Next Article in Journal
Performance Evaluation for China’s Planned CO2-IPDA
Previous Article in Journal
A Method to Obtain Orange Crop Geometry Information Using a Mobile Terrestrial Laser Scanner and 3D Modeling
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Remote Sens. 2017, 9(8), 765;

Correcting InSAR Topographically Correlated Tropospheric Delays Using a Power Law Model Based on ERA-Interim Reanalysis

SAR/InSAR Engineering Applications Laboratory (SEAL), Nanjing Institute of Surveying, Mapping & Geotechnical Investigation, Co., Ltd., Nanjing 210019, China
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing 100083, China
Author to whom correspondence should be addressed.
Received: 20 June 2017 / Revised: 20 July 2017 / Accepted: 20 July 2017 / Published: 26 July 2017
(This article belongs to the Section Atmosphere Remote Sensing)
Full-Text   |   PDF [8560 KB, uploaded 26 July 2017]   |  


Tropospheric delay caused by spatiotemporal variations in pressure, temperature, and humidity in the lower troposphere remains one of the major challenges in Interferometric Synthetic Aperture Radar (InSAR) deformation monitoring applications. Acquiring an acceptable level of accuracy (millimeter-level) for small amplitude surface displacement is difficult without proper delay estimation. Tropospheric delay can be estimated from the InSAR phase itself using the spatiotemporal relationship between the phase and topography, but separating the deformation signal from the tropospheric delay is difficult when the deformation is topographically related. Approaches using external data such as ground GPS networks, space-borne spectrometers, and meteorological observations have been exploited with mixed success in the past. These methods are plagued, however, by low spatiotemporal resolution, unfavorable weather conditions or limited coverage. A phase-based power law method recently proposed by Bekaert et al. estimates the tropospheric delay by assuming the phase and topography following a power law relationship. This method can account for the spatial variation of the atmospheric properties and can be applied to interferograms containing topographically correlated deformation. However, the parameter estimates of this method are characterized by two limitations: one is that the power law coefficients are estimated using the sounding data, which are not always available in a study region; the other is that the scaled factor between band-filtered topography and phase is inverted by least squares regression, which is not outlier-resistant. To address these problems, we develop and test a power law model based on ERA-Interim (PLE). Our version estimates the power law coefficients by using ERA-Interim (ERA-I) reanalysis. A robust estimation technique was introduced in the PLE method to estimate the scaled factor, which is insensitive to outliers. We applied the PLE method to ENVISAT ASAR images collected over Southern California, US, and Tianshan, China. We compared tropospheric corrections estimated from using our PLE method with the corrections estimated using the linear method and ERA-I method. Accuracy was evaluated by using delay measurements from the Medium Resolution Imaging Spectrometer (MERIS) onboard the ENVISAT satellite. The PLE method consistently delivered greater standard deviation (STD) reduction after tropospheric corrections than both the linear method and ERA-I method and agreed well with the MERIS measurements. View Full-Text
Keywords: InSAR; tropospheric delay; ERA-Interim; power law; phase-based model InSAR; tropospheric delay; ERA-Interim; power law; phase-based model

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Zhu, B.; Li, J.; Tang, W. Correcting InSAR Topographically Correlated Tropospheric Delays Using a Power Law Model Based on ERA-Interim Reanalysis. Remote Sens. 2017, 9, 765.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top