Campo-Bescós, Miguel

Profile Picture

Email Address

person.page.identifierURI

https://academica-e.unavarra.es/handle/2454/48790

Birth Date

Job Title

Last Name

Campo-Bescós

First Name

Miguel

person.page.departamento

Ingeniería

person.page.instituteName

IS-FOOD. Research Institute on Innovation & Sustainable Development in Food Chain

ORCID

0000-0002-0435-3765

person.page.observainves

88634

person.page.upna

3584

Name

Filters

20221
Reset filters

Settings

Author: González de Audícana Amenábar, María × Subject: SAR ×

Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    PublicationOpen Access
    New methodology for wheat attenuation correction at C-Band VV-polarized backscatter time series
    (IEEE, 2022) Arias Cuenca, María; Campo-Bescós, Miguel; Arregui Odériz, Luis Miguel; González de Audícana Amenábar, María; Álvarez-Mozos, Jesús; Agronomia, Bioteknologia eta Elikadura; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Agronomía, Biotecnología y Alimentación; Ingeniería
    Wheat is one of the most important crops worldwide, and thus the use of remote sensing data for wheat monitoring has attracted much interest. Synthetic Aperture Radar (SAR) observations show that, at C-band and VV polarization, wheat canopy attenuates the surface scattering component from the underlying soil during a significant part of its growth cycle. This behavior needs to be accounted for or corrected before soil moisture retrieval is attempted. The objective of this paper is to develop a new method for wheat attenuation correction (WATCOR) applicable to Sentinel-1 VV time series and based solely on the information contained in the time series itself. The hypothesis of WATCOR is that without attenuation, VV backscatter would follow a stable long-term trend during the agricultural season, with short-term variations caused by soil moisture dynamics. The method relies on time series smoothing and changing point detection, and its implementation follows a series of simple steps. The performance of the method was compared by evaluating the correlation between backscatter and soil moisture content in six wheat fields with available soil moisture data. The Water Cloud Model (WCM) was also applied as a benchmark. The results showed that WATCOR successfully removed the attenuation in the time series, and achieved the highest correlation with soil moisture, improving markedly the correlation of the original backscatter. WATCOR can be easily implemented, as it does not require parameterization or any external data, only an approximate indication of the period where attenuation is likely to occur.