González de Audícana Amenábar, María
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González de Audícana Amenábar
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María
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IS-FOOD. Research Institute on Innovation & Sustainable Development in Food Chain
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Publication 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 ProiektuakIn 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.Publication 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 ProiektuakLand 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.Publication Open Access Synthetic images for evaluating topographic correction algorithm(IEEE, 2013) Sola Torralba, Ion; González de Audícana Amenábar, María; Álvarez-Mozos, Jesús; Torres Escribano, José Luis; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak; Gobierno de Navarra / Nafarroako GobernuaIn the last years, many topographic correction (TOC) methods have been proposed to correct the illumination differences between the areas observed by optical remote sensors. Although the available number of TOC methods is high, the evaluation of their performance generally relies on the existence of precise land-cover information, and a standardized and objective evaluation procedure has not been proposed yet. In this paper, we propose an objective procedure to assess the accuracy of these TOC methods on the basis of simulated scenes, i.e., synthetically generated images. These images represent the radiance an optical sensor would receive under specific geometric and temporal acquisition conditions and assuming a certain land-cover type. A simplified method for creating synthetic images using the stateof- the-art irradiance models is proposed, both considering the real topography of a certain area [synthetic real (SR) image] or considering the relief of this area as being completely flat [synthetic horizontal image (SH)]. The comparison between the corrected image obtained by applying a TOC method to the SR and SH images of the same area, allows assessing the performance of each TOC algorithm. This comparison is quantitatively carried out using the structural similarity index. The proposed TOC evaluation procedure is applied to a specific case study in northern Spain to explain its implementation and demonstrate its potential. The procedure proposed in this paper could be also used to assess the behavior of TOC methods operating under different scenarios considering diverse topographic, geometrical, and temporal acquisition configurations.Publication Open Access Evaluación multitemporal de métodos de corrección topográfica mediante el uso de imágenes sintéticas multiespectrales(Asociación Española de Teledetección, 2014) Sola Torralba, Ion; Álvarez-Mozos, Jesús; González de Audícana Amenábar, María; Torres Escribano, José Luis; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta ProiektuakEn este trabajo se presentan los resultados de la evaluación multitemporal de varios métodos de corrección topográfica (TOC), cuya bondad se determina de forma cuantitativa mediante el uso de imágenes sintéticas multiespectrales simuladas para diferentes fechas de adquisición a lo largo del año. Para cada fecha se generan dos imágenes sintéticas, una considerando el relieve real (imagen SR), y otra el relieve horizontal (imagen SH). Las imágenes SR se corrigen utilizando distintos TOC y estas imágenes corregidas se comparan con la corrección ideal (imagen SH) mediante el índice de similitud estructural (SSIM). Los valores de SSIM nos permiten evaluar la eficacia de cada corrección para distintas fechas, es decir, para distintos ángulos de elevación solar.Publication Open Access The added value of stratified topographic correction of multispectral images(MDPI, 2016) Sola Torralba, Ion; González de Audícana Amenábar, María; Álvarez-Mozos, Jesús; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaSatellite images in mountainous areas are strongly affected by topography. Different studies demonstrated that the results of semi-empirical topographic correction algorithms improved when a stratification of land covers was carried out first. However, differences in the stratification strategies proposed and also in the evaluation of the results obtained make it unclear how to implement them. The objective of this study was to compare different stratification strategies with a non-stratified approach using several evaluation criteria. For that purpose, Statistic-Empirical and Sun-Canopy-Sensor + C algorithms were applied and six different stratification approaches, based on vegetation indices and land cover maps, were implemented and compared with the non-stratified traditional option. Overall, this study demonstrates that for this particular case study the six stratification approaches can give results similar to applying a traditional topographic correction with no previous stratification. Therefore, the non-stratified correction approach could potentially aid in removing the topographic effect, because it does not require any ancillary information and it is easier to implement in automatic image processing chains. The findings also suggest that the Statistic-Empirical method performs slightly better than the Sun-Canopy-Sensor + C correction, regardless of the stratification approach. In any case, further research is necessary to evaluate other stratification strategies and confirm these results.Publication Open Access Validation of a simplified model to generate multispectral synthetic images(MDPI, 2015) Sola Torralba, Ion; González de Audícana Amenábar, María; Álvarez-Mozos, Jesús; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaA new procedure to assess the quality of topographic correction (TOC) algorithms applied to remote sensing imagery was previously proposed by the authors. This procedure was based on a model that simulated synthetic scenes, representing the radiance an optical sensor would receive from an area under some specific conditions. TOC algorithms were then applied to synthetic scenes and the resulting corrected scenes were compared with a horizontal synthetic scene free of topographic effect. This comparison enabled an objective and quantitative evaluation of TOC algorithms. This approach showed promising results but had some shortcomings that are addressed herein. First, the model, originally built to simulate only broadband panchromatic scenes, is extended to multispectral scenes in the visible, near infrared (NIR), and short wave infrared (SWIR) bands. Next, the model is validated by comparing synthetic scenes with four Satellite pour l'Observation de la Terre 5 (SPOT5) real scenes acquired on different dates and different test areas along the Pyrenees mountain range (Spain). The results obtained show a successful simulation of all the spectral bands. Therefore, the model is deemed accurate enough for its purpose of evaluating TOC algorithms.Publication Open Access Desarrollo de productos avanzados para la misión SEOSAT/Ingenio(Universitat Politecnica de Valencia, 2016) Sabater, N.; Ruiz Verdú, A.; Delegido, J.; Fernández Beltrán, R.; Latorre Carmona, P.; Pla, F.; González de Audícana Amenábar, María; Álvarez-Mozos, Jesús; Sola Torralba, Ion; Villa, G.; Tejeiro, J. A.; Miguel, E. de; Jiménez, M.; Molina, S.; Moreno, J.; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta ProiektuakSEOSAT/Ingenio es la futura misión española de observación de la Tierra en el óptico en alta resolución espacial. Mientras que los productos de imagen a Nivel 1, radiancias geo-referenciadas a nivel de sensor, se encuentran en una fase avanzada de desarrollo existiendo para ello un contrato industrial, los productos de Nivel 2 deben ser desarrollados por los propios usuarios. Este hecho limita el uso de las imágenes a la comunidad científica, restringiendo sus posibles aplicaciones fuera de ésta. Así pues, bajo el marco de un proyecto coordinado y motivados por ofrecer productos de Ingenio/SEOSAT de Nivel 2 a disposición de cualquier usuario, se origina y desarrolla este trabajo. En este artículo se presentan los diferentes procesos desarrollados para la elaboración de productos a Nivel 2, desde reflectividades en superficie a la resolución nominal del sensor hasta imágenes con información espacial realzada y la posibilidad de crear mosaicos espaciales y compuestos temporales. Por una parte, en el caso de los productos de reflectividad en superficie se propone una técnica de corrección atmosférica basada en el uso de la información espacial, previo enmascaramiento de las nubes y una exhaustiva corrección de sombras morfológicas y/o topográficas. Por otra parte, para el realce de la información espacial, han sido evaluados diferentes métodos basados en la fusión de bandas multiespectrales con una banda pancromática así como la aplicación de técnicas llamadas de “Super-resolución”. Finalmente, se proporcionan las herramientas necesarias para la realización de mosaicos tanto espaciales como temporales para todo tipo de usuarios interesados en la explotación de las imágenes.