26 results on '"Jonard, Francois"'
Search Results
2. Modeling gross primary production and transpiration from sun-induced chlorophyll fluorescence using a mechanistic light-response approach
- Author
-
Beauclaire, Quentin, De Cannière, Simon, Jonard, François, Pezzetti, Natacha, Delhez, Laura, and Longdoz, Bernard
- Published
- 2024
- Full Text
- View/download PDF
3. Mapping and monitoring peatlands in the Belgian Hautes Fagnes: Insights from Ground-penetrating radar and Electromagnetic induction characterization
- Author
-
Henrion, Maud, Li, Yanfei, Koganti, Triven, Bechtold, Michel, Jonard, François, Opfergelt, Sophie, Vanacker, Veerle, Van Oost, Kristof, and Lambot, Sébastien
- Published
- 2024
- Full Text
- View/download PDF
4. Vegetation moisture estimation in the Western United States using radiometer-radar-lidar synergy
- Author
-
Chaparro, David, Jagdhuber, Thomas, Piles, María, Jonard, François, Fluhrer, Anke, Vall-llossera, Mercè, Camps, Adriano, López-Martínez, Carlos, Fernández-Morán, Roberto, Baur, Martin, Feldman, Andrew F., Fink, Anita, and Entekhabi, Dara
- Published
- 2024
- Full Text
- View/download PDF
5. Characterization of tillage effects on the spatial variation of soil properties using ground-penetrating radar and electromagnetic induction
- Author
-
Jonard, François, Mahmoudzadeh, Mohammad, Roisin, Christian, Weihermüller, Lutz, André, Frédéric, Minet, Julien, Vereecken, Harry, and Lambot, Sébastien
- Published
- 2013
- Full Text
- View/download PDF
6. Retrieving forest vegetation moisture content from a multi-sensor approach in the Western United States
- Author
-
Chaparro, David, Jagdhuber, Thomas, Piles, Maria, Jonard, Francois, Fluhrer, Anke, Vall-llossera, Mercè, Camps, Adriano, Lopez-Martinez, Carlos, Feldman, Andrew, Entekhabi, Dara, Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. CTE-CRAE - Grup de Recerca en Ciències i Tecnologies de l'Espai, and Universitat Politècnica de Catalunya. CommSensLab-UPC - Centre Específic de Recerca en Comunicació i Detecció UPC
- Subjects
forest ,Vegetation and climate ,vegetation moisture ,multi-sensor ,Vegetació i clima ,Enginyeria de la telecomunicació [Àrees temàtiques de la UPC] ,vegetation optical depth - Abstract
This work was supported by the “la Caixa” Foundation (ID 100010434) under Grant LCF/PR/MIT19/51840001 (MIT-Spain Seed Fund), by MISTI-Germany and MISTI-Belgium Seed Funds, by the XXXIII Ramón Areces Postdoctoral Fellowship, by the NASA (Grant 1510842), by grants PID2020-114623RB-C32 and MDM-2016-0600 funded by MCIN/AEI/10.13039/501100011033, by the European Regional Development Fund (ERDF), and by the NASA Postdoctoral Program at the NASA Goddard Space Flight Center. D. Chaparro thanks the AKS department (DLR) and the CEE department (MIT) for hosting and supervision.
