2025-09-05, 13:30–15:00 (Europe/Amsterdam), Expert Room 2
This tutorial session is designed for Cryosphere applications, focusing on the processing and analysis of satellite remote sensing data over ice sheets and sea ice regions. The session will introduce key satellite missions, including Sentinel-1 SAR, CryoSat-2 radar altimetry, and ICESat-2 laser altimetry, with hands-on exercises in Python.
Participants will gain experience in:
Synthetic Aperture Radar (SAR) processing using Sentinel-1 data for ice type classification.
Radar altimetry (CryoSat-2) data analysis, including elevation and freeboard estimation.
Laser altimetry (ICESat-2) data processing, focusing on surface elevation change detection, and sea ice thickness estimation.
The tutorial will cover Python-based tools and libraries, including rasterio, xarray, h5py, and geopandas, to facilitate the analysis of large-scale remote sensing datasets. By the end of the session, participants will be able to apply these techniques to monitor ice sheet dynamics, track sea ice changes, and assess the impact of climate variability on the cryosphere.
The cryosphere plays a crucial role in Earth's climate system and sea level changes. Satellite remote sensing provides essential observations for understanding ice sheet dynamics, sea ice variability, and snowpack conditions. This Python-based tutorial introduces practical techniques for analyzing Sentinel-1, CryoSat-2, and ICESat-2 data in cryospheric studies.
Topics Covered
Sentinel-1 SAR Processing
Accessing and preprocessing Sentinel-1 GRD and SLC data.
Generating backscatter composites for sea ice classification.
CryoSat-2 Radar Altimetry Analysis
Understanding radar waveforms over ice surfaces.
Deriving sea ice freeboard and thickness from CryoSat-2 Level-2 products.
Comparing altimetry measurements with in-situ validation data.
ICESat-2 Photon Counting Altimetry
Extracting surface elevation from ICESat-2 ATL07 and ATL10 datasets.
Estimating ice sheet elevation change and sea ice thickness.
Visualizing ICESat-2 track data over polar regions.
Tools & Libraries
Participants will work with:
rasterio, geopandas, shapely – for geospatial data handling.
h5py, xarray, numpy – for working with large satellite datasets.
matplotlib, cartopy, seaborn – for visualization of polar data.
https://drive.google.com/drive/folders/182tUPnXv8rhzX3trEOi1TveKv_yJj8aM
Assistant Professor at Utrecht University, working over the remote sensing of Cryosphere