Person:
Martínez de Aguirre Escobar, Alejandro

Profile Picture

Email Address

person.page.identifierURI

https://academica-e.unavarra.es/handle/2454/49520

Birth Date

Research Projects

Organizational Units

Job Title

Last Name

Martínez de Aguirre Escobar

First Name

Alejandro

person.page.departamento

Proyectos e Ingeniería Rural

person.page.instituteName

ORCID

0000-0002-7151-8419

person.page.upna

811010

Name

Filters

2016 - 20208
Reset filters

Settings

Search Results

Now showing 1 - 8 of 8
  • Thumbnail Image
    PublicationOpen Access
    Evaluation of surface roughness parameters in agricultural soils with different tillage conditions using a laser profile meter
    (Elsevier, 2016) Martínez de Aguirre Escobar, Alejandro; Álvarez Mozos, Jesús; Giménez Díaz, Rafael; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
    Surface roughness crucially affects the hydrological and erosive behaviours of soils. In agricultural areas surface roughness is directly related to tillage, whose action strongly affects the key physical properties of soils and determines the occurrence and fate of several processes (e.g., surface storage, infiltration, etc.). The characterisation of surface roughness as a result of tillage operations is not straightforward, and numerous parameters and indices have been proposed for quantifying it. In this article, a database of 164 profiles (each 5 m long), measured in 5 different roughness classes, was analysed. Four roughness classes corresponded to typical tillage operations (i.e., mouldboard, harrow, seedbed, etc.), and the fifth represented a seedbed soil that was subject to rainfall. The aim of the research was to evaluate and select the surface roughness parameters that best characterised and quantified the surface roughness caused by typical tillage operations. In total, 21 roughness parameters (divided into 4 categories) were assessed. The parameters that best separated and characterised the different roughness classes were the limiting elevation difference (LD) and the Mean Upslope Depression index (MUD); however, the parameters most sensitive to rainfall action on seedbed soils were limiting slope (LS) and the crossover lengths measured with the semivariogram method (lSMV) and the root mean square method (lRMS). Many parameters had high degrees of correlation with each other, and therefore gave almost identical information. The results of this study may contribute to the understanding of the surface roughness phenomenon and its parameterisation in agricultural soils.
  • Thumbnail Image
    PublicationOpen 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.
  • Thumbnail Image
    PublicationOpen 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.
  • Thumbnail Image
    PublicationOpen Access
    On the influence of spatial resolution in soil surface roughness characterization using Tls and Sfm techniques
    (IEEE, 2018) Martínez de Aguirre Escobar, Alejandro; Álvarez Mozos, Jesús; Giménez Díaz, Rafael; Milenković, Milutin; Pfeifer, Norbert; Ingeniería; Ingeniaritza
    Soil surface roughness strongly affects the scattering of microwaves and determines the backscattering coefficient observed by SAR (Synthetic Aperture Radar) sensors. The aim of this study is to analyze the influence of the spatial resolution of Terrestrial Laser Scanner (TLS) and Structure from Motion (SfM) techniques to parameterize surface roughness over agricultural soils. Three experimental plots (5 x 5 meters) representing different roughness conditions were measured by TLS and SfM techniques. Roughness parameters (s and l) were calculated from profiles obtained at different spatial resolutions in parallel and in perpendicular to the tillage direction on each plot. The results showed minor differences in the parameters values between both techniques and, in general, a decreasing trend and an increasing trend for lower spatial resolutions for parameter s and l, respectively.
  • Thumbnail Image
    PublicationOpen Access
    Evaluation of terrestrial laser scanner and structure from motion photogrammetry techniques for quantifying soil surface roughness parameters over agricultural soils
    (Wiley, 2020) Martínez de Aguirre Escobar, Alejandro; Álvarez Mozos, Jesús; Milenković, Milutin; Pfeifer, Norbert; Giménez Díaz, Rafael; Ingeniería; Ingeniaritza
    The surface roughness of agricultural soils is mainly related to the type of tillage performed, typically consisting of oriented and random components. Traditionally, soil surface roughness (SSR) characterization has been difficult due to its high spatial variability and the sensitivity of roughness parameters to the characteristics of the instruments, including its measurement scale. Recent advances in surveying have greatly improved the spatial resolution, extent, and availability of surface elevation datasets. However, it is still unknown how new roughness measurements relates with the conventional roughness measurements such as 2D profiles acquired by laser profilometers. The objective of this study was to evaluate the suitability of Terrestrial Laser Scanner (TLS) and Structure from Motion (SfM) photogrammetry techniques for quantifying SSR over different agricultural soils. With this aim, an experiment was carried out in three plots (5 × 5 m) representing different roughness conditions, where TLS and SfM photogrammetry measurements were co‐registered with 2D profiles obtained using a laser profilometer. Differences between new and conventional roughness measurement techniques were evaluated visually and quantitatively using regression analysis and comparing the values of six different roughness parameters. TLS and SfM photogrammetry measurements were further compared by evaluating multi‐directional roughness parameters and analyzing corresponding Digital Elevation Models. The results obtained demonstrate the ability of both TLS and SfM photogrammetry techniques to measure 3D SSR over agricultural soils. However, profiles obtained with both techniques (especially SfM photogrammetry) showed a loss of high‐frequency elevation information that affected the values of some parameters (e.g. initial slope of the autocorrelation function, peak frequency and tortuosity). Nevertheless, both TLS and SfM photogrammetry provide a massive amount of 3D information that enables a detailed analysis of surface roughness, which is relevant for multiple applications, such as those focused in hydrological and soil erosion processes and microwave scattering.
