ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume V-3-2022
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 115–122, 2022
https://doi.org/10.5194/isprs-annals-V-3-2022-115-2022
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 115–122, 2022
https://doi.org/10.5194/isprs-annals-V-3-2022-115-2022
 
17 May 2022
17 May 2022

PERFORMANCE OF NUMERICAL WEATHER PRODUCTS FOR INSAR TROPOSPHERIC CORRECTION: A CASE STUDY OF A TROPICAL REGION

P. Kirui1,2, B. Riedel1, and M. Gerke1 P. Kirui et al.
  • 1Institute of Geodesy and Photogrammetry Bienroder weg 81, 38106 Braunschweig, Germany
  • 2Department of Geomatic Engineering, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

Keywords: Tropospheric delay, numerical weather models, Sentinel-1, InSAR

Abstract. Tropospheric delay variability remains a significant source of error in the InSAR-derived measurements. Numerical weather models have been proposed as an alternative technique to mitigate tropospheric delays in InSAR and have become a standard procedure for some multi-temporal InSAR processing workflows. This study evaluates the viability of three numerical weather models for mitigating tropospheric delay in InSAR for a tropical region. We assess their performance in correcting tropospheric delay in Sentinel-1 interferograms at different spatial wavelengths using variograms. Their performance is validated using GNSS tropospheric delay and our proposed SAR-derived tropospheric delay estimates. The results indicate that numerical weather model estimates do not mitigate short-wavelength turbulent delays, but can mitigate long-wavelength stratified delays to some extent, which may also introduce additional errors in interferograms. At a spatial wavelength of 40 km, 36% of the interferograms showed increased spatial autocorrelation after correction with GACOS, 55% with ERA-5, and 51% with MERRA-2. In contrast the InSAR-derived tropospheric delays resulted in a significant reduction in variance at all wavelengths indicating the ability to mitigate both turbulent and stratified delays. Our study demonstrates the limited potential of numerical weather model estimates to satisfactorily mitigate trophospheric noise in InSAR and the capability of InSAR-derived trophospheric delay to significantly correct tropospheric noise in InSAR.