LiCSAR: An Automatic InSAR Tool for Measuring and Monitoring Tectonic and Volcanic Activity

Remote Sensing - Tập 12 Số 15 - Trang 2430
Milan Lazecký1, Karsten Spaans2, Pablo J. González3,4, Yasser Maghsoudi1, Yu Morishita1,5, F. Albino6, John R. Elliott1, Nicholas Greenall7, Emma Hatton8, Andrew Hooper1, Daniel Juncu1, Alistair McDougall8, R. J. Walters9, C. Scott Watson1, Jonathan Weiss1,10, Tim Wright1
1COMET, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
2SatSense Ltd., 103 Clarendon Rd, Leeds LS2 9DF, UK
3COMET, Department of Earth, Ocean and Ecological Sciences, University of Liverpool, Liverpool L69 3BX, UK
4Volcanology Research Group, Department of Life and Earth Sciences, IPNA-CSIC, 38206 Tenerife, Spain
5Geography and Crustal Dynamics Research Center, Geospatial Information Authority of Japan, Tsukuba 305-0811, Japan
6COMET, School of Earth Sciences, University of Bristol, Senate House, Tyndall Ave, Bristol BS8 1TH, UK
7Independent Software Developer, Leeds LS2 9JT, UK
8Independent Researcher, Leeds LS2 9JT, UK
9COMET, Department of Earth Sciences, Durham University, Durham DH1 3LE, UK
10Institute of Geosciences, University of Potsdam, 14469 Potsdam, Germany

Tóm tắt

Space-borne Synthetic Aperture Radar (SAR) Interferometry (InSAR) is now a key geophysical tool for surface deformation studies. The European Commission’s Sentinel-1 Constellation began acquiring data systematically in late 2014. The data, which are free and open access, have global coverage at moderate resolution with a 6 or 12-day revisit, enabling researchers to investigate large-scale surface deformation systematically through time. However, full exploitation of the potential of Sentinel-1 requires specific processing approaches as well as the efficient use of modern computing and data storage facilities. Here we present Looking Into Continents from Space with Synthetic Aperture Radar (LiCSAR), an operational system built for large-scale interferometric processing of Sentinel-1 data. LiCSAR is designed to automatically produce geocoded wrapped and unwrapped interferograms and coherence estimates, for large regions, at 0.001° resolution (WGS-84 coordinate system). The products are continuously updated at a frequency depending on prioritised regions (monthly, weekly or live update strategy). The products are open and freely accessible and downloadable through an online portal. We describe the algorithms, processing, and storage solutions implemented in LiCSAR, and show several case studies that use LiCSAR products to measure tectonic and volcanic deformation. We aim to accelerate the uptake of InSAR data by researchers as well as non-expert users by mass producing interferograms and derived products.

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Tài liệu tham khảo

European Space Agency (2020, May 27). Copernicus: Sentinel-1. Available online: https://directory.eoportal.org/web/eoportal/satellite-missions/c-missions/copernicus-sentinel-1.

Elliott, 2016, Himalayan megathrust geometry and relation to topography revealed by the Gorkha earthquake, Nat. Geosci., 9, 174, 10.1038/ngeo2623

Massonnet, 1995, Deflation of Mount Etna monitored by spaceborne radar interferometry, Nature, 375, 567, 10.1038/375567a0

Peltzer, 1995, Surface displacement of the 17 May 1993 Eureka Valley, California, earthquake observed by SAR interferometry, Science, 268, 1333, 10.1126/science.268.5215.1333

Atzori, 2008, Postseismic displacement of the 1999 Athens earthquake retrieved by the differential interferometry by synthetic aperture radar time series, J. Geophys. Res., 113, 1

Biggs, 2009, The postseismic response to the 2002 M 7.9 denali fault earthquake: Constraints from InSAR 2003–2005, Geophys. J. Int., 176, 353, 10.1111/j.1365-246X.2008.03932.x

Fialko, 2014, El mayor-cucapah (Mw 7.2) earthquake: Early near-field postseismic deformation from InSAR and GPS observations, J. Geophys. Res. Solid Earth, 119, 1482, 10.1002/2013JB010193

Wang, 2018, Observations and modeling of coseismic and postseismic deformation due to the 2015 Mw 7.8 gorkha (Nepal) earthquake, J. Geophys. Res. Solid Earth, 123, 761, 10.1002/2017JB014620

