DOI

This paper presents the results of a study aiming to identify targets in Synthetic Aperture Radar (SAR) images having different properties in terms of microwave scattering and temporal stability using the interferometric SAR coherence and the Principal Component Analysis (PCA). Coherence maps used in this analysis are generated starting from a time series of Sentinel-1 images. A flat area in Padan plain (Italy), characterized by agricultural fields with different crops, urban settlements and water surfaces is chosen as study area.

Original languageEnglish
Title of host publicationRemote Sensing for Agriculture, Ecosystems, and Hydrology XXI
EditorsChristopher M. U. Neale, Antonino Maltese
PublisherSPIE
ISBN (Electronic)9781510630017
DOIs
StatePublished - 1 Jan 2019
EventRemote Sensing for Agriculture, Ecosystems, and Hydrology XXI 2019 - Strasbourg, France
Duration: 9 Sep 2019 → 11 Sep 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11149
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceRemote Sensing for Agriculture, Ecosystems, and Hydrology XXI 2019
Country/TerritoryFrance
CityStrasbourg
Period9/09/19 → 11/09/19

    Research areas

  • Interferometric coherence, Principal Component Analysis (PCA), SAR interferometry (InSAR), Sentinel-1, Synthetic Aperture Radar (SAR)

    Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

ID: 51466539