DOI: 10.5066/p1ciesuj
title: Time series of InSAR-derived surface deformation from 2015 – 2021 at Johns Hopkins Inlet and Gilman Glacier, Glacier Bay National Park and Preserve, Alaska

description: Satellite interferometric synthetic aperture radar (InSAR) time series data were processed to investigate a large bedrock landslide above Gilman Glacier in Glacier Bay National Park and Preserve, Alaska. The time series of surface deformation for the landslide and surrounding region are presented herein.

The Alaska Satellite Facility (ASF) HyP3 service (Hybrid Pluggable Processing Pipeline; Hogenson and others, 2020) was used to process Sentinel-1 synthetic aperture radar (SAR) satellite imagery (available from the European Space Agency at https://dataspace.copernicus.eu/) from May 2015 to October 2021. We process descending track 145 data with an adaptive phase filter strength of 0.6 at 10x2 looks. This reduces phase noise in interferograms for InSAR pairs with low coherence and multilooks these data in the range and azimuth by 10 and 2 times respectively, which results in an 80 m spatial resolution. We generate an interferogram network with a redundancy of three and create summer-summer year-long interferograms to span winter months where data had low coherence values due to snow-cover (see Gilman_interferogram_dates.txt for all SAR image pairs used). Coherence is a metric reported from 0 to 1 that describes the similarity between two SAR acquisitions, with values closer to 0 indicating that the acquisitions are dissimilar due to changes in surface conditions, making those data too noisy to use. The large amount of water bodies in the region prompted the application of a water mask during processing. ASF HyP3 uses GAMMA software to generate the interferograms and the 30-meter Copernicus digital elevation model (DEM) to orthorectify these data (Johnston and others, 2025; European Space Agency).

The MintPy (Miami InSAR time-series software in Python) software was used to process the HyP3-generated interferograms into a time series of surface deformation (Yunjun and others, 2019). ERA5 (ECMWF Reanalysis v5; European Centre for Medium-Range Weather Forecasts) atmospheric corrections were then applied using the PyAPS software (Python-based atmospheric phase screen; Jolivet and others, 2011; 2014). A time series of deformation was generated for the region (58.77°, 59°, -137.18°, -136.61°; S, N, W, E), which is the final product presented herein. We removed interferograms with an average spatial coherence of less than 0.4. The average spatial coherence of an interferogram is a metric that can be used to understand whether there are any usable data in that interferogram. After inverting for a time series of deformation, we mask out pixels that have a temporal coherence of 0.7 or less to maintain only the higher quality pixels. We also mask out regions with large values of nonzero triplet phase closure, a metric that is used to determine where there may be errors in these data (Yunjun and others, 2019). InSAR measurements are relative in space, so we chose a reference pixel in an assumed stable rocky outcrop located at (58.9009°, -137.0094°; Figure 1) to derive displacements relative to that point. Despite these precautions, there are likely unwrapping errors still present in this product.

Time series values, including the average velocity and the relative displacement at each SAR acquisition date, are reported in the satellite’s line-of-sight (average incidence angle = 35.3°, heading angle = 197.3°, as defined in Van Natijne and others, 2022). This means a displacement of -5 mm is indicating 5 mm of ground movement away from the satellite. The landslide is located on the SW-facing slope above Gilman Glacier, measuring 1690 m wide at its base (Hults and others, 2023). Our time series detected surface displacement on the landslide, indicating steady movement from 2015 to 2021. Outside of the area of interest, a region on the NW-facing slope immediately north of the landslide (labeled A in Figure 1) shows episodic movement away from the satellite, mostly concentrated in the summer of 2021. This is in a region of fractures mapped by Hults and others (2023). Additionally, there is a 750 m wide region of downslope movement in the SW corner of the map above the Johns Hopkins Glacier (labeled B in Figure 1; 58.796°, -137.132°). In the summer of 2018, we see -50 mm of movement, and the net ground movement from 2015 to 2021 is -150 mm. There are no mapped fractures, scarps, faults, and landslides by Hults and others (2023) in this area. For ease of data visualization, we recommend viewing the Gilman_timeseries_2015_2021.shp file using the “InSAR Explorer” Plugin available in QGIS (Haghshenas, 2025; QGIS, 2023).
 
The files provided in this data release are as follows:

“Figure1.png” is a map showing the linear velocity of the InSAR time series. The area of interest, which encompasses Gilman Glacier and the landslide, are outlined in orange. Satellite heading and line-of-sight (LOS) are shown in the bottom right corner.

