DOI: 10.5281/zenodo.10572207
title: Time-series displacement from high-resolution satellite Synthetic Aperture Radar (SAR) data using Sub-Pixel Offset Tracking (SPOT)

description: Time-series displacements at Merapi volcano, Indonesia, from high-resolution SAR and sub-pixel offset tracking (SPOT).

When using this dataset, please cite the authors:

Bemelmans, Mark^1,2,+; Biggs, Juliet^1,2; Wookey, James^1; Poland, Michael^3. 1: School of Earth Sciences, University of Bristol, Bristol, United Kingdom.2: Centre for the Observation and Modelling of Volcanoes, Earthquakes, and Tectonics (COMET), United Kingdom.3: Cascades Volcano Observatory (CVO), U.S. Geological Survey (USGS), Vancouver, Washington, The United States.+: corresponding author, mark.bemelmans@bristol.ac.uk

*Work is currently in preparation and will be updated when publication information is known.*

Background Information:

Synthetic Aperture Radar (SAR) data are collected through the Centre for Earth Observation Satellites (CEOS). The COSMO-Skymed (CSK) data are owned by the Italian Space Agency (ISO) and the TerraSAR-X (TSX) data are owned by the Deutsche Lüft- und Raumfarht Centrum (DLR).

Additionally, the Digital Elevation Model (DEM) used to correct for parallax shift is from Thomas and Darmawan, 2021. (High-resolution Digital Elevation Model of Merapi summit in 2015 generated by UAVs and TLS and TanDEM-X.

The data are processed using GAMMA-rs (Werner et al., 2000) using Sub-Pixel Offset Tracking (SPOT). SPOT uses image cross-correlation of small image patches to extract displacements (offsets) to sub-pixel precision. Details of the data processing can be found in [Bemelmans et al., in prep]

This data set currently includes data from CSK (heading 168 deg., incidence angel 35.6 deg., image resolution 0.34 in slant range, 0.70 in azimuth) with the following dates:

20200910202009192020092620200927202010052020101220201013202011132020111420201122202012242020123120210101202101092021011620210117202101252021020120210202202102172021021820210302202103052021030620210314202103212021032220210330202104062021041920210422202104232021050120210508202105092021052120210609202107112021072020210727202107282021081220210813202108292021091020210913202109142021092220210926202109302021101520211016202110242021103120211101        

We also have data from TSX (heading 191 deg., incidence angle 37.6 deg., image resolution 0.45 m in slant range, 0.17 m in azimuth). We have acquisitions from the following dates:        202011162020112720201208202012192021011020210201202102232021031720210408202104302021052220210602202106132021100120211023

For each acquisition we process pixel offsets to the 3 adjacent acquisitions. We then select the pixels for which we have 1 connected network of acquisition pairs that cover all the dates in the time series. We use (unweighted) least-squares inversion to extract the time series.

This dataset contains the following two files:

- CSK_SPOT_dsc_win13_ts_inv.csv (containing 282,270 points)- TSX_ST134_win13_ts_inv.csv (containing 48,291 points)

CSK_SPOT_dsc_win13_ts_inv.csv contains the time series pixel offsets from the CSK data in the slant range and azimuth directions (in meters).

TSX_ST134_win13_ts_inv.csv contains the time series pixel offsets from the TSX data in the slant range and azimuth directions (in meters).

The Data has the following format:

Row id | Longitude [deg. E] | Latitude [deg. N] | range disp. Date 1 [m] | azimuth disp. Date 1 [m] | range disp.Date 2 [m] | azimuth disp. Date 2 [m] | ...0     110.4641          -7.5363          0               0                0.003            0.0501     110.4639          -7.5363          0               0                0.004            0.0772     110.4638          -7.5364          0                   0                0.047            0.0813     110.4637          -7.5364          0               0                0.054            -0.0274     110.4634          -7.5365          0               0                0.041            -0.0025     110.4633          -7.5365          0               0                0.037            0.022

Note: in this dataset, row id refers to the row index of the original dataset which was filtered for data we could not make a complete time -series for and is not of any use for further interpretation.