1,720,987 research outputs found
Statistical Exploration of SENTINEL-1 Data, Terrain Parameters, and in-situ Data for Estimating the Near-Surface Soil Moisture in a Mediterranean Agroecosystem
Full text linkReliable near-surface soil moisture (θ) information is crucial for supporting risk assessment of future water usage, particularly considering the vulnerability of agroforestry systems of Mediterranean environments to climate change. We propose a simple empirical model by integrating dual-polarimetric Sentinel-1 (S1) Synthetic Aperture Radar (SAR) C-band single-look complex data and topographic information together with in-situ measurements of θ into a random forest (RF) regression approach (10-fold cross-validation). Firstly, we compare two RF models' estimation performances using either 43 SAR parameters (θNovSAR) or the combination of 43 SAR and 10 terrain parameters (θNovSAR+Terrain). Secondly, we analyze the essential parameters in estimating and mapping θ for S1 overpasses twice a day (at 5 a.m. and 5 p.m.) in a high spatiotemporal (17 × 17 m; 6 days) resolution. The developed site-specific calibration-dependent model was tested for a short period in November 2018 in a field-scale agroforestry environment belonging to the “Alento” hydrological observatory in southern Italy. Our results show that the combined SAR + terrain model slightly outperforms the SAR-based model (θNovSAR+Terrain with 0.025 and 0.020 m3 m−3, and 89% compared to θNovSAR with 0.028 and 0.022 m3 m−3, and 86% in terms of RMSE, MAE, and R2). The higher explanatory power for θNovSAR+Terrain is assessed with time-variant SAR phase information-dependent elements of the C2 covariance and Kennaugh matrix (i.e., K1, K6, and K1S) and with local (e.g., altitude above channel network) and compound topographic attributes (e.g., wetness index). Our proposed methodological approach constitutes a simple empirical model aiming at estimating θ for rapid surveys with high accuracy. It emphasizes potentials for further improvement (e.g., higher spatiotemporal coverage of ground-truthing) by identifying differences of SAR measurements between S1 overpasses in the morning and afternoon
Temperature-Corrected Calibration of GS3 and TEROS-12 Soil Water Content Sensors
No full textThe continuous monitoring of soil water content is commonly carried out using low-frequency capacitance sensors that require a site-specific calibration to relate sensor readings to apparent dielectric bulk permittivity (Kb) and soil water content (θ). In fine-textured soils, the conversion of Kb to θ is still challenging due to temperature effects on the bound water fraction associated with clay mineral surfaces, which is disregarded in factory calibrations. Here, a multi-point calibration approach accounts for temperature effects on two soils with medium to high clay content. A calibration strategy was developed using repacked soil samples in which the Kb-θ relationship was determined for temperature (T) steps from 10 to 40 °C. This approach was tested using the GS3 and TEROS-12 sensors (METER Group, Inc. Pullman, WA, USA; formerly Decagon Devices). Kb is influenced by T in both soils with contrasting T-Kb relationships. The measured data were fitted using a linear function θ = aKb + b with temperature-dependent coefficients a and b. The slope, a(T), and intercept, b(T), of the loam soil were different from the ones of the clay soil. The consideration of a temperature correction resulted in low RMSE values, ranging from 0.007 to 0.033 cm3 cm−3, which were lower than the RMSE values obtained from factory calibration (0.046 to 0.11 cm3 cm−3). However, each experiment was replicated only twice using two different sensors. Sensor-to-sensor variability effects were thus ignored in this study and will be systematically investigated in a future study. Finally, the applicability of the proposed calibration method was tested at two experimental sites. The spatial-average θ from a network of GS3 sensors based on the new calibration fairly agreed with the independent area-wide θ from the Cosmic Ray Neutron Sensor (CRNS). This study provided a temperature-corrected calibration to increase the accuracy of commercial sensors, especially under dry conditions, at two experimental sites
Mapping near-surface soil moisture in a Mediterranean agroforestry ecosystem using Cosmic-Ray Neutron Probe and Sentinel-1 Data
No full textAccurate near-surface soil moisture (; ~ 5 cm) estimation is one of the most crucial challenges in agricultural management and hydrological studies. This study aims to
map at high spatiotemporal resolution (17 m grid size, satellite overpass of 6 days) in a small-scale agroforestry experimental site (~ 30 ha) in southern Italy. The observation period is from November 2018 until March 2019. We employed an ensemble machine-learning method based on Random Forest (RF) to map . This RF method is based on three input data types: i) Sentinel-1 (S1) Synthetic Aperture Radar (SAR) measurements, ii) terrain features, and iii) supporting values of sparse point-scale simulated in HYDRUS-1D. We propose two different approaches to obtain supporting simulations via inverse modeling in HYDRUS-1D. The first approach is based on simulated in HYDRUS-1D, which was calibrated on soil moisture data monitored at two soil depths of 15 cm and 30 cm over 20 positions belonging to the SoilNet wireless sensor network installed in the experimental site. The second approach is based on the downscaling of field-scale simulated in HYDRUS-1D which was calibrated on Cosmic-Ray Neutron Probe (CRNP) data. The field-scale was downscaled in order to obtain sparse point-scale supporting over the same 20 positions by using the physical-empirical Equilibrium Moisture from Topography (EMT) model. The CRNP-based approach performed similarly to the one based on SoilNet data.