- Published
- 2022
7. Toward estimation of seasonal water dynamics of winter wheat from ground-based L-band radiometry: a concept study
- Author
-
Jagdhuber, Thomas, Jonard, Francois, Fluhrer, Anke, Chaparro, David, Baur, Martin J., Meyer, Thomas, Piles, Maria, Ministerio de Ciencia e Innovación (España), European Commission, Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, and Universitat Politècnica de Catalunya. CTE-CRAE - Grup de Recerca en Ciències i Tecnologies de l'Espai
- Subjects
Teledetecció ,Vegetation water potential ,radiometry ,Remote sensing ,Enginyeria de la telecomunicació [Àrees temàtiques de la UPC] ,winter wheat ,water fluxes ,L-band ,Plant water uptake ,ddc:550 ,ground-based ,L-band radiometry ,Vegetation optical depth ,SMOS - Abstract
The vegetation optical depth (VOD) variable contains information on plant water content and biomass. It can be estimated alongside soil moisture from currently operating satellite radiometer missions, such as SMOS (ESA) and SMAP (NASA). The estimation of water fluxes, such as plant water uptake (PWU) and transpiration rate (TR), from these earth system parameters (VOD, soil moisture) requires assessing water potential gradients and flow resistances in the soil, the vegetation and the atmosphere. Yet water flux estimation remains an elusive challenge especially on a global scale. In this concept study, we conduct a field-scale experiment to test mechanistic models for the estimation of seasonal water fluxes (PWU and TR) of a winter wheat stand using measurements of soil moisture, VOD, and relative air humidity (RH) in a controlled environment. We utilize microwave L-band observations from a tower-based radiometer to estimate VOD of a wheat stand during the 2017 growing season at the Selhausen test site in Germany. From VOD, we first extract the gravimetric moisture of vegetation and then determine the relative water content (RWC) and vegetation water potential (VWP) of the wheat field. Although the relative water content could be directly estimated from VOD, our results indicate this may be challenging for the phenological phases, when rapid biomass and plant structure development take place within the wheat canopy. We estimate water uptake from the soil to the wheat plants from the difference between the soil and vegetation potentials divided by the flow resistance from soil into wheat plants. The TR from the wheat plants into the atmosphere was obtained from the difference between the vegetation and atmosphere water potentials divided by the flow resistances from plants to the atmosphere. For this, the required soil matric potential (SMP), the vapor pressure deficit (VPD), and the flow resistances were obtained from on-site observations of soil, plant, and atmosphere together with simple mechanistic models. This pathfinder study shows that the L-band microwave radiation contains valuable information on vegetation water status that enables the estimation of water dynamics (up to fluxes) from the soil via wheat plants into the atmosphere, when combined with additional information of soil and atmosphere water content. Still, assumptions have to be made when estimating the vegetation water potential from relative water content as well as the water flow resistances between soil, wheat plants, and atmosphere. Moreover, direct validation of water flux estimates for the assessment of their absolute accuracy could not be performed due to a lack of in situ PWU and TR measurements. Nonetheless, our estimates of water status, potentials, and fluxes show the expected temporal dynamics, known from the literature, and intercompare reasonably well in absolute terms with independent TR estimates of the NASA ECOSTRESS mission, which relies on a Priestly-Taylor type of retrieval model. Our findings support that passive microwave remote-sensing techniques qualify for the estimation of vegetation water dynamics next to traditionally measured stand-scale or plot-scale techniques. They might shed light on future capabilities of monitoring water dynamics in the soil-plant-atmosphere system including wide-area, remote-sensing-based earth observation data., David Chaparro has received funding by “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/MIT19/51840001, by the MIT-MISTI, by the XXXIII Ramón Areces Postdoctoral Fellowship, and by grants PID2020-114623RB-C32 and MDM-2016-0600 funded by MCIN/AEI/10.13039/501100011033 and by the European Regional Development Fund (ERDF, EU). María Piles was supported by grant RTI2018-096765-A-100 funded by MCIN/AEI/10.13039/501100011033 and by the European Regional Development Fund (ERDF, EU).
- Published
- 2022
8. The SARSense Campaign: Air- and Space-Borne C- and L-Band SAR for the Analysis of Soil and Plant Parameters in Agriculture
- Author
-
Mengen, David, Montzka, Carsten, Jagdhuber, Thomas, Fluhrer, Anke, Brogi, Cosimo, Baum, Stephanie, Schüttemeyer, Dirk, Bayat, Bagher, Bogena, Heye, Coccia, Alexander, Masalias, Gerard, Trinkel, Verena, Jakobi, Jannis, Jonard, Francois, Ma, Yueling, Mattia, Francesco, Palmisano, Davide, Rascher, Uwe, Satalino, Giuseppe, Schumacher, Maike, Koyama, Christian, Schmidt, Marius, and Vereecken, Harry
- Subjects
ROSE_L ,Science ,fungi ,Aufklärung und Sicherheit ,airborne campaign ,food and beverages ,L-band ,ROSE-L ,plant parameters ,ddc:550 ,ddc:620 ,soil moisture ,C-band ,SAR - Abstract
With the upcoming L-band Synthetic Aperture Radar (SAR) satellite mission Radar Ob-serving System for Europe L-band SAR (ROSE-L) and its integration into existing C-band satellite missions such as Sentinel-1, multi-frequency SAR observations with high temporal and spatial resolution will become available. The SARSense campaign was conducted between June and August 2019 to investigate the potential for estimating soil and plant parameters at the agricultural test site in Selhausen (Germany). It included C- and L-band air- and space-borne observations accompanied by extensive in situ soil and plant sampling as well as unmanned aerial system (UAS) based multi-spectral and thermal infrared measurements. In this regard, we introduce a new publicly available SAR data set and present the first analysis of C- and L-band co- and cross-polarized backscattering signals regarding their sensitivity to soil and plant parameters. Results indicate that a multi-fre-quency approach is relevant to disentangle soil and plant contributions to the SAR signal and to identify specific scattering mechanisms associated with the characteristics of different crop type, especially for root crops and cereals.
