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David Shean

Faculty Photo

Assistant Professor
Civil & Environmental Engineering

Adjunct Assistant Professor
Aeronautics & Astronautics

Pronouns: He/him/his


David's research involves the development and application of new methods to study dynamic Earth system components with real-world implications for water resources, sea level rise, and natural hazards. His current research uses satellite, airborne, UAV, and terrestrial remote sensing observations to understand the Earth’s cryosphere, with focus on mountain glaciers, seasonal snow, and ice sheets. Much of this work requires the development and application of automated data processing pipelines, modern data science approaches, and cloud computing to answer questions that cannot be addressed using traditional approaches. David is also interested in satellite mission operations, commercial smallsat constellations, and satellite instrument development, specifically high-resolution cameras and laser altimeters.

David’s early research involved documenting past glaciation and evidence for climate change on Mars. He went on to work for Yellowstone National Park, where he studied dynamic hydrothermal features, and then Boston University, where he performed geophysical surveys of glaciers in the Transantarctic Mountains. From 2007-2011, David worked for Malin Space Science Systems as a member of the NASA Mars Reconnaissance Orbiter Context Camera (CTX) and Mars Color Imager (MARCI) science operations team. His PhD research at the University of Washington documented the evolution of ice-shelf basal melt and ice-stream dynamics in West Antarctica to better understand future ice-sheet stability.


  • Ph.D., Earth and Space Sciences, University of Washington, 2016
  • Sc.M., Geology, Brown University, 2006
  • Sc.B, Brown University, Geology-Physics/Mathematics, 2004

Previous appointments

  • Postdoctoral Research Associate, Applied Physics Laboratory, University of Washington, 2016-2017
  • Visiting Scholar, Boston University, 2006-2007

Current projects

Sliderule Earth: Enabling rapid, scalable, open science for the NASA ICESat-2 mission and beyond

SlideRule is an open source server-side framework for on-demand processing of science data in the cloud. The SlideRule project offers a new paradigm for NASA archival data management – rapid delivery of customizable on-demand data products, rather than hosting large volumes of standard derivative products that will inevitably be insufficient for some science applications. The existing ICESat-2 SlideRule plugin offers customizable algorithms to process the archive of low-level data products from the NASA Ice Cloud and land Elevation Satellite-2 (ICESat-2) laser altimetry mission stored in AWS S3. The user defines a geographic area of interest and key processing parameters via an interactive web interface or the API, and SlideRule returns high-level surface elevation point cloud products in seconds to minutes, enabling rapid algorithm development, visualization and scientific interpretation.

Advanced Information Systems to Fill NASA Surface Topography and Vegetation (STV) Mission Gaps: Next-Generation Stereo+Lidar Fusion and Sensor Technology

This NASA technology/science crossover project focuses on the following components for the NASA Surface Topography and Vegetation (STV) Mission under the Decadal Survey Incubation (DSI) program:

  • Develop novel information systems and on-board algorithms that can deliver the precise pointing knowledge needed for next-generation lidar and TDI linescan image sensors. These subsystems will solve the notorious "jitter” problem responsible for large residual geolocation uncertainty in commercial stereo images.
  • Develop information systems that use cutting-edge, multi-sensor deep learning fusion techniques to improve the horizontal resolution, vertical accuracy/precision, and quality of stereo+lidar datasets for priority STV targets (vegetation, ice/snow).
  • Develop stereo photogrammetry information systems with robust joint optimization routines, rigorous uncertainty metrics, and stereo+lidar fusion alignment to support next generation stereo imaging rigs and constellations
  • Leverage state-of-the-art radiative transfer model simulations (DART) and existing/new on-orbit and airborne datasets to support development activities and evaluate key stereo acquisition parameters, which will complement STV OSSE efforts to define STV instrument requirements.

NASA High-Mountain Asia Team (HiMAT)

Assessing and projecting changes in High-mountain Asia's water, ice, snow, hazards, and related phenomena to improve our understanding of regional changes, water resources, and induced impacts and vulnerabilities in human and biogeophysical systems.

NASA Commercial Smallsat Data Analysis Program (CSDAP)

Our group has been involved in multiple projects under the NASA Commercial Smallsat Data Analysis Program (