Gaussian Process Regression for ICESat-2 Point-Cloud Interpolation

Assigned Session: #AGM28: Generic Meeting Session

Abstract ID: 28.7300 | Accepted as Poster | Poster | 2025-02-27 13:00 - 14:30 | Ágnes‐Heller‐Haus/Small Lecture Room

Thorsten Seehaus (0)
Seehaus, Thorsten (1), Gardner, Alex (2)
Thorsten Seehaus (1)
Seehaus, Thorsten (1), Gardner, Alex (2)

1
(1) Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz, Erlangen, Germany
(2) NASA Jet Propulsion Laboratory, Pasadena, USA

(1) Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz, Erlangen, Germany
(2) NASA Jet Propulsion Laboratory, Pasadena, USA

Categories: Monitoring, Remote Sensing
Keywords: Surface elevation change, ICESat-2

Categories: Monitoring, Remote Sensing
Keywords: Surface elevation change, ICESat-2

The content was (partly) adapted by AI
Content (partly) adapted by AI

This study investigates the application of Gaussian Process Regression (GPR) for interpolating ICESat-2 ATL11 land ice height observations. ICESat-2 provides high-quality but spatially sparse measurements of ice surface elevation. GPR, with its ability to model complex spatial dependencies, offers a promising approach for interpolating these sparse observations and generating high-resolution maps of ice surface elevation. Two study sites, the Larsen-B embayment on the Antarctic Peninsula and a region in Southern Svalbard with numerous surging glaciers, were selected to test the performance of GPR for glacier volume change analysis. Various predictor sets and GPR kernels were evaluated and compared to contemporaneous surface elevation change measurements from TanDEM-X over a period of several years. Additionally, yearly surface elevation change maps were derived from ICESat-2 point measurements to investigate the temporal evolution of glacier volume changes. Preliminary results demonstrate the potential of GPR to accurately interpolate ICESat-2 ATL11 data, enabling more comprehensive and spatiotemporally continuous monitoring of ice sheet and glacier balances.


NAME:
Small Lecture Room
BUILDING:
Ágnes‐Heller‐Haus
FLOOR:
0
TYPE:
Lecture Hall
CAPACITY:
200
ACCESS:
Only Participants
ADDITIONAL:
TBA
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