“Gilman_interferogram_dates.txt” is a tab delimited text file that contains a list of all interferogram dates used in the time series analysis. The complex conjugate of the secondary acquisition is cross multiplied by the reference acquisition to generate an interferogram.

“Gilman_timeseries_2015_2021.zip” contains the shapefile “Gilman_timeseries_2015_2021.shp” which is a vector geospatial shapefile containing satellite line-of-sight (average incidence angle = 35.3°, heading angle = 197.3°) displacement values for each date in the timeseries in the region of interest. Heading is measured in degrees clockwise from north and the incidence angle is measured as the angle between the incident radar signal and the local surface normal (Van Natijne and others, 2022). It contains the following attributes: 
    CODE: A unique identifier for each point
    HEIGHT: digital elevation model (DEM) height for each point (m)
    VEL: Calculated satellite line-of-site (LOS) velocity (mm/yr)
    V_STDEV: Estimated uncertainty in satellite line-of-site (LOS) velocity (mm/yr)
    COHERENCE: Temporal coherence (values range from 0 (bad) to 1 (good))
    Dyyyymmdd: Displacement at date in time series in millimeters (D: displacement, four-digit year, two-digit month, two-digit day)
    XCOORD: Longitude, World Geodetic System 84 (WGS84)
    YCOORD: Latitude, World Geodetic System 84 (WGS84)
 
“Time_series_of_InSAR-derived_surface_deformation_from_2015_2021_at_Johns_Hopkins_Inlet_and_Gilman_Glacier_Glacier_Bay_National_Park_and_Preserve_Alaska.xml” is the metadata for the data release.
 
Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
 
References Cited:
European Space Agency, 2022, Copernicus DEM: European Space Agency,https://doi.org/10.5270/ESA-c5d3d65

Haghshenas Haghighi, M., 2025, InSAR Explorer (v.1.0.0): Zenodo. https://doi.org/10.5281/zenodo.15006874

Hogenson, K., Kristenson, H., Kennedy, J., Johnston, A., Rine, J., Logan, T., Zhu, J., Williams, F., Herrmann, J., Smale, J., and Meyer, F., 2020, Hybrid Pluggable Processing Pipeline (HyP3) —A cloud-native infrastructure for generic processing of SAR data: Zenodo, https://doi.org/10.5281/zenodo.4646138

Johnston, A., Kennedy, J.H. cirrusasf, Kristenson, H., Herrmann, J., Logan, T.,  Player, A.,  Hogenson, K., Smale, J., Rine, J., Williams, F., ASF APD/Tools team bot, Gens, R., Lundell, E., and ninneman, 2025, ASFHyP3/hyp3-gamma— HyP3 GAMMA v9.0.4 (v9.0.4): Zenodo, https://doi.org/10.5281/zenodo.15283891.

Jolivet, R., Grandin, R., Lasserre, C., Doin, M. P., and Peltzer, G., 2011, Systematic InSAR tropospheric phase delay corrections from global meteorological reanalysis data: Geophysical Research Letters, 38(17), L17311, doi:10.1029/2011GL048757

Jolivet, R., Agram, P.S., Lin, N.Y., Simons, M., Doin, M.P., Peltzer, G., and Li, Z., 2014, Improving InSAR geodesy using global atmospheric models: Journal of Geophysical Research —Solid Earth, 119(3), 2324-2341, doi:10.1002/2013JB010588

QGIS.org, 2023, QGIS Geographic Information System: QGIS Association, http://www.qgis.org

United States Geological Survey, 2021, United States Geological Survey 3D Elevation Program 1/3 arc-second Digital Elevation Model: Distributed by OpenTopography, https://doi.org/10.5069/G98K778D. Accessed: 2025-05-05

Van Natijne, A.L., Bogaard, T.A., Van Leijen, F.J., Hanssen, R.F., and Lindenbergh, R.C., 2022, World-wide InSAR sensitivity index for landslide deformation tracking: International Journal of Applied Earth Observation and Geoinformation, 111, 102829, https://doi.org/10.1016/j.jag.2022.102829

Yunjun, Z., Fattahi, H., and Amelung, F., 2019, Small baseline InSAR time series analysis —Unwrapping error correction and noise reduction: Computers & Geosciences, 133, 104331, https://doi.org/10.1016/j.cageo.2019.10433