Open Access
Inter-comparison of atmospheric correction methods on Sentinel-2 images applied to croplands
(IEEE, 2018) Sola Torralba, Ion; Álvarez-Mozos, Jesús; González de Audícana Amenábar, María; Ingeniería; Ingeniaritza
Atmospheric correction of high resolution satellite scenery is a necessary preprocessing step for applications where bottom of atmosphere (BOA) reflectances are needed. The selection of the best atmospheric correction method to use on images acquired from new platforms, such as Sentinel-2, is essential to provide accurate BOA reflectances. In this work the performance of three atmospheric correction methods (6S, MAJA and SEN2COR) applied to Sentinel-2 scenes are compared by evaluating the resultant spectral signatures of six crop types on two specific dates, and their NDVI time series along a complete year. Although SEN2COR introduced greater corrections, especially in the infrared bands, the results suggest a varying performance of the methods depending on the land cover and the atmospheric conditions. Further research, particularly incorporating ground truth data, is recommended to rigorously validate the different atmospheric methods.
Open Access
Multi-criteria evaluation of topographic correction methods
(Elsevier, 2016) Sola Torralba, Ion; González de Audícana Amenábar, María; Álvarez-Mozos, Jesús; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
In the last decades, several topographic correction methods (TOC) have been proposed, but there is not an agreement on the best method. Furthermore, different evaluation criteria have been used in the past, and there is not any simple and objective evaluation procedure to measure the quality of the correction. Consequently, a multicriteria analysis of widely used topographic correction methods is required that evaluates their performance over different sensors, terrain and temporal configurations. In this work, ten TOC methods were assessed using seven different evaluation strategies. The analysis was carried out for three SPOT5 images acquired over a mountainous area of northern Spain. The images had different acquisition dates and solar angles, so as to evaluate performance under varying illumination conditions. The results obtained showed that Statistic-Empiricalmethod, CCorrection and Sun-Canopy-Sensor+C performed the best, and differences were minor when favorable illumination conditions were considered. For the seven tested evaluation strategies, interquartile range reduction of land covers or the comparison of sunlit and shaded slopes gave very similar results, whereas there were greater contrasts among other criteria.
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 Proiektuak
Polarimetric 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.
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
Influence of surface roughness sample size for C-band SAR backscatter applications on agricultural soils
(IEEE, 2017) Martínez de Aguirre Escobar, Alejandro; Álvarez-Mozos, Jesús; Lievens, Hans; Verhoest, Niko E. C.; Giménez Díaz, Rafael; Landa Ingeniaritza eta Proiektuak; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Proyectos e Ingeniería Rural
Soil surface roughness determines the backscatter coefficient observed by radar sensors. The objective of this letter was to determine the surface roughness sample size required in synthetic aperture radar applications and to provide some guidelines on roughness characterization in agricultural soils for these applications. With this aim, a data set consisting of ten ENVISAT/ASAR observations acquired coinciding with soil moisture and surface roughness surveys has been processed. The analysis consisted of: 1) assessing the accuracies of roughness parameters s and l depending on the number of 1-m-long profiles measured per field; 2) computing the correlation of field average roughness parameters with backscatter observations; and 3) evaluating the goodness of fit of three widely used backscatter models, i.e., integral equation model (IEM), geometrical optics model (GOM), and Oh model. The results obtained illustrate a different behavior of the two roughness parameters. A minimum of 10-15 profiles can be considered sufficient for an accurate determination of s, while 20 profiles might still be not enough for accurately estimating l. The correlation analysis revealed a clear sensitivity of backscatter to surface roughness. For sample sizes >15 profiles, R values were as high as 0.6 for s and ~0.35 for l, while for smaller sample sizes R values dropped significantly. Similar results were obtained when applying the backscatter models, with enhanced model precision for larger sample sizes. However, IEM and GOM results were poorer than those obtained with the Oh model and more affected by lower sample sizes, probably due to larger uncertainly of l.