Therefore, this study highlights the enormous potential for
modeling reliable maps by integrating soft data such as S1
SAR-based measurements, topographic information, and
CRNP data, having the advantage of being non-invasive and
easy to maintain
Integrating invasive and non-invasive monitoring sensors to detect field-scale soil hydrological behavior.
No full textIn recent decades, while great emphasis has been given to the monitoring of point-scale soil moisture patterns and field-scale integrated soil moisture, the measurement of matric potential has attracted little attention. Information on the soil matric potential is available in point-scale measurements but is still missing at field-scale. This state variable is necessary to understand hydrological fluxes and to determine the soil water retention function (WRF) for field-scale applications. In this study, we combine data from cosmic-ray neutron probes (CRNP, non-invasive proximal soil moisture sensors) and SoilNet wireless sensor networks (invasive ground-based soil moisture and matric potential sensors) installed in two sub-catchments with contrasting land-use (agroforestry vs. near-natural forest) to derive a field-scale WRF. We investigate the hypothesis that both sensor types provide effective measurements that are representative for the entire sub-catchment, as well as the drawbacks of integrating the different measurement scales of the sensor types (i.e., spatial-mean of distributed point-scale data vs. an integrated field-scale measurement). We found discrepancies in the data of the two sensor types related to the effects of the time-varying vertical measurement footprint of the CRNP, which induces a scale mismatch between CRNP-based soil moisture (referring mostly to near-surface depths) and the spatially averaged soil matric potential data measured at soil depths of 0.15 and 0.30 m. To remove the offsets, we opted to use the soil moisture index (SMI) based on the estimation of field capacity and wilting point, retrieved from the knowledge of the field-scale WRF. We found that the bimodality of SMI calculated with SoilNet-based soil moisture induced by Mediterranean rainfall seasonal behavior is not well-captured by CRNP-based soil moisture, except in a particularly dry year like 2017. The contrasts in SMI values between the two test sites were associated with differences in the spatial variability of soil moisture patterns explained by soil texture or terrain characteristics. We argue that field-scale WRFs are useful for the analysis of hydrological processes at the sub-catchment (field) scale and the application of distributed models
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Significance of scale and lower boundary condition in the 3D simulation of hydrological processes and soil moisture variability in a forested headwater catchment
No full textThe measurement and simulation of soil moisture patterns and their spatio-temporal variability are current challenges in hydrology. This study investigated the capability of the three-dimensional model HydroGeoSphere to simulate hydrological processes, soil moisture dynamics and patterns at 25 and 100 m resolutions with daily and hourly time steps in a forested headwater catchment. All simulations reproduced discharge dynamics well, calculated a dominance of the baseflow component but missed macropore driven discharge peaks in the summer and slightly overestimated the discharge. A comparison of discharge and water balance results between daily and hourly time steps revealed considerable scaling issues of saturated conductivity values and in the model’s interception module. Temporally and spatially highly resolved soil moisture measurements were used to calibrate residual saturations and porosities at daily time steps. Therefore, all model setups simulated the long-term temporal soil moisture dynamics well, but short-term soil moisture dynamics were poorly simulated because the simulation did not take into account the effect of macropore flow. The spatial soil moisture patterns of the topsoil were well reproduced except for certain parts in the western part of the catchment. A correlation analysis revealed that the influence of the topography was overestimated in the simulated soil moisture pattern. The spatial scale dependency of all aforementioned results was small due to independent calibration. The consideration of bedrock damped discharge peaks, increased low flow and slightly improved temporal soil moisture simulation
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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