Open Access
On the influence of acquisition geometry in backscatter time series over wheat
(Elsevier, 2022) Arias Cuenca, María; Campo-Bescós, Miguel; Álvarez-Mozos, Jesús; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ingeniería; Gobierno de Navarra / Nafarroako Gobernua
Dense time series of Sentinel-1 imagery are an invaluable information source for agricultural applications. Multiple orbits can observe a specific area and their combination could improve the temporal resolution of the time series. However, the orbits have different acquisition geometries regarding incidence and azimuth angles that need to be considered. Furthermore, crops are dynamic canopies and the influence of incidence and azimuth angles might change during the agricultural season due to different phenological stages. The main objective of this letter is to evaluate the influence of different acquisition geometries in Sentinel-1 backscatter time series over wheat canopies, and to propose a strategy for their correction. A large dataset of wheat parcels (∼40,000) was used and 344 Sentinel-1 images from three relative orbits were processed during two agricultural seasons. The first analysis was a monthly evaluation of the influence of incidence angle on backscatter (σ0) and terrain flattened backscatter (γ0). It showed that terrain flattening significantly reduced the backscatter dependence on incidence angle, being negligible in VH polarization but not completely in VV polarization. Incidence angle influence in VV backscatter changed in time due to wheat growth dynamics. To further reduce it, an incidence angle normalization technique followed by an azimuthal anisotropy correction were applied. In conclusion, γ0 enabled a reasonable combination of different relative orbits, that may be sufficient for many applications. However, for detailed analyses, the correction techniques might be implemented to further reduce orbit differences, especially in bare soil periods or winter months.
Open 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.
Open Access
Sentinel-1 time series applications over agricultural fields: proposal, evaluation and comparison of different methodologies
(2023) Arias Cuenca, María; Álvarez-Mozos, Jesús; Campo-Bescós, Miguel; Ingeniería; Ingeniaritza
La monitorización de los cultivos es esencial para diferentes aplicaciones, como el aseguramiento de la seguridad alimentaria, la gestión de los cultivos y la implementación de políticas agrarias. La teledetección proporciona información acerca de las propiedades biofísicas de las plantas y los suelos, así como de la variabilidad espacial en amplias áreas del territorio de forma periódica. El lanzamiento de los satélites radar de apertura sintética (SAR) Sentinel-1 en 2014 y 2016 permitió la adquisición de series temporales densas de imágenes con buena resolución espacial y temporal incluso en zonas cubiertas de nubes. El principal objetivo de esta tesis es la evaluación de diferentes metodologías para aplicaciones agrícolas a escala de parcela usando series temporales Sentinel-1. En primer lugar, se propuso una metodología de clasificación de cultivos supervisada basada en las firmas temporales de Sentinel-1. Se implementó en un caso de estudio con 14 clases de cultivos y un dataset grande de parcelas agrícolas. En segundo lugar, se evaluó la influencia de la geometría de adquisición de las imágenes Sentinel-1 sobre parcelas de trigo. Se evaluó la influencia del ángulo de incidencia en la retrodispersión y los coeficientes de terrain-flattening, y se aplicó una normalización del ángulo de incidencia seguida de una corrección de la anisotropía azimutal en las series temporales de polarización VV. En tercer lugar, se evaluó la atenuación de la retrodispersión producida por las cubiertas de trigo en polarización VV, y un nuevo método de corrección del efecto de la atenuación llamado WATCOR fue propuesto. Finalmente, cuatro técnicas para estimar la humedad del suelo basadas en series temporales de Sentinel-1 en cultivo de trigo fueron evaluadas, proponiendo diferentes alternativas metodológicas para su aplicación a escala de parcela. A pesar de la complejidad de la estimación de la humedad del suelo a escala de parcela únicamente con datos SAR, se obtuvieron estimaciones aceptables. Los resultados de esta tesis demostraron que el análisis y la extracción de información contenida en series temporales SAR es útil para diferentes aplicaciones, augurando interesantes desarrollos futuros en este campo.

Arias Cuenca, María

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