- Published
- 2021
9. Long-term drought effects on spruce forests in a low mountain range of Germany – crossing the tipping point
- Author
-
Brüggemann, Nicolas, Graf, Alexander, Montzka, Carsten, Rothfuss, Youri, Tewes, Andreas, Vereecken, Harry, Schmidt, Marius, Bates, Jordan, Bayat, Bagher, Becker, Nils, Bogena, Heye, Dolfus, Daniel, Jakobi, Jannis, and Jonard, Francois
- Published
- 2021
10. UAS mounted LiDAR for Estimating LAI Type Metrics for Winter Wheat
- Author
-
Bates, Jordan, Montzka, Carsten, Schmidt, Marius, and Jonard, Francois
- Abstract
Metrics such as Leaf Area Index (LAI) are key factors in agricultural monitoring to understand the health and predictive yield of crops. Knowing the spatial distribution and variability in more detail increases the precision of fertilizer and irrigation practices. Unmanned Aircraft Systems (UAS) provide a means to carry sensors at a low altitude below the clouds providing a much higher spatial and temporal resolution than previously seen with satellite remote sensing while also providing more spatially complete data as compared to ground methods. Being that LiDAR is an active sensor and does not depend on solar reflectance and its corresponding zenith angle like commonly used passive optical sensors, it can further improve upon these UAS characteristics. It can also sense further into the canopy as the laser signals can pass through small gaps and are not affected by the shadowing of plant features created by the canopy itself. Evaluating the penetration of these signals and investigating the gap fraction (GF) that relates to canopy density, we are able to retrieve LAI. However, as LiDAR is sensing all above-ground plant elements it may present the ability to estimate Plant Area Index (PAI) rather than LAI when monitoring an entire growing season for a cereal crop like winter wheat that begins browning during senescence. This study investigates the feasibility of using LiDAR to estimate LAI or similar crop canopy density metrics. As LiDAR sensors for UAS are just becoming more accessible, studies related to this topic are scarcely seen.In this study, a winter wheat field in Selhausen, Germany (~10 ha in size) was monitored throughout the growing season using the following methods: [1] air campaigns with a DJI Matrice 600 UAS with a YellowScan Surveyor LiDAR system, [2] a DJI Matrice 600 UAS with a Micasense RedEdge-M (five band) multispectral sensor, and [3] ground measurements using a SS1 SunScan ceptometer. The resulting LAI type metrics of the UAS LiDAR methods used were compared to methods commonly used with multispectral (MS) and ground instruments to assess the proposed method’s potential. Additionally, because both products are spatially complete unlike the ground measurements, the LiDAR and multispectral methods were compared for similarities in spatial patterns.The results showed promise in using UAS LiDAR to estimate metrics that relate to LAI. Pearson correlation coefficient between the LiDAR and multispectral methods were moderate to high (R= 0.39 – 0.66) over the growing season. The comparison of UAS LiDAR towards the ground reference was within a 3% difference at times before senescence. Later in the growing season, the discrepancy increased between LiDAR and MS sensor retrievals mainly because of plant browning related to changes in plant chlorophyll content. This study covers the benefits of using UAS mounted LiDAR for LAI related measurements and its potential for improving crop health monitoring for precision farming.
