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4. EVAPOTRANSPIRATION AND EVAPORATION/TRANSPIRATION RETRIEVAL USING DUAL-SOURCE SURFACE ENERGY BALANCE MODELS INTEGRATING VIS/NIR/TIR DATA WITH SATELLITE SURFACE SOIL MOISTURE INFORMATION

Author

Boulet, G., primary, Delogu, E., additional, Chebbi, W., additional, Rafi, Z., additional, Le Dantec, V., additional, Mallick, K., additional, Mougenot, B., additional, Olioso, A., additional, Zribi, M., additional, Lili-Chabaane, Z., additional, Er-Raki, S., additional, and Merlin, O., additional

Published
2019
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6. Potential of Sentinel-1 radar datA for the assessment of soil and cereal cover parameters

Author

Bousbih, Safa, Zribi, Mehrez, Lili Chabaane, Z., Baghdadi, N., El Hajj, Mohammad, Gao, Qi, Mougenot, Bernard, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Université de Carthage - University of Carthage, Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
water, lcsh:Chemical technology, RETRODIFFUSION RADAR, Article, soil, modelling, RUGOSITE, remote sensing, vegetation, moisture, backscattering model, lcsh:TP1-1185, C-band, radar return, TELEDETECTION, roughness, cereals, cloud model, HUMIDITE DU SOL, water cloud model, soil water content, CEREALE, MODELISATION, [SDE]Environmental Sciences, Sentinel-1, radar
Abstract

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS; International audience; The main objective of this study is to analyze the potential use of Sentinel-1 (S1) radar data for the estimation of soil characteristics (roughness and water content) and cereal vegetation parameters (leaf area index (LAI), and vegetation height (H)) in agricultural areas. Simultaneously to several radar acquisitions made between 2015 and 2017, using S1 sensors over the Kairouan Plain(Tunisia, North Africa), ground measurements of soil roughness, soil water content, LAI and H were recorded. The NDVI (normalized difference vegetation index) index computed from Landsatoptical images revealed a strong correlation with in situ measurements of LAI. The sensitivity of the S1 measurements to variations in soil moisture, which has been reported in several scientific publications, is confirmed in this study. This sensitivity decreases with increasing vegetation cover growth (NDVI), and is stronger in the VV (vertical) polarization than in the VH cross-polarization. The results also reveal a similar increase in the dynamic range of radar signals observed in the VV and VH polarizations as a function of soil roughness. The sensitivity of S1 measurements to vegetation parameters (LAI and H) in the VV polarization is also determined, showing that the radar signal strength decreases when the vegetation parameters increase. No vegetation parameter sensitivity is observed in the VH polarization, probably as a consequence of volume scattering effects.

Published
2017

7. The Mediterranean region under climate change : a scientific update

Author

Jarlan, Lionel, Khabba, S., Szczypta, C., Lili-Chabaane, Z., Driouech, F., Le Page, Michel, Hanich, L., Fakir, Y., Boone, A., Boulet, Gilles, Thiébault, S. (ed.), and Moatti, Jean-Paul (ed.)

Subjects
BASSIN VERSANT, GESTION, PRECIPITATION, FACTEUR CLIMATIQUE, IRRIGATION, CHANGEMENT CLIMATIQUE, CHANGEMENT SOCIAL, HISTOIRE, RESSOURCES EN EAU, TEMPERATURE, NEIGE, MONTAGNE, PROSPECTIVE
Published
2016

8. Bare soil moisture retrieval from multi-temporal X-band TerraSAR-X SAR images

Author

Gorrab, Azza, Zribi, Mehrez, Baghdadi, N., Lili-Chabaane, Z., Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), INAT, Université de Carthage - University of Carthage, Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
RUGOSITE, VERY HIGH SPATIAL RESOLUTION, HUMIDITE DU SOL, IMAGE SATELLITE, [SDE]Environmental Sciences, ROUGHNESS, TRES HAUTE RESOLUTION SPATIALE, SOIL WATER CONTENT, TELEDETECTION, RADAR, CARTOGRAPHIE
Abstract

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOSIGARSS 2015, Milan, ITA, 26-/07/2015 - 31/07/2015; International audience; The aim of the present study is to analyze the sensitivity of X-band SAR (TerraSAR-X) signals as a function of different physical bare soil parameters (soil moisture, soil roughness), and to evaluate the accuracy of change detection approach proposed for soil moisture estimation. Firstly, we presented a brief description of our ground and satellite database. Secondly, we considered the main results of our statistical analysis of the relationships between radar and soil parameters: soil moisture and different roughness parameters (the rms height, Zs parameter, and a new roughness parameter Zg. Finally, we proposed an algorithm combing multi-temporal X-band SAR images (TerraSAR-X) with different continuous thetaprobe measurements for the retrieval of surface soil moisture at a high spatial resolution.

