Reconstruction and Evaluation of DEMs From Bistatic Tandem-X SAR in Mountainous and Coastal Areas of China

TerraSAR-X add-on for Digital Elevation Measurements (TanDEM-X) mission is designed to generate 3-D images of the Earth as the first bistatic synthetic aperture radar (SAR). However, few quantitative studies of TanDEM-X digital elevation model (DEM) quality validation have been conducted specifically in China. This article presents an iterative method to generate high-resolution TanDEM-X DEMs and assesses the vertical accuracy with high-accuracy GPS observations, 1 arc second global DEMs available [Advanced Land Observing Satellite World 3-D-30 m v2.2, Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) v3, Shuttle Radar Topography Mission (SRTM) v3.1, NASADEM, and X-band SRTM], and TanDEM-X 90 m DEM. The results demonstrate remarkable elevation quality and consistency in coastal areas with root mean square error of 1.7 m and 90% linear error (LE90) of 0.4 m, whereas 3–4 times weaker accuracies in steep mountainous areas. A positive bias of 1–2 m for an overall LE90 measure exists in the dense vegetation and steep-slope mountainous areas. TanDEM-X DEM-based SAR interferometry deformation uncertainty simulation indicates a low or even negligible topographic error contribution of 2–4 mm in mountainous areas and less than 1 mm in coastal areas. It indicates that the TanDEM-X DEM performs better than other global DEMs overall and shows a better elevation consistence with SRTM C-band DEM in the coastal area. As an excellent source of up-to-date information, the TanDEM-X DEM are expected be an advantage for understanding dynamic land use changes and improving identification and delineation of coastal lands, mountainous landslides, and earthquakes disasters.

[1]  Roberto Tomás,et al.  Monitoring activity at the Daguangbao mega-landslide (China) using Sentinel-1 TOPS time series interferometry , 2016 .

[2]  Bin Chen,et al.  Stable classification with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017. , 2019, Science bulletin.

[3]  Benjamin Bräutigam,et al.  First Characterization and Performance Evaluation of Bistatic TanDEM-X Experimental Products , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[4]  Antonio Pepe,et al.  On the Extension of the Minimum Cost Flow Algorithm for Phase Unwrapping of Multitemporal Differential SAR Interferograms , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Thomas A. Hennig,et al.  The Shuttle Radar Topography Mission , 2001, Digital Earth Moving.

[6]  P. Rosen,et al.  SYNTHETIC APERTURE RADAR INTERFEROMETRY TO MEASURE EARTH'S SURFACE TOPOGRAPHY AND ITS DEFORMATION , 2000 .

[7]  Seung-Kuk Lee,et al.  High-Accuracy Tidal Flat Digital Elevation Model Construction Using TanDEM-X Science Phase Data , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[8]  E. Rodríguez,et al.  A Global Assessment of the SRTM Performance , 2006 .

[9]  B. Bookhagen,et al.  High-resolution digital elevation models from single-pass TanDEM-X interferometry over mountainous regions: A case study of Inylchek Glacier, Central Asia , 2017 .

[10]  Ali P. Yunus,et al.  Evaluation of DEM generation based on Interferometric SAR using TanDEM-X data in Tokyo , 2015 .

[11]  C. Werner,et al.  Radar interferogram filtering for geophysical applications , 1998 .

[12]  Alessandro Simoni,et al.  The Influence of External Digital Elevation Models on PS-InSAR and SBAS Results: Implications for the Analysis of Deformation Signals Caused by Slow Moving Landslides in the Northern Apennines (Italy) , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[13]  Keqi Zhang,et al.  Comparison of TanDEM-X DEM with LiDAR Data for Accuracy Assessment in a Coastal Urban Area , 2019, Remote. Sens..

[14]  Jan-Peter Muller,et al.  A new quality validation of global digital elevation models freely available in China , 2016 .

[15]  M. Liao,et al.  Landslide Displacement Monitoring with Split-Bandwidth Interferometry: A Case Study of the Shuping Landslide in the Three Gorges Area , 2017, Remote. Sens..

[16]  Carlos H. Grohmann,et al.  Evaluation of TanDEM-X DEMs on selected Brazilian sites: Comparison with SRTM, ASTER GDEM and ALOS AW3D30 , 2017, Remote Sensing of Environment.

[17]  Arif Oguz Altunel,et al.  Evaluation of TanDEM-X 90 m Digital Elevation Model , 2019, International Journal of Remote Sensing.

[18]  Paul D. Bates,et al.  Improving the TanDEM-X Digital Elevation Model for flood modelling using flood extents from Synthetic Aperture Radar images , 2016 .

[19]  T. Wright,et al.  Multi-interferogram method for measuring interseismic deformation: Denali Fault, Alaska , 2007 .

[20]  Michael Höhle,et al.  Accuracy assessment of digital elevation models by means of robust statistical methods , 2009 .

[21]  Michael Eineder,et al.  TanDEM-X calibrated Raw DEM generation , 2012 .

[22]  Gianfranco Fornaro,et al.  A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms , 2002, IEEE Trans. Geosci. Remote. Sens..

[23]  Peizhen Zhang,et al.  Slip maxima at fault junctions and rupturing of barriers during the 2008 Wenchuan earthquake , 2009 .

[24]  Wolfgang Koppe,et al.  Evaluation of Vertical Accuracy of the WorldDEM™ Using the Runway Method , 2016, Remote. Sens..

[25]  Gang Li,et al.  Heterogeneous decadal glacier downwasting at the Mt. Everest (Qomolangma) from 2000 to ~ 2012 based on multi-baseline bistatic SAR interferometry , 2018 .

