Open Access
Clasificación de usos y cubiertas del suelo y análisis de cambios en los alrededores de la Reserva Ecológica Manglares Churute (Ecuador) mediante una serie de imágenes Sentinel-1
(Universidad Politécnica de Valencia, 2020) Vélez Alvarado, Diana; Álvarez-Mozos, Jesús; Ingeniería; Ingeniaritza; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
La gestión de las áreas naturales protegidas frecuentemente obvia la importancia que tiene el territorio que rodea el perímetro del espacio protegido (zona de amortiguación). Estas zonas pueden ser el origen de impactos que amenacen el estado de conservación de los ecosistemas protegidos. En este artículo se describe un caso de estudio centrado en la Reserva Ecológica Manglares Churute (REMCh) de Ecuador, en el que se utilizó una serie temporal de imágenes Sentinel-1 para clasificar los usos y cubiertas del suelo y para analizar los cambios ocurridos en el periodo 2015-2018. Tras procesar la serie de imágenes y delinear el conjunto de zonas de entrenamiento sobre los principales usos y cubiertas se implementó un algoritmo de clasificación Random Forests (RF), cuyos parámetros fueron optimizados mediante una validación cruzada con el conjunto de datos de entrenamiento (70% de la verdad campo). El 30% restante se utilizó para validar la clasificación realizada, logrando una fiabilidad global del 84%, un coeficiente Kappa de 0,8 y unas métricas de rendimiento por clase satisfactorias para los principales cultivos y usos del suelo. Los resultados fueron peores para las clases más heterogéneas y minoritarias, no obstante, se considera que la clasificación fue lo suficientemente precisa para realizar el análisis de cambios perseguido. Entre 2015 y 2018 se constató un aumento en la superficie destinada a usos intensivos como el cultivo de camarón blanco y la caña de azúcar, en detrimento de otros cultivos tradicionales como el arroz o el banano. Aunque estos cambios se produjeron en las zonas que rodean al área natural protegida, pueden causar un deterioro de la calidad del agua debido al uso de fertilizantes y pesticidas, por tanto, se recomienda prestar atención a estas zonas de amortiguamiento a la hora de diseñar políticas e instrumentos adecuados de protección medioambiental.
Open Access
Automatic detection of uprooted orchards based on orthophoto texture analysis
(MDPI, 2017) Ciriza Labiano, Raquel; Sola Torralba, Ion; Albizua, Lourdes; Álvarez-Mozos, Jesús; González de Audícana Amenábar, María; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
Permanent crops, such as olive groves, vineyards and fruit trees, are important in European agriculture because of their spatial and economic relevance. Agricultural geographical databases (AGDBs) are commonly used by public bodies to gain knowledge of the extension covered by these crops and to manage related agricultural subsidies and inspections. However, the updating of these databases is mostly based on photointerpretation, and thus keeping this information up-to-date is very costly in terms of time and money. This paper describes a methodology for automatic detection of uprooted orchards (parcels where fruit trees have been eliminated) based on the textural classification of orthophotos with a spatial resolution of 0.25 m. The textural features used for this classification were derived from the grey level co-occurrence matrix (GLCM) and wavelet transform, and were selected through principal components (PCA) and separability analyses. Next, a Discriminant Analysis classification algorithm was used to detect uprooted orchards. Entropy, contrast and correlation were found to be the most informative textural features obtained from the co-occurrence matrix. The minimum and standard deviation in plane 3 were the selected features based on wavelet transform. The classification based on these features achieved a true positive rate (TPR) of over 80% and an accuracy (A) of over 88%. As a result, this methodology enabled reducing the number of fields to photointerpret by 60–85%, depending on the membership threshold value selected. The proposed approach could be easily adopted by different stakeholders and could increase significantly the efficiency of agricultural database updating tasks.