Walters, 2011, Interseismic strain accumulation across the North Anatolian fault from envisat InSAR measurements, Geophys. Res. Lett., 38, 1, 10.1029/2010GL046443

Wright, 2001, Measurement of interseismic strain accumulation across the North Anatolian fault by satellite radar interferometry, Geophys. Res. Lett., 28, 2117, 10.1029/2000GL012850

Wright, 2013, Earthquake cycle deformation and the moho: Implications for the rheology of continental lithosphere, Tectonophysics, 609, 504, 10.1016/j.tecto.2013.07.029

Xu, 2018, Interseismic ground deformation and fault slip rates in the greater San Francisco bay area from two decades of space geodetic data, J. Geophys. Res. Solid Earth, 123, 8095, 10.1029/2018JB016004

Pritchard, 2004, An InSAR-based survey of volcanic deformation in the central Andes, Geochem. Geophys. Geosyst., 5, 1, 10.1029/2003GC000610

Biggs, 2009, Multiple inflation and deflation events at Kenyan volcanoes, East African Rift, Geology, 37, 979, 10.1130/G30133A.1

Biggs, 2014, Global link between deformation and volcanic eruption quantified by satellite imagery, Nat. Commun., 5, 3471, 10.1038/ncomms4471

Juncu, 2017, Anthropogenic and natural ground deformation in the Hengill geothermal area, Iceland, J. Geophys. Res. Solid Earth, 122, 692, 10.1002/2016JB013626

Maghsoudi, 2018, Using PS-InSAR to detect surface deformation in geothermal areas of West Java in Indonesia, Int. J. Appl. Earth Obs. Geoinf., 64, 386

Temtime, 2018, Spatial and temporal patterns of deformation at the Tendaho geothermal prospect, Ethiopia, J. Volcanol. Geotherm. Res., 357, 56, 10.1016/j.jvolgeores.2018.04.004

Ardizzone, 2014, Enhanced landslide investigations through advanced DInSAR techniques: The ivancich case study, Assisi, Italy, Remote Sens. Environ., 142, 69, 10.1016/j.rse.2013.11.003

Lauknes, 2010, Detailed rockslide mapping in northern Norway with small baseline and persistent scatterer interferometric SAR time series methods, Remote Sens. Environ., 114, 2097, 10.1016/j.rse.2010.04.015

European Space Agency (2020, May 27). Sentinel 1 Observation Scenario. Available online: https://sentinel.esa.int/web/sentinel/missions/sentinel-1/observation-scenario.

Elliott, 2016, The role of space-based observation in understanding and responding to active tectonics and earthquakes, Nat. Commun., 7, 13844, 10.1038/ncomms13844

Hooper, A., Wright, T.J., Spaans, K., Elliott, J., Weiss, J.R., Bagnardi, M., Hatton, E.L., Ebmeier, S.K., Gaddes, M., and Qiu, Q. (2018, January 22–27). Global monitoring of fault zones and volcanoes with Sentinel-1. Proceedings of the IGARSS 2018, Valencia, Spain.

Elliott, J. (2020). Earth Observation for the assessment of earthquake hazard, risk and disaster management. Surv. Geophys., under review.

Gaddes, 2019, Using machine learning to automatically detect volcanic unrest in a time series of interferograms, J. Geophys. Res. Solid Earth, 124, 12304, 10.1029/2019JB017519

Albino, 2019, Dyke intrusion between neighbouring arc volcanoes responsible for 2017 pre-eruptive seismic swarm at Agung, Nat. Commun., 10, 748, 10.1038/s41467-019-08564-9

Zinno, I., Elefante, S., Luca, C.D., Manunta, M., Lanari, R., and Casu, F. (2015, January 26–31). New advances in intensive DInSAR processing through cloud computing environments. Proceedings of the IGARSS 2015, Milan, Italy.

Sentinel Application Platform (SNAP) (2020, February 12). Sentinel-1 Toolbox. Available online: https://step.esa.int/main/toolboxes/sentinel-1-toolbox/.

Rosen, P.A., Gurrola, E., Sacco, G.F., and Zebker, H. (2012, January 23–26). The InSAR scientific computing environment. Proceedings of the EUSAR 2012, Nuremberg, Germany.

Sandwell, 2011, Open radar interferometry software for mapping surface deformation, EOS Trans. AGU, 92, 234, 10.1029/2011EO280002

Hooper, 2004, A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers, Geophys. Res. Lett., 31, 1, 10.1029/2004GL021737

Werner, C., Wegmüller, U., Strozzi, T., and Wiesmann, A. (2000, January 16–20). Gamma SAR and interferometric processing software. Proceedings of the ERS-ENVISAT Symposium, Gothenburg, Sweden.