- Published
- 2021
11. Estimating Forest Structure from UAV-mounted LiDAR Point CloudUsing Machine Learning
- Author
-
Neuville, Romain, Bates, Jordan, and Jonard, Francois
- Subjects
ddc:620 - Abstract
Monitoring the structure of forest stands is of high importance for forest managers to help them in maintaining ecosystem services. For that purpose, Unmanned Aerial Vehicles (UAVs) open new prospects, especially in combination with Light Detection and Ranging (LiDAR) technology. Indeed, the shorter distance from the Earth’s surface significantly increases the point density beneath the canopy, thus offering new possibilities for the extraction of the underlying semantics. For example, tree stems can now be captured with sufficient detail, which is a gateway to accurately locating trees and directly retrieving metrics—e.g., the Diameter at Breast Height (DBH). Current practices usually require numerous site-specific parameters, which may preclude their use when applied beyond their initial application context. To overcome this shortcoming, the machine learning Hierarchical Density-Based Spatial Clustering of Application of Noise (HDBSCAN) clustering algorithm was further improved and implemented to segment tree stems. Afterwards, Principal Component Analysis (PCA) was applied to extract tree stem orientation for subsequent DBH estimation. This workflow was then validated using LiDAR point clouds collected in a temperate deciduous closed-canopy forest stand during the leaf-on and leaf-off seasons, along with multiple scanning angle ranges. The results show that the proposed methodology can correctly detect up to 82% of tree stems (with a precision of 98%) during the leaf-off season and have a Maximum Scanning Angle Range (MSAR) of 75 degrees, without having to set up any site-specific parameters for the segmentation procedure. In the future, our method could then minimize the omission and commission errors when initially detecting trees, along with assisting further tree metrics retrieval. Finally, this research shows that, under the study conditions, the point density within an approximately 1.3-meter height above the ground remains low within closed-canopy forest stands even during the leaf-off season, thus restricting the accurate estimation of the DBH. As a result, autonomous UAVs that can both fly above and under the canopy provide a clear opportunity to achieve this purpose.
- Published
- 2021
12. UAS LIDAR CROP LAI ESTIMATIONS FROM CANOPY DENSITY
- Author
-
Bates, Jordan, Montzka, Carsten, Schmidt, Marius, and Jonard, Francois
- Published
- 2021
13. Integrated Modeling of Active and Passive Microwaves and Passive Optical Signatures
- Author
-
Baris, Ismail, Jagdhuber, Thomas, Jonard, Francois, Judge, Jasmeet, and Anglberger, Harald
- Subjects
microwave ,radiative transfer ,Aufklärung und Sicherheit ,optics ,radar - Abstract
A method of physical integration of scatteringmodels is presented here to estimate the backscattering coefficient(BSC) for L-band, brightness temperature (TB) for L- and C-Bandand the reflectance for visible (VIS) and near-infrared (NIR)region for dynamic vegetated terrain. The SPIN (SpectrumInvariant Interaction) model is obtained by solving vectorradiative transfer (VRT) equations kernel-based and therefore fordifferent wave interaction mechanisms. To demonstrate itsapplication for the microwave region, the measurements duringthe growing cycle of corn from the Eleventh Microwave, Water,and Energy Balance Experiment (MicroWEX-11) have been used.For the optical part the results are compared with the PROSAILmodel. By applying the SPIN model in the radar regime, it couldbe shown that the modeled backscattering coefficients (BSC)correlate strongly with the vertical polarization measurements(Pearson 0.83, R20.69) and are less correlated with the horizontalmeasurements (Pearson 0.45, R20.20). In addition, the modeledbrightness temperatures (L- and C-band) in both polarizationstates are also highly correlated with the MicroWEX-11measurements (L-band: Pearson 0.755, R2 0.57; C-band: Pearson0.73, R2 0.53). Finally, the optical results are consistent with theresults of other optical models (Pearson 0.99, R2 0.98).
- Published
- 2019
14. Electromagnetic Interactions with Vegetated Soils: An Integrative Modeling Approach
- Author
-
Baris, Ismail, Jagdhuber, Thomas, Jonard, Francois, Judge, Jasmeet, and Anglberger, Harald
- Subjects
radiative Transfer ,Radar ,microwave ,Aufklärung und Sicherheit ,optics - Abstract
Many attempts have been made and are undertaken to model the electromagnetic (EM) interaction with vegetation-coveredsoils at different frequencies. The modelling concepts and architectures range from empirical correlations to simple andsophisticated physical models [1, 2]. However, a general understanding of the physical properties and interactions along frequencyand for a wider part of the EM spectrum is difficult if the different models are treating the single frequencies and acquisitioncharacteristics (e.g. active or passive recording) separately. Due to the increasing fleet of earth observation sensors operating inmultiple frequency bands, demand for a spectrum-overarching EM modelling is becoming increasingly important. An integrativemodeling approach offers the chance that the different insights into biophysical and biochemical processes can be consideredconsistently including the respective dielectric properties and structural characteristics. With this objective we developed a kernel-driven electromagnetic interaction model using vector radiative transfer (VRT), called SPIN (Spectrum Invariant Interaction)model, which represents an integrated model approach for active and passive microwaves and passive optical as well as thermalsignatures [3]. Preparatory research for this study was the development of the RadOptics Model [4]. The main advantage of a kernel-driven approach is its analytical invertibility and the representation of the VRT as sum of linear equations, which leads toan enlargement of the information by including multiple frequencies. In addition, the model does not require semi-empirical or statistical calibration (i.e. all model parameters have physical meaning and none just for model adjustment.).
