Larrañaga Urien, Arantzazu
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Larrañaga Urien
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Arantzazu
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Proyectos e Ingeniería Rural
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Publication Open Access On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imagery(MDPI, 2016) Larrañaga Urien, Arantzazu; Álvarez-Mozos, Jesús; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta ProiektuakPolarimetric SAR images are a rich data source for crop mapping. However, quad-pol sensors have some limitations due to their complexity, increased data rate, and reduced coverage and revisit time. The main objective of this study was to evaluate the added value of quad-pol data in a multi-temporal crop classification framework based on SAR imagery. With this aim, three RADARSAT-2 scenes were acquired between May and June 2010. Once we analyzed the separability and the descriptive analysis of the features, an object-based supervised classification was performed using the Random Forests classification algorithm. Classification results obtained with dual-pol (VV-VH) data as input were compared to those using quad-pol data in different polarization bases (linear H-V, circular, and linear 45º), and also to configurations where several polarimetric features (Pauli and Cloude–Pottier decomposition features and co-pol coherence and phase difference) were added. Dual-pol data obtained satisfactory results, equal to those obtained with quad-pol data (in H-V basis) in terms of overall accuracy (0.79) and Kappa values (0.69). Quad-pol data in circular and linear 45º bases resulted in lower accuracies. The inclusion of polarimetric features, particularly co-pol coherence and phase difference, resulted in enhanced classification accuracies with an overall accuracy of 0.86 and Kappa of 0.79 in the best case, when all the polarimetric features were added. Improvements were also observed in the identification of some particular crops, but major crops like cereals, rapeseed, and sunflower already achieved a satisfactory accuracy with the VV-VH dual-pol configuration and obtained only minor improvements. Therefore, it can be concluded that C-band VV-VH dual-pol data is almost ready to be used operationally for crop mapping as long as at least three acquisitions in dates reflecting key growth stages representing typical phenology differences of the present crops are available. In the near future, issues regarding the classification of crops with small field sizes and heterogeneous cover (i.e., fallow and grasslands) need to be tackled to make this application fully operational.Publication Open Access Influence of surface roughness spatial variability and temporal dynamics on the retrieval of soil moisture from SAR observations(MDPI, 2009) Álvarez-Mozos, Jesús; Verhoest, Niko E. C.; Larrañaga Urien, Arantzazu; Casalí Sarasíbar, Javier; González de Audícana Amenábar, María; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta ProiektuakRadar-based surface soil moisture retrieval has been subject of intense research during the last decades. However, several difficulties hamper the operational estimation of soil moisture based on currently available spaceborne sensors. The main difficulty experienced so far results from the strong influence of other surface characteristics, mainly roughness, on the backscattering coefficient, which hinders the soil moisture inversion. This is especially true for single configuration observations where the solution to the surface backscattering problem is ill-posed. Over agricultural areas cultivated with winter cereal crops, roughness can be assumed to remain constant along the growing cycle allowing the use of simplified approaches that facilitate the estimation of the moisture content of soils. However, the field scale spatial variability and temporal variations of roughness can introduce errors in the estimation of soil moisture that are difficult to evaluate. The objective of this study is to assess the impact of roughness spatial variability and roughness temporal variations on the retrieval of soil moisture from radar observations. A series of laser profilometer measurements were performed over several fields in an experimental watershed from September 2004 to March 2005. The influence of the observed roughness variability and its temporal variations on the retrieval of soil moisture is studied using simulations performed with the Integral Equation Model, considering different sensor configurations. Results show that both field scale roughness spatial variability and its temporal variations are aspects that need to be taken into account, since they can introduce large errors on the retrieved soil moisture values.Publication Open Access Clasificación de cultivos en la zona media de Navarra mediante imágenes radar polarimétricas(Universidad Politécnica de Valencia, 2010) Larrañaga Urien, Arantzazu; Albizua, Lourdes; Álvarez-Mozos, Jesús; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta ProiektuakNavarra lleva años empleando la técnica de clasificación supervisada de imágenes multiespectrales de satélite para la realización de la estadística agraria. La cubierta nubosa, muy habitual en esta zona, limita e incluso imposibilita el uso de imágenes ópticas para este fin. Los sensores radar representan una alternativa interesante, dado que a las longitudes de onda que trabajan, la cobertura nubosa es transparente, por lo que la nubosidad no supone ningún tipo de limitación para su empleo. Por otro lado, los sensores radar de nueva generación (por ejemplo ALOS/PALSAR o RADARSAT- 2), incorporan mejoras importantes respecto a sus predecesores (ERS-1/-2 o RADARSAT-1). En lo que respecta a la clasificación de cultivos, los sensores radar que adquieren imágenes en múltiples polarizaciones resultan especialmente interesantes. El principal objetivo de este trabajo es evaluar la viabilidad del empleo de observaciones de teledetección radar de polarización múltiple en la clasificación de cultivos de la zona media de Navarra. Para ello, se han utilizado dos imágenes ALOS/PALSAR. Una vez realizado un detallado análisis polarimétrico, se han obtenido las firmas o signaturas de los distintos cultivos de secano y de regadío por separado y se ha realizado una clasificación supervisada. La clasificación obtenida se ha comparado con la verdad campo resultando en un índice Kappa y fiabilidad global de 0,52 y 85% respectivamente.