(2020, February 12). GAMMA Remote Sensing GAMMA Software Information. Available online: https://www.gamma-rs.ch/uploads/media/GAMMA_Software_information_02.pdf.

(2020, February 12). Harris-Geospatial ENVI SARscape—Read, Process, Analyze, and Output Products from SAR Data. Available online: https://www.harrisgeospatial.com/SoftwareTechnology/ENVISARscape.aspx.

SARPROZ (2020, February 12). SARPROZ—The SAR PROcessing Tool by PeriZ. Available online: https://www.sarproz.com/.

Lazecky, M., Hatton, E., Gonzalez, P.J., Hlavacova, I., Jirankova, E., Dvorak, F., Sustr, Z., and Martinovic, J. (2020). Displacements Monitoring over Czechia by IT4S1 System for Automatised Interferometric Measurements using Sentinel-1 Data. Remote Sens., under review.

Dong, 2019, Remote sensing and geospatial technologies in support of a normative land system science: Status and prospects, Curr. Opin. Environ. Sustain., 38, 44, 10.1016/j.cosust.2019.05.003

Sudmanns, 2019, Big earth data: Disruptive changes in earth observation data management and analysis?, Int. J. Digit. Earth, 13, 832, 10.1080/17538947.2019.1585976

(2020, February 13). ESA Thematic Exploitation Platform. Available online: https://tep.eo.esa.int/home.

(2020, February 13). Geohazard Exploitation Platform (GEP). Available online: https://geohazards-tep.eu/.

(2020, February 13). ESA’s Grid Processing on Demand (G-POD) Environment. Available online: https://gpod.eo.esa.int/.

Galve, J.P., Pérez-Peña, J.V., Azañón, J.M., Closson, D., Caló, F., Reyes-Carmona, C., Jabaloy, A., Ruano, P., Mateos, R.M., and Notti, D. (2017). Evaluation of the SBAS InSAR service of the European space agency’s geohazard exploitation platform (GEP). Remote Sens., 9.

Bally, P., and Pinto, S. (2015, January 23–27). The Geohazards Exploitation Platform (GEP). Proceedings of the FRINGE 2015, Frascati, Italy.

Kreemer, 2003, An integrated global model of present-day plate motions and plate boundary deformation, Geophys. J. Int., 154, 8, 10.1046/j.1365-246X.2003.01917.x

Bekaert, D.P., Karim, M., Linick, J.P., Hua, H., Sangha, S., Lucas, M., Malarout, N., Agram, P.S., Pan, L., and Owen, S.E. (2019, January 9–13). Development of open-access Standardized InSAR Displacement Products by the Advanced Rapid Imaging and Analysis (ARIA) Project for Natural Hazards. Proceedings of the AGU Fall Meeting 2019, San Francisco, CA, USA.

Werner, 2016, Sentinel-1 support in the GAMMA software, Procedia Comput. Sci., 100, 1305, 10.1016/j.procs.2016.09.246

Yu, 2018, Generic atmospheric correction model for interferometric synthetic aperture radar observations, J. Geophys. Res. Solid Earth, 123, 9202, 10.1029/2017JB015305

Weiss, 2020, High-Resolution surface velocities and strain for Anatolia from Sentinel-1 InSAR and GNSS data, Geophys. Res. Lett., GL087376, 1

Wright, 2004, Toward mapping surface deformation in three dimensions using InSAR, Geophys. Res. Lett., 31, 1, 10.1029/2003GL018827

Farr, 2007, The shuttle radar topography mission, Rev. Geophys., 45, 1, 10.1029/2005RG000183

Brcic, 2016, Interferometric Processing of Sentinel-1 TOPS Data, IEEE Trans. Geosci. Remote Sens., 54, 2220, 10.1109/TGRS.2015.2497902

Qin, Y., Perissin, D., and Bai, J. (2018). Investigations on the coregistration of Sentinel-1 TOPS with the conventional cross-correlation technique. Remote Sens., 10.