Open Access
Multitemporal evaluation of topographic correction algorithms using synthetic images
(SPIE, 2012) Sola Torralba, Ion; Álvarez-Mozos, Jesús; González de Audícana Amenábar, María; Torres Escribano, José Luis; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
Land cover classification and quantitative analysis of multispectral data in mountainous regions is considerably hampered by the influence of topography on the spectral response pattern. In the last years, different topographic correction (TOC) algorithms have been proposed to correct illumination differences between sunny and shaded areas observed by optical remote sensors. Although the available number of TOC methods is high, the evaluation of their performance usually relies on the existence of precise land cover information, and a standardised and objective evaluation procedure has not been proposed yet. Besides, previous TOC assessment studies only considered a limited set of illumination conditions, normally assuming favourable illumination conditions. This paper presents a multitemporal evaluation of TOC methods based on synthetically generated images in order to evaluate the influence of solar angles on the performance of TOC methods. These synthetic images represent the radiance an optical sensor would receive under specific geometric and temporal acquisition conditions and assuming a certain land-cover type. A method for creating synthetic images using state-of-the-art irradiance models has been tested for different periods of the year, which entails a variety of solar angles. Considering the real topography of a specific area a Synthetic Real image (SR) is obtained, and considering the relief of this area as being completely flat a Synthetic Horizontal image (SH) is obtained. The comparison between corrected image obtained applying a TOC method to SR image and SH image of the same area, i.e. considered the ideal correction, allows assessing the performance of each TOC algorithm.
Open Access
Effect of topography on retreat rate of different gully headcuts in Bardenas Reales area (Navarre, Spain)
(Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, 2007) Campo-Bescós, Miguel; Álvarez-Mozos, Jesús; Casalí Sarasíbar, Javier; Giménez Díaz, Rafael; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
In Northeast Spain, gullying is a widespread phenomenon. This type of erosion is especially intense in Bardenas Reales (Navarre) where at least two major typical kinds of gully headcut are present. A first group developed in soil material (named, conventional gully headcut), and second group of gully headcut with a sandstone layer as a top horizon (named, sandstone gully headcut). In addition, within the former group, we can distinguish a subgroup of gully headcuts developed in soils particularly prone to piping and tunnelling due to the dispersive condition of the materials (named piping associated gully headcut). In this situation, a question arises: to what extent simple topographic parameters account for the retreat rate of the different kind of gully headcuts observed in the region of Bardenas Reales? The aim of this study was to investigate and gain insight in this issue.
Open Access
On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation
(Elsevier, 2018) Loizu Maeztu, Javier; Massari, Christian; Álvarez-Mozos, Jesús; Tarpanelli, Angelica; Brocca, Luca; Casalí Sarasíbar, Javier; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
Assimilation of remotely sensed surface soil moisture (SSM) data into hydrological catchment models has been identified as a means to improve stream flow simulations, but reported results vary markedly depending on the particular model, catchment and assimilation procedure used. In this study, the in fluence of key aspects, such as the type of model, re-scaling technique and SSM observation error considered, were evaluated. For this aim, Advanced SCATterometer ASCAT-SSM observations were assimilated through the ensemble Kalman filter into two hydrological models of different complexity namely MISDc and TOPLATS) run on two Mediterranean catchments of similar size (750 km2). Three different re-scaling techniques were evaluated (linear re-scaling, variance matching and cumulative distribution function matching), and SSM observation error values ranging from 0.01% to 20% were considered. Four different efficiency measures were used for evaluating the results. Increases in Nash-Sutcliffe efficiency (0.03–0.15) and efficiency indices (10–45%) were obtained, especially when linear re-scaling and observation errors within 4-6% were considered. This study found out that there is a potential to improve stream flow prediction through data assimilation of remotely sensed SSM in catchments of different characteristics and with hydrological models of different conceptualizations schemes, but for that, a careful evaluation of the observation error and re-scaling technique set-up utilized is required.
Open Access
Error in radar-derived soil moisture due to roughness parameterization: an analysis based on synthetical surface profiles
(MDPI, 2009) Lievens, Hans; Vernieuwe, Hilde; Álvarez-Mozos, Jesús; Baets, Bernard de; Verhoest, Niko E. C.; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
In the past decades, many studies on soil moisture retrieval from SAR demonstrated a poor correlation between the top layer soil moisture content and observed backscatter coefficients, which mainly has been attributed to difficulties involved in the parameterization of surface roughness. The present paper describes a theoretical study, performed on synthetical surface profiles, which investigates how errors on roughness parameters are introduced by standard measurement techniques, and how they will propagate through the commonly used Integral Equation Model (IEM) into a corresponding soil moisture retrieval error for some of the currently most used SAR configurations. Key aspects influencing the error on the roughness parameterization and consequently on soil moisture retrieval are: the length of the surface profile, the number of profile measurements, the horizontal and vertical accuracy of profile measurements and the removal of trends along profiles. Moreover, it is found that soil moisture retrieval with C-band configuration generally is less sensitive to inaccuracies in roughness parameterization than retrieval with L-band configuration.