- Published
- 2019
15. The Soil Moisture Active Passive Experiments: Validation of the SMAP Products in Australia.
- Author
-
Ye, Nan, Walker, Jeffrey P., Wu, Xiaoling, de Jeu, Richard, Gao, Ying, Jackson, Thomas J., Jonard, Francois, Kim, Edward, Merlin, Olivier, Pauwels, Valentijn R. N., Renzullo, Luigi J., Rudiger, Christoph, Sabaghy, Sabah, von Hebel, Christian, Yueh, Simon H., and Zhu, Liujun
- Subjects
SOIL moisture ,MICROWAVE remote sensing ,RADAR in aeronautics ,SEAWATER salinity ,REMOTE sensing by radar - Abstract
The fourth and fifth Soil Moisture Active Passive Experiments (SMAPEx-4 and -5) were conducted at the beginning of the SMAP operational phase, May and September 2015, to: 1) evaluate the SMAP microwave observations and derived soil moisture (SM) products and 2) intercompare with the Soil Moisture and Ocean Salinity (SMOS) and Aquarius missions over the Murrumbidgee River Catchment in the southeast of Australia. Airborne radar and radiometer observations at the same microwave frequencies as SMAP were collected over SMAP footprints/grids concurrent with its overpass. In addition, intensive ground sampling of SM, vegetation water content, and surface roughness was carried out, primarily for validation of airborne SM retrieval over six ~ 3 km × 3 km focus areas. In this study, the SMAPEx-4 and -5 data sets were used as independent reference for extensively evaluating the brightness temperature and SM products of SMAP, and intercompared with SMOS and Aquarius under a wide range of SM and vegetation conditions. Importantly, this is the only extensive airborne field campaign that collected data while the SMAP radar was still operational. The SMAP radar, radiometer, and derived SM showed a high agreement with the SMAPEx-4 and -5 data set, with a root-mean-squared error (RMSE) of ~3 K for radiometer brightness temperature, and an RMSE of ~ 0.05 m
3 /m3 for the radiometer-only SM product. The SMAP radar backscatter had an RMSE of 3.4 dB, while the retrieved SM had an RMSE of 0.11 m3 /m3 when compared with the SMAPEx-4 data set. [ABSTRACT FROM AUTHOR]- Published
- 2021
- Full Text
- View/download PDF
16. Estimation of Vegetation Structure Parameters From SMAP Radar Intensity Observations.
- Author
-
Jagdhuber, Thomas, Montzka, Carsten, Lopez-Martinez, Carlos, Baur, Martin J., Link, Moritz, Piles, Maria, Das, Narendra Narayan, and Jonard, Francois
- Subjects
RADAR ,LAND cover ,RAIN forests ,SYNTHETIC aperture radar ,SOIL moisture ,GROUND vegetation cover - Abstract
In this article, we present a multipolarimetric estimation approach for two model-based vegetation structure parameters (shape ${A}_{P}$ and orientation distribution ${\psi }$ of the main canopy elements). The approach is based on a reduced observation set of three incoherent (no phase information) polarimetric backscatter intensities ($| {S}_{\mathrm{ HH}} |^{2}$ , $| {S}_{\mathrm{ HV}} |^{2}$ , and $| {S}_{\mathrm{ VV}} |^{2}$) combined with a two-parameter (${A}_{P}$ and ${\psi }$) discrete scatterer model of vegetation. The objective is to understand whether this confined set of observations contains enough information to estimate the two vegetation structure parameters from the L-band radar signals. In order to disentangle soil and vegetation scattering influences on these signals and ultimately perform a vegetation-only retrieval of vegetation shape ${A}_{P}$ and orientation distribution ${\psi }$ , we use the subpixel spatial heterogeneity expressed by the covariation of co- and cross-polarized backscatter ${\Gamma }_{{{\mathrm{PP-PQ}}}}$ of the neighboring cells and assume it is indicative for the amount of a vegetation-only co-to-cross-polarized backscatter ratio ${\mu }_{{{\mathrm{PP-PQ}}}}$. The ratio-based retrieval approach enables a relative (no absolute backscatter) estimation of the vegetation structure parameters which is more robust compared to retrievals with absolute terms. The application of the developed