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
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 Publikoa
A 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.
Open Access
On the influence of acquisition geometry in backscatter time series over wheat
(Elsevier, 2022) Arias Cuenca, María; Campo-Bescós, Miguel; Álvarez-Mozos, Jesús; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ingeniería; Gobierno de Navarra / Nafarroako Gobernua
Dense time series of Sentinel-1 imagery are an invaluable information source for agricultural applications. Multiple orbits can observe a specific area and their combination could improve the temporal resolution of the time series. However, the orbits have different acquisition geometries regarding incidence and azimuth angles that need to be considered. Furthermore, crops are dynamic canopies and the influence of incidence and azimuth angles might change during the agricultural season due to different phenological stages. The main objective of this letter is to evaluate the influence of different acquisition geometries in Sentinel-1 backscatter time series over wheat canopies, and to propose a strategy for their correction. A large dataset of wheat parcels (∼40,000) was used and 344 Sentinel-1 images from three relative orbits were processed during two agricultural seasons. The first analysis was a monthly evaluation of the influence of incidence angle on backscatter (σ0) and terrain flattened backscatter (γ0). It showed that terrain flattening significantly reduced the backscatter dependence on incidence angle, being negligible in VH polarization but not completely in VV polarization. Incidence angle influence in VV backscatter changed in time due to wheat growth dynamics. To further reduce it, an incidence angle normalization technique followed by an azimuthal anisotropy correction were applied. In conclusion, γ0 enabled a reasonable combination of different relative orbits, that may be sufficient for many applications. However, for detailed analyses, the correction techniques might be implemented to further reduce orbit differences, especially in bare soil periods or winter months.
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
Effects of spatial sampling interval on roughness parameters and microwave backscatter over agricultural soil surfaces
(MDPI, 2016) Barber, Matías Ernesto; Grings, Francisco Matías; Álvarez-Mozos, Jesús; Piscitelli, Marcela; Perna, Pablo Alejandro; Karszenbaum, Haydee; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
The spatial sampling interval, as related to the ability to digitize a soil profile with a certain number of features per unit length, depends on the profiling technique itself. From a variety of profiling techniques, roughness parameters are estimated at different sampling intervals. Since soil profiles have continuous spectral components, it is clear that roughness parameters are influenced by the sampling interval of the measurement device employed. In this work, we contributed to answer which sampling interval the profiles needed to be measured at to accurately account for the microwave response of agricultural surfaces. For this purpose, a 2-D laser profiler was built and used to measure surface soil roughness at field scale over agricultural sites in Argentina. Sampling intervals ranged from large (50 mm) to small ones (1 mm), with several intermediate values. Large- and intermediate-sampling-interval profiles were synthetically derived from nominal, 1 mm ones. With these data, the effect of sampling-interval-dependent roughness parameters on backscatter response was assessed using the theoretical backscatter model IEM2M. Simulations demonstrated that variations of roughness parameters depended on the working wavelength and was less important at L-band than at C- or X-band. In any case, an underestimation of the backscattering coefficient of about 1-4 dB was observed at larger sampling intervals. As a general rule a sampling interval of 15 mm can be recommended for L-band and 5 mm for C-band.
Open 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.