  • Thumbnail Image
    PublicationOpen Access
    Analysis of surface roughness in agricultural soils using in-situ measurements and remote sensing techniques
    (2017) Martínez de Aguirre Escobar, Alejandro; Álvarez-Mozos, Jesús; Giménez Díaz, Rafael; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
    El término rugosidad superficial del suelo es utilizado para describir las variaciones de elevación de la superficie del suelo (micro-relieve). La rugosidad afecta diferentes procesos hidrológicos importantes como el almacenamiento superficial, la infiltración, la escorrentía y la erosión del suelo. Al mismo tiempo, la rugosidad superficial también afecta la retrodispersión de las microondas en la superficie del suelo y determina el coeficiente de retrodispersión observado por los sensores radar. Debido a esto, su caracterización y cuantificación es relevante en diferentes áreas científicas. Sin embargo, el conocimiento actual sobre esta cuestión está lejos de ser completo y aceptado universalmente. Además, el micro-relieve natural de los suelos agrícolas puede verse afectado también de muy diferentes maneras por la acción del laboreo. En esta tesis doctoral, se ha llevado a cabo experimentación en suelos agrícolas afectados por diferentes tipos de tratamientos de laboreo, persiguiendo los siguientes objetivos: (i) La evaluación y caracterización de diferentes parámetros de rugosidad. (ii) El análisis de la influencia de la escala de medida de la rugosidad en la retrodispersión radar. (iii) El análisis de la influencia del tamaño de la muestra de rugosidad en la retrodispersión radar. (iv) La evaluación de las técnicas de Laser Escáner Terrestre y la denominada “Structure from Motion” para cuantificar la rugosidad superficial. Con todo ello, se espera que esta tesis doctoral contribuya a un mejor entendimiento del fenómeno de la rugosidad superficial del suelo y su caracterización en suelos agrícolas.
  • Thumbnail Image
    PublicationOpen Access
    Evaluation of 2D models for the prediction of surface depression storage using realistic reference values
    (Wiley, 2016) Giménez Díaz, Rafael; Mezkiritz Barberena, Irantzu; Campo-Bescós, Miguel; Álvarez Mozos, Jesús; González de Audícana Amenábar, María; Martínez de Aguirre Escobar, Alejandro; Casalí Sarasíbar, Javier; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
    Depression storage (DS) is the maximum storage of precipitation and runoff in the soil surface at a given slope. The DS is determined by soil roughness that in agricultural soils is largely affected by tillage. The direct measurement of DS is not straightforward because of the natural permeability of the soil. Therefore, DS has generally been estimated from 2D/3D empirical relationships and numerical algorithms based on roughness indexes and height measurements of the soil surface, respectively. The objective of this work was to evaluate the performance of some 2D models for DS, using direct and reliable measurements of DS in an agricultural soil as reference values. The study was carried out in experimental microplots where DS was measured in six situations resulting from the combination of three types of tillage carried out parallel and perpendicular to the main slope. Those data were used as reference to evaluate four empirical models and a numerical method. Longitudinal altitudinal profiles of the relief were obtained by a laser profilometer. Infiltration measurements were carried out before and after tillage. The DS was largely affected by tillage and its direction. Highest values of DS are found on rougher surfaces mainly when macroforms cut off the dominant slope. The empirical models had a limited performance while the numerical method was the most effective, even so, with an important variability. In addition, a correct hydrological management should take into account that each type of soil tillage affects infiltration rate differently.
  • Thumbnail Image
    PublicationOpen Access
    Comparison of digital terrain models obtained with LiDAR and photogrammetry
    (Springer, 2020) Martínez de Aguirre Escobar, Alejandro; García Morales, Víctor; Álvarez Mozos, Jesús; Ingeniería; Ingeniaritza
    Airborne LiDAR sensors capture three-dimensional information of the Earth, useful for obtaining high accuracy Digital Terrain Models (DTM). The Spanish National Plan for Aerial Orthophotography (PNOA) is an initiative of the Spanish Geographical Institute whereby nationwide LiDAR datasets are periodically acquired and made available to the public as.las files and value added products (e.g., DTM). The objective of this study is to assess the added value of PNOA LiDAR DTMs by comparing them to DTMs obtained through classical photogrammetric techniques. With this aim, four areas of interest were selected in Navarre (north of Spain), in areas with challenging characteristics such as forests, karst landforms, agricultural terraces and ravines. A 5 × 5 m DTM obtained with classical photogrammetry in 2008 was compared with a LiDAR DTM of the same pixel size obtained in 2011, assuming no significant changes occurred in this time. Height differences were evaluated, as well as slope, aspect and curvature differences. Besides, a multiresolution analysis was carried out to quantify how DTM smoothing affected height variations between neighbor pixels, measured with the standard deviation on a 5 × 5 window. The results obtained showed that the LiDAR DTMs provided an enhanced description of topography, particularly under forests and in areas with complex topography.