’s research cycle. New ideas and technology need a little money and a lot of space with collaborative support to do the incremental work of pushing the Earth sciences forward.
$100k
Total dollars granted through the ESIP Lab each year for pilot projects and FUNding Friday
50+
Total projects funded and guided through the ESIP Lab small-grant innovation process.
>$2M
Additional funding secured by ESIP Lab pilot projects through NSF, NASA, and NOAA.
$200k
Cloud provider credits used by ESIP Lab projects each year.
Wildfire and Water Resources
Machine-Learning Tutorials
2022
Machine Learning for Flood Risk Assessment
Tom Narock | Goucher University
2022
Integrated Gradient Boosting Decision Trees and Deep Learning For Large-Scale SWE Estimation
Ryan Johnson | University of Alabama
2021
- Deep Learning based Submesoscale Ocean Eddy Detection on the Amazon Web Service Cloud | Jianwu Wang, University of Maryland, Baltimore County
- Comparison of Machine Learning Techniques for Predicting Complex Flows at the Breach of the Great Salt Lake | Som Dutta, Utah State University
- Developing a Cloud-based Open-Source Platform for an Automatic High-throughput Monitoring System to Safeguard Stream Water Quality | Tao Wen, Syracuse University
- Developing an Environmental Enforcement Data Portal | Kelsey Breseman, EDGI
- Piloting the OSDU platform for inter-state geological survey data management for synthetic 3D mapping initiatives | Gary Motz, Indiana Geological Survey
- Cloud-based Open Science Machine Learning Tutorials for Earth Science | Douglas Rao, NCICS
- A Geospatial-Natural Language Processing Analysis of the Snow Albedo Literature | Eric Sproles, Montana State University
- Auto-reconstruction of Inundation map using Deep Learning: Benchmarking with UDAR data | Trung Bao Le, North Dakota State University | ESIP Blog Post
- Modeling data and information needs for avian conservation using Neo4j | Brian Wee, Massive Connections
2020
- Developing Tutorials for Satellite Imagery Analysis using AWS Open Data and Cloud-Native Workflows | Amanda Tan, University of Washington
- Developing an Open-Source Workflow and Toolset for Quantifying Lacustrine Sedimentation using Publicly Available Data | Jake Gearon, University of Texas | ESIP Blog Post
- Sensors and Microclimate in Snowy Alpine Environment | Martha Apple, Montana Technological University
- Open source data harmonization: beyond data entry | Kathe Todd-Brown, University of Florida | ESIP Blog Post
- Cloud based analytics for TerraFusion data | John Ready, HDF Group
- 2020 Science-On-Schema.Org Validator | Dave Vieglais, University of Kansas | ESIP News Story
2019
- Use of UAVs to assess satellite measurements of snow albedo in mountainous regions | Eric Sproles, Montana State University | ESIP Blog Post
- FAIRTool.org toward better Earth science data stewardship | Abdullah Alowairdhi, University of Idaho
- Improve conda-forge CI infrastructure and packages auto-updating dependencies | Rich Signell, USGS
- Deep optical wave gauging | Daniel Buscombe, Northern Arizona University | ESIP Blog Post
- Subaqueous Landslide Morphometrics Database and Website for Global Outreach and Data Collection | Zane Jobe, Colorado School of Mines
- Scalable Serverless Workflows for Processing Cubesat Imagery to Identify Flowering Hotspots in Sub Alpine Meadows | Amanda Tan, University of Washington | ESIP Blog Post
- A cloud-based community tool for ambient seismic noise analysis and monitoring with Julia | Dylan Mikesell, Boise State
- Community Open Data and Experimental Mesonet (CODE-M) | Agbeli Ameko, NCAR
2018
- Enabling the encoding and visualization of provenance metadata for better discovery and understanding of climate resilience strategies for agriculture-related decision-making | Brian Wee, Massive Connections
- ESIPhub: Developing and promoting an ESIP community resource for sharing and running scientific workflows via JupyterHub | Keith Maull, UCAR
- SensorDat: Real-time sensor testbed for improved provenance and data quality | Mike Daniels, UCAR
- Geoweaver: a web-based prototype system for managing compound geospatial workflows of large-scale distributed deep networks | Ziheng Sun | ESIP Blog Post | Project Q&A
- Operational data provenance and cybersecurity for anticipatory disaster communication built on mesh networks | Christina Bandaragoda, University of Washington
- A deep-learning driven improved ensemble approach for hurricane forecasting | Yunsoo Choi, University of Houston
2017
- ESIPhub: Developing and promoting an ESIP community resource for sharing and running scientific workflows via JupyterHub | Sean Gordon
- Equipping OPeNDAP with data citation functionality | Niklas Griessbaum
- Enhancing sUAS Data with Semantic Technologies | Andrea Thomer
- Improve Earth Data Discovery through Deep Query Understanding | Yongyao Jiang
2016
- An Automatic Approach to Building Earth Science Knowledge Graph to Improve Data Discovery | Lewis McGibbney, NASA Jet Propulsion Laboratory | github | ESIP Blog Post
- Prototyping a Cloud-based High-Performance Spatial Web Portal for Parallel Analytics of Big Climate Data | Zhenlong Li, University of South Carolina | github
- Cloud-based computing for predicting streamflow in snowmelt-dominated watersheds | Anne Nolin, Oregon State University | ESIP Blog Post