Open Access
Crop classification based on temporal signatures of Sentinel-1 observations over Navarre province, Spain
(MDPI, 2020) Arias Cuenca, María; Campo-Bescós, Miguel; Álvarez-Mozos, Jesús; Ingeniería; Ingeniaritza
Crop classification provides relevant information for crop management, food security assurance and agricultural policy design. The availability of Sentinel-1 image time series, with a very short revisit time and high spatial resolution, has great potential for crop classification in regions with pervasive cloud cover. Dense image time series enable the implementation of supervised crop classification schemes based on the comparison of the time series of the element to classify with the temporal signatures of the considered crops. The main objective of this study is to investigate the performance of a supervised crop classification approach based on crop temporal signatures obtained from Sentinel-1 time series in a challenging case study with a large number of crops and a high heterogeneity in terms of agro-climatic conditions and field sizes. The case study considered a large dataset on the Spanish province of Navarre in the framework of the verification of Common Agricultural Policy (CAP) subsidies. Navarre presents a large agro-climatic diversity with persistent cloud cover areas, and therefore, the technique was implemented both at the provincial and regional scale. In total, 14 crop classes were considered, including different winter crops, summer crops, permanent crops and fallow. Classification results varied depending on the set of input features considered, obtaining Overall Accuracies higher than 70% when the three (VH, VV and VH/VV) channels were used as the input. Crops exhibiting singularities in their temporal signatures were more easily identified, with barley, rice, corn and wheat achieving F1-scores above 75%. The size of fields severely affected classification performance, with ~14% better classification performance for larger fields (>1 ha) in comparison to smaller fields (<0.5 ha). Results improved when agro-climatic diversity was taken into account through regional stratification. It was observed that regions with a higher diversity of crop types, management techniques and a larger proportion of fallow fields obtained lower accuracies. The approach is simple and can be easily implemented operationally to aid CAP inspection procedures or for other purposes. © 2020 by the authors.
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
Accuracy of methods for field assessment of rill and ephemeral gully erosion
(Elsevier, 2006) Casalí Sarasíbar, Javier; Loizu Maeztu, Javier; Campo-Bescós, Miguel; Santisteban Comino, Luisa María de; Álvarez-Mozos, Jesús; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
To properly assess soil erosion in agricultural areas, it is necessary to determine precisely the volume of ephemeral gullies and rills in the field by using direct measurement procedures. However, little information is available on the accuracy of the different methods used. The main purpose of this paper is to provide information for a suitable assessment of rill and ephemeral gully erosion with such direct measurement methods. To achieve this objective: a) the measurement errors associated to three methods used for field assessment of channel cross sectional areas are explored; b) the influence of the number of cross sections used per unit channel length on the assessment accuracy, is analysed and; c) the effect of the channel size and shape on measurement errors is examined. The three methods considered to determine the cross sectional areas were: micro-topographic profile meter (1); detailed measurement of section characteristic lengths with a tape (2); measurement of cross section width and depth with a tape (3). Five reaches of different ephemeral gully types 14.0 or 30.0 m long and a set of six 20.4 to 29.4 m long rill reaches were selected. On each gully reach, the cross sectional areas were measured using the three above mentioned methods, with a separation (s) between cross sections of 1 m. For rills, the cross sectional areas were measured with methods 1 and 3, with s= 2 m. Then, the corresponding total erosion volumes were computed. The volume calculated with method 1 with s= 1 m for gullies and s= 2 m for rills was taken as the reference method. For each channel, and for each one of the possible combinations of s and measurement method (m), the relative measurement error and the absolute value of the relative measurement error (Ersm and |Ersm| ), defined with respect to the reference one, was calculated. |Ersm| much higher than 10% were obtained very easily, even for small s values and for apparently quasi prismatic channels. Channel size and shape had a great influence on measurement errors. In fact, the selection of the more suitable method for a certain gully shape and size seemed to be much more important than s, at least when s< 10 m. Method 1 always provided the most precise measurements, and its results were the less dependent on s. However, s must be <5 m to guarantee an error smaller than 10%. Method 2 is not recommended, because it is difficult, time consuming and can lead to large errors. Method 3 seems to be enough for small, wide and shallow gullies, and for small rills, but only if s is shorter than 5 m. Results obtained after the analysis of rill measurement errors were similar to those of gullies. The analysis of Ersm and |Ersm| when calculating channel volumes using a unique representative cross section highlighted the importance of correctly selecting the adequate cross section. Due to the high error values that this method can entail, it is not considered as advisable whenever accurate erosion measurements are pursued.
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 Proiektuak
Radar-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.