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Ashton Wiens, Ph.D.

Ashton Wiens is a Mathematical Statistician with the USGS Geology, Energy & Minerals (GEM) Science Center in Reston, VA.

Ashton is currently involved in developing mathematical and statistical methods for energy and mineral resource assessments, including critical minerals, geologic energy storage, and carbon mineralization. Current multi-resource assessment work across mission areas involves the interaction between wind energy and wildlife. Previous work in population ecology focused on methods for evaluating species status and trends, including providing analytic support for the North American Bat Monitoring Program.

Professional Experience

  • USGS, Energy and Minerals Mission Area, Geology, Energy & Minerals Science Center (GEMSC), 2022-Present

  • USGS, Ecosystems Mission Area, Upper Midwest Environmental Sciences Center (UMESC) Ecological Sciences branch, 2020-2022

  • NCAR, Institute for Mathematics Applied to the Geosciences 2018-2020

  • University of Colorado, Boulder; Graduate research assistant 2017-2020

Education and Certifications

  • University of Colorado; M.S. and Ph.D. in applied mathematics, 2015-2020

  • University of Kansas; B.S. in mathematics, 2011-2015

Science and Products

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Filter Total Items: 13

Topographic change detection at Chalk Cliffs, Colorado, USA, using Airborne LiDAR and UAS-based Structure-from-Motion photogrammetry Topographic change detection at Chalk Cliffs, Colorado, USA, using Airborne LiDAR and UAS-based Structure-from-Motion photogrammetry

The Chalk Cliffs debris-flow site is a small headwater catchment incised into highly fractured and hydrothermally altered quartz monzonite in a semi-arid climate. Over half of the extremely steep basin is exposed bedrock. Debris flows occur multiple times per year in response to rainstorm events, typically during the summer monsoon season. The frequency of debris flows, and the...
Authors
Katherine R Barnhart, Francis K. Rengers, Ghent Jessica N, Gregory E. Tucker, Jeffrey A. Coe, Jason W. Kean, Joel B. Smith, Dennis M. Staley, William Kleiber, Ashton M Wiens
By
Natural Hazards Mission Area, Landslide Hazards Program, Geologic Hazards Science Center, Geology, Minerals, Energy, and Geophysics Science Center

Non-USGS Publications**

Wiens, A, Nychka, D, Kleiber, W. Modeling spatial data using local likelihood estimation and a Matérn to spatial autoregressive translation. Environmetrics. 2020; 31:e2652. https://doi.org/10.1002/env.2652
Wiens, A., Kleiber, W., Nychka, D. et al. Nonrigid Registration Using Gaussian Processes and Local Likelihood Estimation. Math Geosci 53, 1319–1337 (2021). https://doi.org/10.1007/s11004-020-09917-7

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

Science and Products

No Result Found
Filter Total Items: 13

Topographic change detection at Chalk Cliffs, Colorado, USA, using Airborne LiDAR and UAS-based Structure-from-Motion photogrammetry Topographic change detection at Chalk Cliffs, Colorado, USA, using Airborne LiDAR and UAS-based Structure-from-Motion photogrammetry

The Chalk Cliffs debris-flow site is a small headwater catchment incised into highly fractured and hydrothermally altered quartz monzonite in a semi-arid climate. Over half of the extremely steep basin is exposed bedrock. Debris flows occur multiple times per year in response to rainstorm events, typically during the summer monsoon season. The frequency of debris flows, and the...
Authors
Katherine R Barnhart, Francis K. Rengers, Ghent Jessica N, Gregory E. Tucker, Jeffrey A. Coe, Jason W. Kean, Joel B. Smith, Dennis M. Staley, William Kleiber, Ashton M Wiens
By
Natural Hazards Mission Area, Landslide Hazards Program, Geologic Hazards Science Center, Geology, Minerals, Energy, and Geophysics Science Center

Non-USGS Publications**

Wiens, A, Nychka, D, Kleiber, W. Modeling spatial data using local likelihood estimation and a Matérn to spatial autoregressive translation. Environmetrics. 2020; 31:e2652. https://doi.org/10.1002/env.2652
Wiens, A., Kleiber, W., Nychka, D. et al. Nonrigid Registration Using Gaussian Processes and Local Likelihood Estimation. Math Geosci 53, 1319–1337 (2021). https://doi.org/10.1007/s11004-020-09917-7

**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.

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