Published
2015

9. Operational soil moisture mapping using multitemporal ASAR/Wide Swath ENVISAT data

Author

Zribi, Mehrez, Kotti, F., Gorrab, Azza, Baghdadi, N., Mougenot, Bernard, Lili-Chabaane, Z., Amri, Rim, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), INAT UNIVERSITE DE CATHARGE TUNIS TUN, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), and Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)

Subjects
NDVI, [SDE]Environmental Sciences, SPOT-VGT, TUNISIE
Abstract

International audience; In this paper, an operational algorithm is proposed for the mapping of surface moisture over the northern and central parts of Tunisia, in North Africa. A change detection approach is applied, using 160 multi-incidence Envisat ASAR Wide Swath images acquired in the horizontal polarization over a 7-year period. Parameterization of this algorithm is considered for three classes of vegetation cover density (NDVI

Published
2014

10. The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat

Author

Boulet, G., primary, Mougenot, B., additional, Lhomme, J.-P., additional, Fanise, P., additional, Lili-Chabaane, Z., additional, Olioso, A., additional, Bahir, M., additional, Rivalland, V., additional, Jarlan, L., additional, Merlin, O., additional, Coudert, B., additional, Er-Raki, S., additional, and Lagouarde, J.-P., additional

Published
2015
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13. Soil texture estimation using TerraSAR X-band SAR

Author

Zribi, Mehrez, Kotti, F., Gorrab, Azza, Lili-Chabaane, Z., Chahbi, Aicha, Baghdadi, N., Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), INAT ARIANA TUN, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), and Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)

Subjects
[SDE]Environmental Sciences, TERRASAR-X, GeneralLiterature_MISCELLANEOUS
Abstract

International audience; Different methodologies have been proposed over the last decades, for the estimation of soil textures using specific multi- and hyper-spectral sensors, allowing the rapid and relatively inexpensive measurement of soil properties. In recent years, some studies have illustrated the potential of SAR measurements and very high resolution data for the retrieval of soil texture (Paris et al., 2010). Our objective in this paper is to analyze quantitatively the estimation of clay percent using TERRASAR-X data.

Published
2013

18. Assessing the hydrological impacts of agricultural changes upstream of the Tunisian World Heritage sea-connected Ichkeul Lake.

Author

AOUISSI, J., LILI CHABAANE, Z., BENABDALLAH, S., and CUDENNEC, C.

Subjects
LAND use, GEOGRAPHIC spatial analysis, REMOTE sensing, NONPOINT source pollution, WORLD Heritage Sites, WATER levels, SALINITY
Abstract

The impact of changes in agricultural land use and practices as a controlling driver of hydrologic response and as a source of diffuse pollution, are studied in the Joumine River basin, discharging into the Ichkeul Lake, northern Tunisia, a UNESCO World Heritage site since 1979. The lake is characterized by a very specific hydrological functioning based on a seasonal alternation of water levels and salinity through its link to the Mediterranean Sea. Three Landsat images, in situ surveys and SWAT modelling were used to simulate and assess streamflows and nitrate loads under retrospective land uses. [ABSTRACT FROM AUTHOR]

Published
2015
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27. Analysis of C-Band Scatterometer Moisture Estimations Derived Over a Semiarid Region.

Author

Amri, R., Zribi, M., Lili-Chabaane, Z., Wagner, W., and Hasenauer, S.

Subjects
SOIL moisture, FLOODS, EROSION, VEGETATION & climate, ATMOSPHERIC pressure, EVAPORATION (Meteorology)
Abstract

Spatial and temporal variations of soil moisture strongly affect flooding, erosion, solute transport, and vegetation productivity. Their characterization offers numerous possibilities for the improvement of our understanding of complex land-surface-atmosphere interactions. In this paper, soil moisture dynamics at the soil's surface (the first centimeters) and in its root zone (at depths down to 1 m) are investigated using 25 × 25 km2 scale data (Advanced Scatterometer (ASCAT)/METorological OPerational (METOP) scatterometer), for a semiarid region in North Africa. Our study highlights the quality of the surface and root-zone soil moisture products, derived from ASCAT data recorded over a two-year period. Surface soil moisture tends to be highly variable because it is strongly influenced by atmospheric conditions (rain and evaporation). On the other hand, root-zone moisture is considerably less variable. A statistical drought-monitoring index, referred to as the “moisture anomaly index,” is derived from ASCAT and European Remote Sensing (ERS) time series. This index was tested with ERS and ASCAT products during the 1991-2010 study period. A strong correlation is found between the proposed index and the standardized precipitation index. [ABSTRACT FROM AUTHOR]

Published
2012
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29. Investigation of Multi-Frequency SAR Data to Retrieve the Soil Moisture within a Drip Irrigation Context Using Modified Water Cloud Model.