algorithm on global L-band Soil Moisture Active Passive (SMAP) radar data acquired from April to July 2015 indicates the potential and limitations of estimating these two parameters when no fully polarimetric data are available. A focus study on six different regions of interest, spanning land cover from barren land to tropical rainforest, shows a steady increase in orientation distribution toward randomly oriented volumes and a continuous decrease in shape arriving at dipoles for tropical vegetation. A comparison with independent data sets of vegetation height and above-ground biomass confirms this consistent and meaningful retrieval of ${A}_{P}$ and ${\psi }$. The retrieved shapes and orientation distributions represent the main vegetation elements matching the literature results from model-based decompositions of fully polarimetric L-band data at the SMAP spatial resolution. Based on our findings, ${A}_{P}$ and ${\psi }$ can be directly applied for parameterizing the vegetation scattering component of model-based polarimetric decompositions. This should facilitate decomposition into ground and vegetation scattering components and improve the retrieval of soil parameters (moisture and roughness) under vegetation. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
17. Modeling of Multilayered Media Green’s Functions With Rough Interfaces.
- Author
-
Jonard, Francois, Andre, Frederic, Pinel, Nicolas, Warren, Craig, Vereecken, Harry, and Lambot, Sebastien
- Subjects
- *
GREEN'S functions , *GROUND penetrating radar , *ELECTRICAL conductors , *INTERFACIAL roughness , *SCATTERING (Physics) , *STRIKE-slip faults (Geology) - Abstract
Horizontally stratified media are commonly used to represent naturally occurring and man-made structures, such as soils, roads, and pavements, when probed by ground-penetrating radar (GPR). Electromagnetic (EM) wave scattering from such multilayered media is dependent on the roughness of the interfaces. In this paper, we developed a closed-form asymptotic EM model considering random rough layers based on the scalar Kirchhoff-tangent plane approximation (SKA) model that we combined with planar multilayered media Green’s functions. In order to validate our extended SKA model, we conducted simulations using a numerical EM solver based on the finite-difference time-domain (FDTD) method. We modeled a medium with three layers—a base layer of perfect electric conductor (PEC) overlaid by two layers of different materials with rough interfaces. The reflections at the first and at the second interface were both well reproduced by the SKA model for each roughness condition. For the reflection at the PEC surface, the extended SKA model slightly overestimated the reflection, and this overestimation increased with the roughness amplitude. Good agreement was also obtained between the FDTD simulation input values and the inverted root mean square (rms) height estimates of the top interface, while the inverted rms heights of the second interface were slightly overestimated. The accuracy and the performances of our asymptotic forward model demonstrate the promising perspectives for simulating rough multilayered media and, hence, for the full waveform inversion of GPR data to noninvasively characterize soils and materials. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
18. Characterization of forest litter horizons through full-wave inversion of ground-penetrating radar data
- Author
-
Andre, Frederic, Jonard, M., Jonard, Francois, and Lambot, S.
- Published
- 2015
19. Roving system for soil moisture monitoring using GNSS-R and L-band radiometry:Surveys on semi-arid grassland during SMAPEx-4
- Author
-
Monerris, A., Jonard, Francois, Wu, X., and Walker, J. P.
- Published
- 2015
20. Using geophysical techniques to characterize tillage effect on soil properties
- Author
-
Jonard, Francois, Mahmoudzadeh, Roisin, Weihermüller, Lutz, Andre, Frederic, Vereecken, Harry, and Lambot, S.
