Agricultural Land Cover Mapping based on Sentinel-1 Coherence Time-Series

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Abstract

The study is aimed at understanding the value of interferometric coherence in mapping regions characterized by a mixture of crops and grasses. The results highlight that a 5% improvement in the classification accuracy can be achieved by using the coherence in addition to the backscatter intensity and by combining VV and VH. It is shown that the largest contribute in class discrimination is brought in winter, when dry vegetation and bare soils can be expected. It was also notably observed that coherence information can enhance the identification of harvesting events in a small but significant number of cases.

Original languageEnglish
Title of host publicationEUSAR 2021 - 13th European Conference on Synthetic Aperture Radar, Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages517-520
Number of pages4
ISBN (Electronic)9783800754571
Publication statusPublished - 2021
Event13th European Conference on Synthetic Aperture Radar, EUSAR 2021 - Virtual, Online, Germany
Duration: 29 Mar 20211 Apr 2021

Publication series

NameProceedings of the European Conference on Synthetic Aperture Radar, EUSAR
Volume2021-March
ISSN (Print)2197-4403

Conference

Conference13th European Conference on Synthetic Aperture Radar, EUSAR 2021
CountryGermany
CityVirtual, Online
Period29/03/211/04/21

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