Author

Ayari E, Kassouk Z, Lili-Chabaane Z, Baghdadi N, and Zribi M

Subjects
Environmental Monitoring, Water, Radar, Soil
Abstract

The objective of this paper was to estimate soil moisture in pepper crops with drip irrigation in a semi-arid area in the center of Tunisia using synthetic aperture radar (SAR) data. Within this context, the sensitivity of L-band (ALOS-2) in horizontal-horizontal (HH) and horizontal-vertical (HV) polarizations and C-band (Sentinel-1) data in vertical-vertical (VV) and vertical-horizontal (VH) polarizations is examined as a function of soil moisture and vegetation properties using statistical correlations. SAR signals scattered by pepper-covered fields are simulated with a modified version of the water cloud model using L-HH and C-VV data. In spatially heterogeneous soil moisture cases, the total backscattering is the sum of the bare soil contribution weighted by the proportion of bare soil (one-cover fraction) and the vegetation fraction cover contribution. The vegetation fraction contribution is calculated as the volume scattering contribution of the vegetation and underlying soil components attenuated by the vegetation cover. The underlying soil is divided into irrigated and non-irrigated parts owing to the presence of drip irrigation, thus generating different levels of moisture underneath vegetation. Based on signal sensitivity results, the potential of L-HH data to retrieve soil moisture is demonstrated. L-HV data exhibit a higher potential to retrieve vegetation properties regarding a lower potential for soil moisture estimation. After calibration and validation of the proposed model, various simulations are performed to assess the model behavior patterns under different conditions of soil moisture and pepper biophysical properties. The results highlight the potential of the proposed model to simulate a radar signal over heterogeneous soil moisture fields using L-HH and C-VV data.

Published
2022
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30. Forecasting of Cereal Yields in a Semi-arid Area Using the Simple Algorithm for Yield Estimation (SAFY) Agro-Meteorological Model Combined with Optical SPOT/HRV Images.

Author

Chahbi Bellakanji A, Zribi M, Lili-Chabaane Z, and Mougenot B

Abstract

In semi-arid areas characterized by frequent drought events, there is often a strong need for an operational grain yield forecasting system, to help decision-makers with the planning of annual imports. However, monitoring the crop canopy and production capacity of plants, especially for cereals, can be challenging. In this paper, a new approach to yield estimation by combining data from the Simple Algorithm for Yield estimation (SAFY) agro-meteorological model with optical SPOT/ High Visible Resolution (HRV) satellite data is proposed. Grain yields are then statistically estimated as a function of Leaf Area Index (LAI) during the maximum growth period between 25 March and 5 April. The LAI is retrieved from the SAFY model, and calibrated using SPOT/HRV data. This study is based on the analysis of a rich database, which was acquired over a period of two years (2010⁻2011, 2012⁻2013) at the Merguellil site in central Tunisia (North Africa) from more than 60 test fields and 20 optical satellite SPOT/HRV images. The validation and calibration of this methodology is presented, on the basis of two subsets of observations derived from the experimental database. Finally, an inversion technique is applied to estimate the overall yield of the entire studied site.

Published
2018
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31. Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters.

Author

Bousbih S, Zribi M, Lili-Chabaane Z, Baghdadi N, El Hajj M, Gao Q, and Mougenot B

Abstract

The main objective of this study is to analyze the potential use of Sentinel-1 (S1) radar data for the estimation of soil characteristics (roughness and water content) and cereal vegetation parameters (leaf area index (LAI), and vegetation height (H)) in agricultural areas. Simultaneously to several radar acquisitions made between 2015 and 2017, using S1 sensors over the Kairouan Plain (Tunisia, North Africa), ground measurements of soil roughness, soil water content, LAI and H were recorded. The NDVI (normalized difference vegetation index) index computed from Landsat optical images revealed a strong correlation with in situ measurements of LAI. The sensitivity of the S1 measurements to variations in soil moisture, which has been reported in several scientific publications, is confirmed in this study. This sensitivity decreases with increasing vegetation cover growth (NDVI), and is stronger in the VV (vertical) polarization than in the VH cross-polarization. The results also reveal a similar increase in the dynamic range of radar signals observed in the VV and VH polarizations as a function of soil roughness. The sensitivity of S1 measurements to vegetation parameters (LAI and H) in the VV polarization is also determined, showing that the radar signal strength decreases when the vegetation parameters increase. No vegetation parameter sensitivity is observed in the VH polarization, probably as a consequence of volume scattering effects., Competing Interests: The authors declare no conflict of interest.

Published
2017
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