Multitemporal SAR and polarimetric SAR optimization and classification: Reinterpreting temporal coherence

In multitemporal synthetic aperture radar (SAR) and polarimetric SAR (PolSAR), coherence is a capital parameter to exploit common information between temporal acquisitions. Yet, its use is limited to high coherences. This article proposes the analysis of low-coherence scenarios by introducing a rein...

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Detalles Bibliográficos
Autores: Ni, Jun, López Martínez, Carlos|||0000-0002-1366-9446, Hu, Zhongbo, Zhang, Fan
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/376656
Acceso en línea:https://hdl.handle.net/2117/376656
https://dx.doi.org/10.1109/TGRS.2022.3214097
Access Level:acceso abierto
Palabra clave:Synthetic aperture radar
Radiation -- Measurement
Data mining
Change detection
Classification
Coherence
Crop monitoring
Polarimetric synthetic aperture radar (PolSAR)
SAR
Radar d'obertura sintètica
Radiació -- Mesurament
Mineria de dades
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Radar
Descripción
Sumario:In multitemporal synthetic aperture radar (SAR) and polarimetric SAR (PolSAR), coherence is a capital parameter to exploit common information between temporal acquisitions. Yet, its use is limited to high coherences. This article proposes the analysis of low-coherence scenarios by introducing a reinterpretation of coherence. It is demonstrated that coherence results from the product of two terms accounting for coherent and radiometric changes, respectively. For low coherences, the first term presents low values, preventing its exploitation for information retrieval. The information provided by the second term can be used in these circumstances to exploit common information. This second term is proposed, as an alternative to coherence, for information retrieval for low coherences. Besides, it is shown that polarimetry allows the temporal optimization of its values. To prove the benefits of this approach, multitemporal SAR and PolSAR data classification is considered as a tool, showing that improvements of the classification overall accuracy may range between 20% and 50%, compared to classification based on coherence.