[26]  Yann Klinger,et al.  Coseismic reverse- and oblique-slip surface faulting generated by the 2008 Mw 7.9 Wenchuan earthquake, China , 2009 .

[27]  Willem Viveen,et al.  Evaluation of ASTER GDEM2, SRTMv3.0, ALOS AW3D30 and TanDEM-X DEMs for the Peruvian Andes against highly accurate GNSS ground control points and geomorphological-hydrological metrics , 2020 .

[28]  K. Feigl,et al.  Radar interferometry and its application to changes in the Earth's surface , 1998 .

[29]  Achim Roth,et al.  Accuracy assessment of the global TanDEM-X Digital Elevation Model with GPS data , 2018 .

[30]  Zhenhong Li,et al.  Integration of InSAR Time-Series Analysis and Water-Vapor Correction for Mapping Postseismic Motion After the 2003 Bam (Iran) Earthquake , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[31]  Jing-nan Liu,et al.  Entering the Era of Earth Observation-Based Landslide Warning Systems: A Novel and Exciting Framework , 2020, IEEE Geoscience and Remote Sensing Magazine.

[32]  Peng Li,et al.  Evaluation of ASTER GDEM using GPS benchmarks and SRTM in China , 2013 .

[33]  Keqi Zhang,et al.  Accuracy assessment of ASTER, SRTM, ALOS, and TDX DEMs for Hispaniola and implications for mapping vulnerability to coastal flooding , 2019, Remote Sensing of Environment.

[34]  Sean Vitousek,et al.  Doubling of coastal flooding frequency within decades due to sea-level rise , 2017, Scientific Reports.

[35]  R. Horton,et al.  Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood , 2016 .

[36]  M. Stokes,et al.  Which DEM is best for analysing fluvial landscape development in mountainous terrains? , 2018 .

[37]  R. Hanssen Radar Interferometry: Data Interpretation and Error Analysis , 2001 .

[38]  David Loibl,et al.  Evaluation of TanDEM-X elevation data for geomorphological mapping and interpretation in high mountain environments — A case study from SE Tibet, China , 2015 .

[39]  Christiane Schmullius,et al.  TanDEM-X IDEM precision and accuracy assessment based on a large assembly of differential GNSS measurements in Kruger National Park, South Africa , 2016 .

[40]  Yong Li,et al.  Mass wasting triggered by the 2008 Wenchuan earthquake is greater than orogenic growth , 2011 .

[41]  Gerhard Krieger,et al.  Generation and performance assessment of the global TanDEM-X digital elevation model , 2017 .

[42]  Laurence Hawker,et al.  Accuracy assessment of the TanDEM-X 90 Digital Elevation Model for selected floodplain sites , 2019, Remote Sensing of Environment.

[43]  XU Caijun,et al.  Rupture of deep faults in the 2008 Wenchuan earthquake and uplift of the Longmen Shan , 2011 .

[44]  Michael Abrams,et al.  ASTER Global Digital Elevation Model (GDEM) and ASTER Global Water Body Dataset (ASTWBD) , 2020, Remote. Sens..

[45]  Takeo Tadono,et al.  Quality Improvements of ‘AW3D’ Global Dsm Derived from Alos Prism , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[46]  A. Cazenave,et al.  Sea level rise and its coastal impacts , 2014 .

[47]  Pedro Skvarca,et al.  Constraining glacier elevation and mass changes in South America , 2019, Nature Climate Change.

[48]  D. Gesch Consideration of Vertical Uncertainty in Elevation-Based Sea-Level Rise Assessments: Mobile Bay, Alabama Case Study , 2013 .

[49]  Gerhard Krieger,et al.  TanDEM-X: The New Global DEM Takes Shape , 2014, IEEE Geoscience and Remote Sensing Magazine.

[50]  Fabio Rocca,et al.  Permanent scatterers in SAR interferometry , 2001, IEEE Trans. Geosci. Remote. Sens..

[51]  Peng Liu,et al.  Spatiotemporal characteristics of the Huangtupo landslide in the Three Gorges region (China) constrained by radar interferometry , 2014 .

[52]  Cem Kincal,et al.  Using advanced InSAR time series techniques to monitor landslide movements in Badong of the Three Gorges region, China , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[53]  N. K. Pavlis,et al.  The Development of the Joint NASA GSFC and the National Imagery and Mapping Agency (NIMA) Geopotential Model EGM96 , 1998 .

[54]  Ping Sun,et al.  Landslide hazards triggered by the 2008 Wenchuan earthquake, Sichuan, China , 2009 .

[55]  K. Yin,et al.  Mechanism of the slow-moving landslides in Jurassic red-strata in the Three Gorges Reservoir, China , 2014 .

[56]  Jan-Peter Muller,et al.  Evaluating sub-pixel offset techniques as an alternative to D-InSAR for monitoring episodic landslide movements in vegetated terrain , 2014 .

[57]  Heresh Fattahi,et al.  DEM Error Correction in InSAR Time Series , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[58]  Peter F. Fisher,et al.  Causes and consequences of error in digital elevation models , 2006 .

[59]  A. Brenning,et al.  The performance of landslide susceptibility models critically depends on the quality of digital elevation models , 2020 .

[60]  James A. Slater,et al.  Global Assessment of the New ASTER Global Digital Elevation Model , 2011 .

[61]  Chuang Shi,et al.  Impacts of geoid height on large-scale crustal deformation mapping with InSAR observations , 2013 .