Open Access
Comparison between capacitive and microstructured optical fiber soil moisture sensors
(MDPI, 2018) López Aldaba, Aitor; López Torres, Diego; Campo-Bescós, Miguel; López Rodríguez, José Javier; Yerro Lizarazu, David; Elosúa Aguado, César; Arregui San Martín, Francisco Javier; Auguste, Jean-Louis; Jamier, Raphael; Roy, Philippe; López-Amo Sáinz, Manuel; Ingeniaritza Elektrikoa eta Elektronikoa; Landa Ingeniaritza eta Proiektuak; Institute of Smart Cities - ISC; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ingeniería Eléctrica y Electrónica; Proyectos e Ingeniería Rural
Soil moisture content has always been an important parameter to control because it is a deterministic factor for site-specific irrigation, seeding, transplanting, and compaction detection. In this work, a discrete sensor that is based on a SnO2–FP (Fabry-Pérot) cavity is presented and characterized in real soil conditions. As far as authors know, it is the first time that a microstructured optical fiber is used for real soil moisture measurements. Its performance is compared with a commercial capacitive soil moisture sensor in two different soil scenarios for two weeks. The optical sensor shows a great agreement with capacitive sensor’s response and gravimetric measurements, as well as a fast and reversible response; moreover, the interrogation technique allows for several sensors to be potentially multiplexed, which offers the possibility of local measurements instead of volumetric: it constitutes a great tool for real soil moisture monitoring.
Open Access
Microstructured optical fiber sensor for soil moisture measurements
(Optical Society of America, 2018) López Aldaba, Aitor; López Torres, Diego; Campo-Bescós, Miguel; López Rodríguez, José Javier; Yerro Lizarazu, David; Elosúa Aguado, César; Arregui San Martín, Francisco Javier; Auguste, Jean-Louis; Jamier, Raphael; Roy, Philippe; López-Amo Sáinz, Manuel; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Ingeniaritza; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniería
A discrete sensor based on a Sn0₂-FP (Fabry-Pérot) cavity is presented and characterized in real soil conditions. Results are compared, for the first time to our knowledge, with a commercial capacitive sensor and gravimetric measurements.
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
Combined spatial and temporal effects of environmental controls on long-term monthly NDVI in the Southern Africa savanna
(MDPI, 2013) Campo-Bescós, Miguel; Muñoz Carpena, Rafael; Southworth, Jane; Zhu, Likai; Waylen, Peter; Bunting, Erin; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds in the southern Africa savanna. Dynamic Factor Analysis (DFA), a multivariate time-series dimension reduction technique, was used to identify the most important physical drivers of regional vegetation change. We first evaluated the Advanced Very High Resolution Radiometer (AVHRR)- vs. the Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) datasets across their overlapping period (2001–2010). NDVI follows a general pattern of cyclic seasonal variation, with distinct spatio-temporal patterns across physio-geographic regions. Both NDVI products produced similar DFA models, although MODIS was simulated better. Soil moisture and precipitation controlled NDVI for mean annual precipitation (MAP) < 750 mm, and above this, evaporation and mean temperature dominated. A second DFA with the full AVHRR (1982–2010) data found that for MAP < 750 mm, soil moisture and actual evapotranspiration control NDVI dynamics, followed by mean and maximum temperatures. Above 950 mm, actual evapotranspiration and precipitation dominate. The quantification of the combined spatio-temporal environmental drivers of NDVI expands our ability to understand landscape level changes in vegetation evaluated through remote sensing and improves the basis for the management of vulnerable regions, like the southern Africa savannas.

Campo-Bescós, Miguel

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