Modeling Time Series of Land Ice Changes

Directed by Abani Patra

Project Description

Project will involve improving on a robust p-spline based model for time series of noisy remote sensing data [1] for ice sheet elevation observations. We will look closely at the automated strategy for outlier/anomaly detection which can greatly affect the elevation estimates that are used for net ice loss calculations.

Desired Background

Linear Algebra, Calculus, optionally Probability and Statistics and Python/Matlab.

  1. [1] P. Shekhar, B. Csathó, T. Schenk, C. Roberts and A. K. Patra, “ALPS: A Unified Framework for Modeling Time Series of Land Ice Changes,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 8, pp. 6466-6481, Aug. 2021, doi: 10.1109/TGRS.2020.3027190.J. Frikel and E. T. Quinto. Artifacts in incomplete data tomography with applications to photoacoustic tomography and sonar. SIAM J. Appl. Math., 75(2):703–725, 2015.