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

Public 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 Editeur : Washington DC [Etats-Unis] : Earth and Space Science Open Archive ESSOAr Année de publication : 2021 Projets : 1-Pas de projet / Importance : 29 p. Note générale : bibliographie soumis au Journal of Geophysical Research - Solid Earth Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes IGN] aquifère [Termes IGN] Arkansas (Etats-Unis) [Termes IGN] déformation de la croute terrestre [Termes IGN] élasticité [Termes IGN] Kansas (Etats-Unis ; état) [Termes IGN] masse d'eau [Termes IGN] Missouri (Etats-Unis) [Termes IGN] Oklahoma (Etats-Unis) [Termes IGN] série temporelle [Termes IGN] surcharge hydrologique Résumé : (auteur) The continuous redistribution of water mass involved in the hydrologic cycle leads to deformation of the solid Earth. On a global scale, this deformation is well explained by redistribution in surface loading 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 central United States. We begin by characterizing the most important sources of signal in the spatially heterogeneous groundwater level dataset using an Independent Component Analysis. Then, to estimate the associated poroelastic displacements, we project geodetic time series corrected for surface loading effects onto orthogonalized versions of the 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 surficial layers with a high fracture density. Our findings suggest that OPAS undergoes significant poroelastic deformation, including highly heterogeneous horizontal poroelastic displacements. Numéro de notice : P2021-006 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Preprint nature-HAL : Préprint DOI : 10.1002/essoar.10507870.1 Date de publication en ligne : 02/09/2021 En ligne : https://doi.org/10.1002/essoar.10507870.1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98994

Automatic canola mapping using time series of Sentinel 2 images / Davoud Ashourloo in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 156 (October 2019) . - pp 63 - 76 Titre : Automatic canola mapping using time series of Sentinel 2 images Type de document : Article/Communication Auteurs : Davoud Ashourloo, Auteur ; Hamid Salehi Shahrabi, Auteur ; Mohsen Azadbakht, Auteur ; Hossein Aghighi, Auteur ; Hamed Nematollahi, Auteur ; Abbas Alimohammadi, Auteur ; Ali Akbar Matkan, Auteur Année de publication : 2019 Article en page(s) : pp 63 - 76 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] agriculture de précision [Termes IGN] Brassica napus subsp. napus [Termes IGN] image proche infrarouge [Termes IGN] image RVB [Termes IGN] image Sentinel-MSI [Termes IGN] Iran [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Oklahoma (Etats-Unis) [Termes IGN] rendement agricole [Termes IGN] série temporelle Résumé : (Auteur) Different techniques utilized for mapping various crops are mainly based on using training dataset. But, due to difficulties of access to a well-represented training data, development of automatic methods for detection of crops is an important need which has not been considered as it deserves. Therefore, main objective of present study was to propose a new automatic method for canola (Brassica napus L.) mapping based on Sentinel 2 satellite time series data. Time series data of three study sites in Iran (Moghan, Gorgan, Qazvin) and one site in USA: (Oklahoma), were used. Then, spectral reflectance values of canola in various spectral bands were compared with those of the other crops during the growing season. NDVI, Red and Green spectral bands were successfully applied for automatic identification of canola flowering date using the threshold values. Examination of the fisher function indicated that multiplication of the near-infrared (NIR) band by the sum of red and green bands during the flowering date is an efficient index to differentiate canola from the other crops. The Kappa and overall accuracy (OA) for the four study sites were more than 0.75 and 88%, respectively. Results of this research demonstrated the potential of the proposed approach for canola mapping using time series of remotely sensed data. