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Fusion of SAR and multi-spectral time series for determination of water table depth and lake area in peatlands / Katrin Krzepek in PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, vol 90 n° 6 (December 2022)  

Public [article]  inPFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science > vol 90 n° 6 (December 2022) . - pp 561 - 575 Titre : Fusion of SAR and multi-spectral time series for determination of water table depth and lake area in peatlands Type de document : Article/Communication Auteurs : Katrin Krzepek, Auteur ; Jacob Schmidt, Auteur ; Dorota Iwaszczuk, Auteur Année de publication : 2022 Article en page(s) : pp 561 - 575 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] apprentissage non-dirigé [Termes IGN] aquifère [Termes IGN] Bade-Wurtemberg (Allemagne) [Termes IGN] bande C [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] fusion d'images [Termes IGN] image multibande [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] Normalized Difference Water Index [Termes IGN] puits de carbone [Termes IGN] seuillage d'image [Termes IGN] théorie de Dempster-Shafer [Termes IGN] tourbière Résumé : (auteur) Peatlands as natural carbon sinks have a major impact on the climate balance and should therefore be monitored and protected. The hydrology of the peatland serves as an indicator of the carbon storage capacity. Hence, we investigate the question how suitable different remote sensing data are for monitoring the size of open water surface and the water table depth (WTD) of a peatland ecosystem. Furthermore, we examine the potential of combining remote sensing data for this purpose. We use C-band synthetic aperture radar (SAR) data from Sentinel-1 and multi-spectral data from Sentinel-2. The radar backscatter σ0, the normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) are calculated and used for consideration of the WTD and the lake size. For the measurement of the lake size, we implement and investigate the methods: random forest, adaptive thresholding and an analysis according to the Dempster–Shafer theory. Correlations between WTD and the remote sensing data σ0 as well as NDWI are investigated. When looking at the individual data sets the results of our case study show that the VH polarized σ0 data produces the clearest delineation of the peatland lake. However the adaptive thresholding of the weighted fusion image of σ0-VH, σ0-VV and MNDWI, and the random forest algorithm with all three data sets as input proves to be the most suitable for determining the lake area. The correlation coefficients between σ0/NDWI and WTD vary greatly and lie in ranges of low to moderate correlation. Numéro de notice : A2022-942 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s41064-022-00216-w Date de publication en ligne : 06/09/2022 En ligne : https://doi.org/10.1007/s41064-022-00216-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102876 [article]

A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers / Qasim Khan in Geocarto international, vol 37 n° 20 ([20/09/2022])  

Public [article]  inGeocarto international > vol 37 n° 20 [20/09/2022] . - pp 5832 - 5850 Titre : A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers Type de document : Article/Communication Auteurs : Qasim Khan, Auteur ; Muhammad Usman Liaqat, Auteur ; Mohamed Mostafa Mohamed, Auteur Année de publication : 2022 Article en page(s) : pp 5832 - 5850 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse en composantes principales [Termes IGN] apprentissage automatique [Termes IGN] aquifère [Termes IGN] ArcGIS [Termes IGN] classification bayesienne [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] eau souterraine [Termes IGN] Emirats Arabes Unis [Termes IGN] estimation par noyau [Termes IGN] nitrate [Termes IGN] vulnérabilité Résumé : (auteur) Groundwater is more prone to contamination due to its extensive usage. Different methods are applied to study vulnerability of groundwater including widely used DRASTIC method, SI and GOD. This study proposes a novel method of mapping groundwater vulnerability using machine learning algorithms. In this study, point extraction method was used to extract point values from a grid of 646 points of seven raster layer in the Al Khatim study area of United Arab Emirates. These extracted values were classified based on nitrate concentration threshold of 50 mg/L into two classes. Machine learning models were developed, using depth to water (D), recharge (R), aquifer media (A), soil media (S), topography (T), vadose zone (I) and hydraulic conductivity (C), on the basis of nitrate class. Classified ‘groundwater vulnerability class values’ were trained using 10-fold cross-validation, using four machine learning models which were Random Forest, Support Vector Machine, Naïve Bayes and C4. 5. Accuracy showed the model developed by Random Forest gained highest accuracy of 93%. Four groundwater vulnerability maps were developed from machine learning classifiers and was compared with base method of DRASTIC index. The efficiency, accuracy and validity of machine learning based models were evaluated based on Receiver Operating Characteristics (ROC) curve and Precision-Recall curve (PRC). The results proved that machine learning is an efficient tool to access, analyze and map groundwater vulnerability. Numéro de notice : A2022-716 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2021.1923833 Date de publication en ligne : 01/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1923833 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101641 [article]

Understanding the geodetic signature of large aquifer systems: Example of the Ozark plateaus in central United States / Stacy Larochelle in Journal of geophysical research : Solid Earth, vol 127 n° 3 (March 2022)  

Public [article]  inJournal of geophysical research : Solid Earth > vol 127 n° 3 (March 2022) . - n° e2021JB023097 Titre : Understanding the geodetic signature of large aquifer systems: Example of the Ozark plateaus in central United States Type de document : Article/Communication Auteurs : Stacy Larochelle, Auteur ; Kristel Chanard , Auteur ; Luce Fleitout, Auteur ; Jérôme Nicolas Fortin, Auteur ; Adriano Gualandi, Auteur ; Laurent Longuevergne, Auteur ; Paul Rebischung , Auteur ; Sophie Violette, Auteur ; Jean-Philippe Avouac, Auteur Année de publication : 2022 Article en page(s) : n° e2021JB023097 Note générale : bibliographie - financial support : PGSD‐3‐517078‐2018, Natural Sciences and Engineering Research Council of Canada 2019‐2020 STEM Chateaubriand Fellowship, Office for Science and Technology of the Embassy of France in the United States IPGP contribution #4232, Institut de Physique du Globe de Paris Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] analyse en composantes indépendantes [Termes IGN] aquifère [Termes IGN] déformation de la croute terrestre [Termes IGN] données GNSS [Termes IGN] données GRACE [Termes IGN] élasticité [Termes IGN] Etats-Unis [Termes IGN] hydrogéologie [Termes IGN] surcharge hydrologique Résumé : (auteur) The continuous redistribution of water involved in the hydrologic cycle leads to deformation of the solid Earth. On a global scale, this deformation is well explained by the loading imposed by hydrological mass variations and can be quantified to first order with space-based gravimetric and geodetic measurements. At the regional scale, however, aquifer systems also undergo poroelastic deformation in response to groundwater fluctuations. Disentangling these related but distinct 3D deformation fields from geodetic time series is essential to accurately invert for changes in continental water mass, to understand the mechanical response of aquifers to internal pressure changes as well as to correct time series for these known effects. Here, we demonstrate a methodology to accomplish this task by considering the example of the well-instrumented Ozark Plateaus Aquifer System (OPAS) in the central United States. We begin by characterizing the most important sources of groundwater level variations in the spatially heterogeneous piezometer dataset using an Independent Component Analysis. Then, to estimate the associated poroelastic displacements, we project geodetic time series corrected for hydrological loading effects onto the dominant groundwater temporal functions. We interpret the extracted displacements in light of analytical solutions and a 2D model relating groundwater level variations to surface displacements. In particular, the relatively low estimates of elastic moduli inferred from the poroelastic displacements and groundwater fluctuations may be indicative of aquifer layers with a high fracture density. Our findings suggest that OPAS undergoes significant poroelastic deformation, including highly heterogeneous horizontal poroelastic displacements. Numéro de notice : A2022-944 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1029/2021JB023097 Date de publication en ligne : 15/02/2022 En ligne : https://doi.org/10.1029/2021JB023097 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103155 [article]

Multi-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques / Saman Javadi in Geocarto international, vol 37 n° 4 ([15/02/2022])  

Public [article]  inGeocarto international > vol 37 n° 4 [15/02/2022] . - pp 1160-1182 Titre : Multi-parameter risk mapping of Qazvin aquifer by classic and fuzzy clustering techniques Type de document : Article/Communication Auteurs : Saman Javadi, Auteur ; Seied Mehdy Hashemy Shahdany, Auteur ; Hashemy Shahdany, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1160-1182 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] aquifère [Termes IGN] arsenic [Termes IGN] cartographie des risques [Termes IGN] contamination [Termes IGN] eau souterraine [Termes IGN] Iran [Termes IGN] logique floue [Termes IGN] nitrate [Termes IGN] pollution des eaux [Termes IGN] vulnérabilité Résumé : (auteur) This study proposes a new approach to establish a multi-parameter risk mapping method by employing the K-Means clustering technique. Accordingly, spatial assessment of arsenic (As), nitrate (NO3) and total dissolved solids (TDS) were carried out based on the type of land use to estimate contamination potential in an aquifer. Since risk mapping is always associated with the occurrence probability of a phenomenon, pollution occurrence probability was then obtained using the fuzzy C-means clustering. The results reveal that NO3 and As contamination levels increase from the first cluster (C1), covers 22.3% of the aquifer, to C5 encompassing 35.1% of the aquifer devoted to extensive industrial and agricultural activities. Fuzzy clustering results show that the pollution occurrence probability in each aquifer cell varied from less than 30 to more than 90%. Moreover, the results show, industrial and agricultural land uses cover about 70% of the areas with high risk of contamination. Numéro de notice : A2022-396 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1778099 Date de publication en ligne : 23/06/2020 En ligne : https://doi.org/10.1080/10106049.2020.1778099 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100690 [article]

Monitoring and modeling of the Sacramento Valley aquifer (California) using geodetic and piezometric measurements / Stacy Larochelle (2022)  

Public Titre : Monitoring and modeling of the Sacramento Valley aquifer (California) using geodetic and piezometric measurements Type de document : Article/Communication Auteurs : Stacy Larochelle, Auteur ; Kristel Chanard , Auteur ; Manon Dalaison, Auteur ; Luce Fleitout, Auteur ; Jérôme Nicolas Fortin, Auteur ; Laurent Longuevergne, Auteur ; Donald F. Argus, Auteur ; Romain Jolivet, Auteur ; Jean-Philippe Avouac, Auteur Editeur : Washington DC [Maryland - Etats-Unis] : American Geophysical Union AGU Année de publication : 2022 Conférence : AGU 2022, Fall meeting, American Geophysical Union Fall Meeting 12/12/2022 16/12/2022 Chicago Illinois - Etats-Unis Importance : n° NS23A-06 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] aquifère [Termes IGN] Californie (Etats-Unis) [Termes IGN] données GNSS [Termes IGN] hydrogéologie [Termes IGN] surveillance hydrologique Résumé : (auteur) Changes in groundwater levels associated with hydroclimatic variations and anthropogenic water extraction can deform the solid Earth, both elastically and inelastically. Satellite-based geodetic techniques which measure the Earth’s surface displacements can thus be used to track changing conditions in aquifer systems. However, accurately extracting groundwater-induced deformation signals still poses a challenge as geodetic techniques like GNSS and InSAR also record noise, systematic errors and other sources of deformation. In this study, we take advantage of the relatively dense in situ groundwater monitoring network of the Sacramento Valley aquifer in California to constrain its deformation and hydromechanical properties. We start by characterizing the main seasonal and multiannual fluctuations in groundwater levels with an Independent Component Analysis (ICA) and exploit the resulting temporal signature to extract the associated deformation field from GNSS and InSAR time series. We then develop a poroelastic model of the aquifer to invert for its elastic storage capacity and estimate the respective contributions of elastic and inelastic processes to long-term subsidence. Our modeling also suggests that depth-dependent elastic properties are necessary to explain the spatial distribution of horizontal poroelastic displacements measured by GNSS. This work has important implications for the sustainable management of heavily-stressed Californian aquifers but also serves as a calibration between in situ and remote sensing techniques, which is essential for the successful deployment of satellite-based groundwater monitoring in areas with sparse field-based instrumentation. Numéro de notice : C2022-053 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans En ligne : https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1093662 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103158

Groundwater vulnerability assessment of the chalk aquifer in the northern part of France / Lahcen Zouhri in Geocarto international, vol 36 n° 11 ([15/06/2021])  

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Electrical resistivity, remote sensing and geographic information system approach for mapping groundwater potential zones in coastal aquifers of Gurpur watershed / H.S. Virupaksha in Geocarto international, vol 36 n° 8 ([01/05/2021])  

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Apports de la télédétection des puits pastoraux à la cartographie des eaux souterraines du Sahel / Bernard Collignon in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)  

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Understanding the geodetic signature of large aquifer systems: Example of the Ozark Plateaus in Central United States / Stacy Larochelle (2021)  

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Hydrogeology of the western Po plain (Piedmont, NW Italy) / Domenico Antonio De Luca in Journal of maps, vol 16 n° 2 ([01/06/2020])  

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Les eaux de pluie maîtrisées ou en excès / Pierre Clergeot in Géomètre, n° 2173 (octobre 2019)

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Développement d’un « ModelBuilder » pour l’évaluation de la recharge nette : cas de la nappe phréatique de Zéramdine Beni Hassène (Tunisie) / Imen Hentati in Géomatique expert, n° 128 (juin - juillet 2019)

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Identification of rainwater harvesting sites using SCS-CN methodology, remote sensing and Geographical Information System techniques / Tarun Kumar in Geocarto international, vol 32 n° 12 (December 2017)  

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InSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley, Mexico / Pascal Castellazzi in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)  

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Cartographie de la vulnérabilité de la nappe à la pollution dans la plaine de Sidi Bel Abbes : Apport des données de télédétection et le SIG / N. Bentekhici in Bulletin des sciences géographiques, n° 30 (2015 - 2016)

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