- Abstract
Tillage practices influence physical, chemical, and biological soil properties, which also affect soil quality and consequently plant growth. In this study, the main objective was to evaluate the effect of different tillage systems on soil physical properties by using geophysical methods, namely, ground-penetrating radar (far-field and near-field GPR), capacitance probes (ThetaProbe and 5TE), electromagnetic induction (EMI) (Profiler and EM38), soil sampling, and by soil penetrometer. Since 2005, three contrasting tillage systems were applied on different plots of an agricultural field: i) conventional tillage (CT) with mouldboard ploughing to 27 cm depth, ii) deep loosening tillage (DL) with a heavy tine cultivator to 30 cm depth, and iii) reduced tillage (RT) with a spring tine cultivator to 10 cm depth. The geophysical and soil strength measurements were performed in April 2010. We observed that tillage influences the soil resistance (deeper tillage decreases soil resistance), which could be partly seen in the radar data. Soil water content reference measurements (capacitance probes and soil sampling) were in a relatively good agreement with the water content estimates from far-field GPR. We also observed that the tillage influences surface water content. Mean surface water content was significantly lower for CT than for DL and RT, which was partly explained by lower macropore connectivity between the topsoil and the deeper layers after conventional tillage. This study confirms the potential of GPR and EMI sensors for soil physical properties determination at the field scale and for the characterization of agricultural management practices.
- Published
- 2012
21. Estimating soil hydraulic properties using passive and active microwave data
- Author
-
Jonard, Francois, Weihermüller, Lutz, Jadoon, Khan Zaib, Schwank, M., Vereecken, Harry, and Lambot, S.
- Abstract
Soil hydraulic properties are of main interest for estimating water and energy fluxes at the land surface. In general, estimation of the hydraulic properties relies on the measurement of the soil water status within the soil profile usually performed with in-situ sensors such as time-domain reflectometry (TDR) or capacitance probes. Unfortunately, these sensors do not account for the high spatial and temporal variability in the soil, especially over large areas. In the opposite, proximal sensors such as ground-based microwave radiometer and radar can be used to obtained information at a larger scale. However, these sensors solely provide shallow subsurface information on the moisture status, and the retrievals might be biased by confounding factors such as soil surface roughness. L-band radiometer and off-ground ground-penetrating radar (GPR) measurements were performed above a rectangular wooden box (2.00 x 2.00 m2 area and 1.00 m height) homogeneously filled with sand. The radiometer was fixed on an arc of 5 m radius with an observation angle of 35° while the GPR was fixed above the sand box at nadir position. In order to avoid the brightness temperatures measured being affected by radiance originating from areas outside the sand box, the surrounding of the sand box was covered with a reflector made up of a mesh grid with a mash-size much smaller than the wavelength of the radiometer. Ground-truth soil moisture data were obtained by using TDR and capacitance sensors installed at 7 depths ranging from 5 to 80 cm. Soil temperature and soil conductivity data were also collected at each depth. The objective of this study is to compare estimated soil hydraulic properties of the sand box from radiometer, radar, and in-situ measurements and analyze the uncertainty related to these estimations.
- Published
- 2012
22. Reconstruction of forest litter horizons using ground-penetrating radar.
- Author
-
Andre, Frederic, Jonard, Mathieu, Lambot, Sebastien, and Jonard, Francois
- Published
- 2015
- Full Text
- View/download PDF
23. Integrated approach for effective permittivity estimation of multi-layered soils at L-Band.
- Author
-
Demontoux, Francois, Jonard, Francois, Bircher, Simone, Razafindratsima, Stephen, Schwank, Mike, Wigneron, Jean-Pierre, and Kerr, Yann H.
- Published
- 2014
- Full Text
- View/download PDF
24. Electromagnetic characterization of organic-rich soils at the microwave L-band with ground-penetrating radar, radiometry and laboratory measurements.
- Author
-
Jonard, Francois, Demontoux, Francois, Bircher, Simone, Razafindratsima, Stephen, Schwank, Mike, Weillermuller, Lutz, Lambot, Sebastien, Wigneron, Jean-Pierre, Kerr, Yann, and Vereecken, Harry
- Published
- 2014
- Full Text
- View/download PDF
25. Soil moisture retrieval using L-band radiometer and ground-penetrating radar.
- Author
-
Jonard, Francois, Weihermuller, Lutz, Schwank, Mike, Vereecken, Harry, and Lambot, Sebastien
- Published
- 2011
- Full Text
- View/download PDF
26. Postprocessing Data from Monitoring Field Spectrometers for the Study of Seasonal Trends in Chlorophyll Fluorescence on Canopy Scale over Grassland.
- Author
-
Naethe, Paul, Burkart, Andreas, Julitta, Tommaso, Junker, Laura Verena, Knaps, Axel, Jonard, Francois, Lud, Daniela, and Rascher, Uwe
- Published
- 2019
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.