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
Assessment of atmospheric correction methods for Sentinel-2 images in Mediterranean landscapes
(Elsevier, 2018) Sola Torralba, Ion; García-Martín, Alberto; Sandonís Pozo, Leire; Álvarez-Mozos, Jesús; González de Audícana Amenábar, María; Ingeniería; Ingeniaritza
Atmospheric correction of optical satellite imagery is an essential pre-processing for modelling biophysical variables, multi-temporal analysis, and digital classification processes. Sentinel-2 products available for users are distributed by the European Space Agency (ESA) as Top Of Atmosphere reflectance values in cartographic geometry (Level-1C product). In order to obtain Bottom Of Atmosphere reflectance images (Level-2A product) derived from this Level-1C products, ESA provides the SEN2COR module, which is implemented in the Sentinel Application Platform. Alternatively, ESA recently distributes Level-2A products processed by SEN2COR with a default configuration. On the other hand, the conversion from Level-1C to Level-2A product can be generated using alternative atmospheric correction methods, such as MAJA, 6S, or iCOR. In this context, this paper aims to evaluate the quality of Level-2A products obtained through different methods in Mediterranean shrub and grasslands by comparing data obtained from Sentinel-2 imagery with field spectrometry data. For that purpose, six plots with different land covers (asphalt, grass, shrub, pasture, and bare soil) were analyzed, by using synchronous imagery to fieldwork (from July to September 2016). The results suggest the suitability of the applied atmospheric corrections, with coefficients of determination higher than 0.90 and root mean square error lower than 0.04 achieving a relative error in bottom of atmosphere reflectance of only 2–3%. Nevertheless, minor differences were observed between the four tested methods, with slightly varying results depending on the spectral band and land cover.
Open Access
Influence of surface roughness measurement scale on radar backscattering in different agricultural soils
(IEEE, 2017) Martínez de Aguirre Escobar, Alejandro; Álvarez-Mozos, Jesús; Lievens, Hans; Verhoest, Niko E. C.; Landa Ingeniaritza eta Proiektuak; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Proyectos e Ingeniería Rural
Soil surface roughness strongly affects the scattering of microwaves on the soil surface and determines the backscattering coefficient (σ 0 ) observed by radar sensors. Previous studies have shown important scale issues that compromise the measurement and parameterization of roughness especially in agricultural soils. The objective of this paper was to determine the roughness scales involved in the backscattering process over agricultural soils. With this aim, a database of 132 5-m profiles taken on agricultural soils with different tillage conditions was used. These measurements were acquired coinciding with a series of ENVISAT/ASAR observations. Roughness profiles were processed considering three different scaling issues: 1) influence of measurement range; 2) influence of low-frequency roughness components; and 3) influence of high-frequency roughness components. For each of these issues, eight different roughness parameters were computed and the following aspects were evaluated: 1) roughness parameters values; 2) correlation with σ 0 ; and 3) goodness-of-fit of the Oh model. Most parameters had a significant correlation with σ 0 especially the fractal dimension, the peak frequency, and the initial slope of the autocorrelation function. These parameters had higher correlations than classical parameters such as the standard deviation of surface heights or the correlation length. Very small differences were observed when longer than 1-m profiles were used as well as when small-scale roughness components (<;5 cm) or large-scale roughness components (>100 cm) were disregarded. In conclusion, the medium-frequency roughness components (scale of 5-100 cm) seem to be the most influential scales in the radar backscattering process on agricultural soils.
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 Proiektuak
Navarra 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.
Open Access
Factors controlling sediment export in a small agricultural watershed in Navarre (Spain)
(Elsevier, 2012) Giménez Díaz, Rafael; Casalí Sarasíbar, Javier; Grande Esteban, Ildefonso; Díez Beregaña, Javier; Campo-Bescós, Miguel; Álvarez-Mozos, Jesús; Goñi Garatea, Mikel; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak; Gestión de Empresas; Enpresen Kudeaketa; Gobierno de Navarra / Nafarroako Gobernua
It is recognised that the hydrological and erosion processes in watersheds are very much conditioned by the (inter)action of a number of variables. This paper covers a 15-year period of studying those factors that have a major influence on the sediment yield and transport during individual hydrological events in a small Mediterranean agricultural watershed. Multivariate statistical techniques such as cluster analysis and principal component analysis were applied for the interpretation of datasets. In addition, the relationships between suspended sediment concentration and discharge (hysteretic loops) were also analysed. The hydrological response of the studied watershed is mainly controlled by the antecedent condition of the flow. Most of the runoff and sediment are generated during the wet season when vegetation cover is scant and saturation overland flow occurs promptly as a response to almost any rainfall events. In contrast, during the dry seasons even if high-intensity rainfalls normally occur, very scant runoffs are, however recorded, at the exit of the watershed. Most of the eroded sediment seems to come from riparian areas. The discharge registered at the watershed outlet up to 1 h prior to the flood is a very good surrogate for antecedent soil moisture.