Terrain Analysis and Cryosphere Observation Lab

University of Washington Civil & Environmental Engineering

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UW TACO Lab

About Us

We develop and apply new methods to understand Earth system change, with real-world implications for water resources, sea level rise, and natural hazards.

We specialize in remote sensing measurement techniques (optical, lidar, radar) using a range of platforms (satellite, aircraft, UAV), and leverage automated data processing pipelines, modern data science approaches (i.e., deep learning), and HPC/cloud computing to answer questions that cannot be addressed using traditional approaches.

We use these approaches to understand glaciers, seasonal snow, and natural hazards, and how these systems and processes are impacted by ongoing climate change.

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Our Team

David Shean

Assistant Professor

Shashank Bhushan

Postdoctoral scholar

Eric Gagliano

PhD student

Friedrich Knuth

PhD student

Ben Purinton

Research scientist

Chris Hayner

PhD student

Karthik Venkataramani

Postdoctoral scholar

Quinn Brencher

PhD student

Romain Hugonnet

Postdoctoral scholar

Alan Viola

Website Manager

Alumni

Yara Mohajerani

Postdoctoral scholar

Michelle Hu

PhD student

Grégoire Guillet

Postdoctoral scholar

Seth Vanderwilt

MS student

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Projects

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

This project aims to fill gaps in NASA STV missions by improving instrument fusion, enabling data fusion and scientific analysis. We are working to develop novel information systems and on-board algorithms, using tools like multi-sensor deep learning fusion techniques and state-of-the-art radiative transfer model simulations (DART) to improve the resolution, accuracy, and quality of stereo images.

David Shean

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.

David Shean

Capturing the evolution of mountain snow in the Western U.S. using Synthetic Aperture Radar

This work focuses on capturing the spatial and temporal variability of snowmelt timing in mountain environments using Synthetic Aperture Radar (SAR). SAR is a powerful tool for assessing the evolution of mountain snow, with even greater potential when paired with optical data.

Eric Gagliano

Digital Glacier Time Machine

The Digital Glacier Time Machine (DGTM) project aims to quantify the decadal evolution of glacier mass change for all glaciers in the western U.S. during the past ~70 years. To accomplish this, we create new data sets through innovative image processing and quantitative analysis techniques.

Friedrich Knuth

NASA Commercial Smallsat Data Analysis Program (CSDAP)

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

Shashank Bhushan, David Shean

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.

Shashank Bhushan, David Shean

Selected Publications

For complete list and most recent publications, please visit Google Scholar

Hannah Besso, David Shean, Jessica D. Lundquist (2024). Mountain snow depth retrievals from customized processing of ICESat-2 satellite laser altimetry. In Remote Sensing of Environment.

Cite DOI

Michelle Hu, David Shean, Shashank Bhushan (2023). Six Consecutive Seasons of High-Resolution Mountain Snow Depth Maps From Satellite Stereo Imagery. In Geophysical Research Letters.

Cite DOI

Courses

Advanced Surveying & Geomatics

Covers modern surveying techniques that can be used for a range of engineering and scientific applications, with focus on precision mapping and 3D model generation using survey-grade GNSS receivers, drone-based Structure from Motion (SfM), and laser scanning (lidar).

Geospatial Data Analysis in Python

Explores geospatial data processing, analysis, interpretation, and visualization techniques using Python and open-source tools/libraries. Covers fundamental concepts, real-world data engineering problems, and data science applications using a variety of geospatial and remote sensing datasets.

Join us!

General Information

We are always looking for passionate, talented people to join our research group. While we will post specific job openings, please reach out regardless, as there are usually other opportunities at all levels (Undergrad, MS, PhD, Postdoc, Research Scientist, Technician). Read more more about our group and how to join…

Feb 5, 2024

Funded PhD student Research Assistant position

Opening for a funded PhD student Research Assistant position involving the development of scalable data processing and data fusion pipelines to create precise, high-resolution surface elevation change time series from archives of stereo satellite imagery (Maxar, Planet, BlackSky), satellite laser altimetry data (ICESat-2, GEDI), and airborne LiDAR data. Science questions focus on understanding how different components of the Earth’s cryosphere are evolving under ongoing climate change, including (but not limited to) seasonal snow, glaciers and ice sheets, and high-mountain natural hazards.

Feb 15, 2024