Open Access
On the soil roughness parameterization problem in soil moisture retrieval of bare surfaces from synthetic aperture radar
(MDPI, 2008) Verhoest, Niko E. C.; Lievens, Hans; Wagner, Wolfgang; Álvarez-Mozos, Jesús; Moran, M. Susan; Mattia, Francesco; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar backscatter usually provides inaccurate estimates. The characterization of soil roughness is not fully understood, and a large range of roughness parameter values can be obtained for the same surface when different measurement methodologies are used. In this paper, a literature review is made that summarizes the problems encountered when parameterizing soil roughness as well as the reported impact of the errors made on the retrieved soil moisture. A number of suggestions were made for resolving issues in roughness parameterization and studying the impact of these roughness problems on the soil moisture retrieval accuracy and scale.
Open Access
Photogrammetrical and field measurement of gullies with contrasting morphology
(Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, 2007) Marzolff, I.; Giménez Díaz, Rafael; Seeger, M.; Campo-Bescós, Miguel; Ries, J. B.; Casalí Sarasíbar, Javier; Álvarez-Mozos, Jesús; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
Despite a wealth of studies on monitoring different types of gullies by using remote-sensing technique such as photogrammetry, relatively few efforts have been made to test their accuracy. Therefore the question arises as to what extent the accuracy of gully monitoring using photogrammetric technique depends on gully morphology. The objective of this work is to investigate this issue. To do that, we confront field measurements of cross-sectional areas of gullies with contrasting morphology with a similar dataset obtained using photogrammetry. Below, we present the first findings of this investigation.
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
Estrategia para la verificación de declaraciones PAC a partir de imágenes Sentinel-2 en Navarra
(Universidad Politécnica de Valencia, 2020) González de Audícana Amenábar, María; López Sáenz, Sandra; Sola Torralba, Ion; Álvarez-Mozos, Jesús; Ingeniería; Ingeniaritza
En junio de 2018, la Comisión Europea aprobó una modificación de la Política Agraria Común (PAC) que, entre otros aspectos, plantea el uso de imágenes del programa Copernicus para verificar que las declaraciones presentadas por los agricultores son correctas. En los últimos años distintas iniciativas investigadoras han tratado de desarrollar herramientas operativas con este fin, entre estas se encuentra el proyecto Interreg-POCTEFA PyrenEOS. En este artículo se expone la estrategia metodológica propuesta en el proyecto PyrenEOS, que se basa en la identificación del cultivo más probable utilizando el algoritmo Random Forests. Como elemento diferenciador, se propone seleccionar la muestra de entrenamiento a partir de una selección de las declaraciones PAC según su NDVI. Además, se definen una serie de reglas para determinar el grado de incertidumbre en la clasificación y los criterios para categorizar cada recinto del mapa de verificación según un código de colores a modo de semáforo, en el que el verde indica recintos con declaración correcta, el rojo recintos con declaración dudosa y el naranja recintos con una incertidumbre alta en la clasificación. Esta estrategia de verificación se aplica a dos Comarcas Agrarias de Navarra, en una campaña agrícola para la que se contó con inspecciones de campo de aproximadamente el 7% de los recintos declarados. Los resultados de esta validación, con fiabilidades globales en la clasificación próximas al 80% cuando se considera el cultivo más probable predicho por el clasificador y al 90% cuando se consideran los dos cultivos más probables, ponen de manifiesto que es posible identificar los recintos correctamente declarados (recintos verdes) con una tasa de error inferior al 1%. Los recintos naranjas y rojos, que requerirán del análisis y juicio posterior de técnicos de inspección, suponen un porcentaje reducido de las declaraciones (~6% de los recintos) y concentran la mayoría de las declaraciones incorrectas.