On the separation of ground and canopy scatterings using single polarimetric multi-baseline SAR tomography

H. Aghababaee, Alessandra Budillon, Giampaolo Ferraioli, Vito Pascazio, Gilda Schirinzi

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

Abstract

Backscattering separation coming from ground and canopy is one of the main aims in dealing with forest scenario using synthetic aperture radar (SAR) tomography. Theoretically SAR tomography (TomoSAR) provides layover solution, but in practice, insufficient vertical resolution using typical reconstruction approaches may not be sufficient for identification of the vertically aligned scatterers. To cope with this intrinsic issue, we proposed a method that separates the ground and canopy backscatterings based on Random- Volume-over-Ground (RVOG) model and by employing the generalized likelihood ratio test (GLRT) detection schemes over the covariance matrix. Such a separation allows identification of interference of the backscattering, which simply brings the possibility to resolve and separate ground and canopy superposition in the tomogram. Experimental validation of the proposed methodology is provided using a real data set acquired by the ONERA SETHI in the framework of the ESA's campaign, TropiSAR.

Original languageEnglish
Title of host publicationIGARSS 2019 - IEEE International Geoscience and Remote Sensing Symposium
Subtitle of host publication Proceedings
PublisherIEEE
Pages975-978
Number of pages4
ISBN (Electronic)9781538691540
DOIs
Publication statusPublished - Jul 2019
Externally publishedYes
Event39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, Japan
Duration: 28 Jul 20192 Aug 2019
Conference number: 39

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
PublisherIEEE
ISSN (Electronic)2153-7003

Conference

Conference39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Abbreviated titleIGARSS 2019
CountryJapan
CityYokohama
Period28/07/192/08/19

Keywords

  • Forest
  • GLRT
  • RVOG
  • SAR tomography
  • ITC-CV

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