A Discussion on the Goldstein Filtering Parameters Within the Snap Software

Y. Y. Wu, H. Ren, A. Madson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Goldstein filtering is a widely used phase filtering method for Interferometric Synthetic Aperture Radar (InSAR) processing for the purpose of noise reduction. While filtering methods can effectively reduce noise, we note that strong filters may produce artifact features shown as cross-like patterns in interferograms. In this paper, the adjustable parameters of Goldstein filtering in the Sentinel Application Platform (SNAP) software are explored, and InSAR-derived DEMs were generated to investigate how each parameter influences interferograms and whether the cross-like patterns are adverse features for InSAR processing. The results showed that adaptive filter exponent and FFT size are the most influential parameters that significantly affect the strength of Goldstein filters. Furthermore, our findings imply that the presence of cross-like patterns has a negative impact on InSAR processing. As the default values for Goldstein filtering in the SNAP software are excessively high and frequently exhibits cross-like patterns, we suggest users to modify the adaptive filter exponent to a value of 0.5-0.6.

Original languageEnglish
Title of host publicationIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7985-7988
Number of pages4
ISBN (Electronic)9798350320107
DOIs
StatePublished - 2023
Event2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, United States
Duration: 16 Jul 202321 Jul 2023

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2023-July

Conference

Conference2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Country/TerritoryUnited States
CityPasadena
Period16/07/2321/07/23

Keywords

  • Cross-like Pattern
  • Goldstein Filtering
  • Interferometric Synthetic Aperture Radar Technique
  • SNAP

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