Chen, 2002, Phase unwrapping for large SAR interferograms: Statistical segmentation and generalized network models, IEEE Trans. Geosci. Remote Sens., 40, 1709, 10.1109/TGRS.2002.802453

Goldstein, 1998, Radar interferogram filtering for geophysical applications, Geophys. Res. Lett., 25, 4035, 10.1029/1998GL900033

Hooper, A. (December, January 30). A statistical-cost approach to unwrapping the phase of InSAR time series. Proceedings of the International Workshop on ERS SAR Interferometry, Frascati, Italy.

USGS (2020, May 27). LIBCOMCAT. Available online: https://github.com/usgs/libcomcat/.

Lawrence, B.N., Kunkel, J.M., Churchill, J., Massey, N., Kershaw, P., and Pritchard, M. (2020, February 12). Beating Data Bottlenecks in Weather and Climate Science. Available online: https://www.bnlawrence.net/assets/papers/LawEA18.pdf.

Lawrence, B.N., Bennett, V.L., Churchill, J., Juckes, M., Kershaw, P., Pascoe, S., Pepler, S., Pritchard, M., and Stephens, A. (2013, January 6–9). Storing and manipulating environmental big data with JASMIN. Proceedings of the 2013 IEEE International Conference on Big Data, Santa Clara, CA, USA.

European Space Agency (2020, May 27). Sentinel 1A C-Band Synthetic Aperture Radar (SAR): Interferometric Wide (IW) Mode Single Look Complex (SLC) Level 1 Data. Available online: https://catalogue.ceda.ac.uk/uuid/f7014a8d35b648a5983a681fa346d8fc.

Venzke, E. (2020, July 27). Global Volcanism Program—Volcanoes of the World, v. 4.9.0 (04 June 2020). Available online: https://doi.org/10.5479/si.GVP.VOTW4-2013.

Styron, R. (2020, July 27). GEMScienceTools/gem-global-active-faults: First Release of 2019 (Version 2019.0). Available online: http://doi.org/10.5281/zenodo.3376300.

European Space Agency (2020, February 12). Sentinel-1 Strip Map Mode. Available online: https://sentinel.esa.int/web/sentinel/technical-guides/sentinel-1-sar/products-algorithms/level-1/single-look-complex/stripmap.

Shen, 2019, A spatially varying scaling method for InSAR tropospheric corrections using a high-resolution weather model, J. Geophys. Res. Solid Earth, 124, 4051, 10.1029/2018JB016189

Morishita, Y., Lazecky, M., Wright, T.J., Weiss, J.R., Elliott, J.R., and Hooper, A. (2020). LiCSBAS: An open-source InSAR time series analysis package integrated with the LiCSAR automated Sentinel-1 InSAR processor. Remote Sens., 12.

Heimann, 2019, A python framework for efficient use of pre-computed green’s functions in seismological and other physical forward and inverse source problems, Solid Earth, 10, 1921, 10.5194/se-10-1921-2019

Hussain, 2016, Interseismic strain accumulation across the central North Anatolian fault from iteratively unwrapped InSAR measurements, J. Geophys. Res. Solid Earth, 121, 9000, 10.1002/2016JB013108

Emre, 2018, Active fault database of Turkey, Bull. Earthq. Eng., 16, 3229, 10.1007/s10518-016-0041-2

Gaddes, 2018, Blind signal separation methods for InSAR: The potential to automatically detect and monitor signals of volcanic deformation, J. Geophys. Res. Solid Earth, 123, 210, 10.1029/2018JB016210

Anantrasirichai, 2019, A deep learning approach to detecting volcano deformation from satellite imagery using synthetic datasets, Remote Sens. Environ., 230, 111179, 10.1016/j.rse.2019.04.032

Anantrasirichai, 2019, The application of convolutional neural networks to detect slow, sustained deformation in InSAR time series, Geophys. Res. Lett., 46, 11850, 10.1029/2019GL084993

Anantrasirichai, 2018, Application of machine learning to classification of volcanic deformation in routinely generated InSAR data, J. Geophys. Res. Solid Earth, 123, 6592, 10.1029/2018JB015911

Moore, 2019, The 2017 eruption of erta ‘ale volcano, ethiopia: Insights into the shallow axial plumbing system of an incipient mid-ocean ridge, Geochem. Geophys. Geosystems, 20, 5727, 10.1029/2019GC008692

Atwood, 2010, Using L-band SAR coherence to delineate glacier extent, Can. J. Remote Sens., 36, S186, 10.5589/m10-014

Burrows, K., Walters, R.J., Milledge, D., Spaans, K., and Densmore, A.L. (2019). A new method for large-scale landslide classification from satellite radar. Remote Sens., 11.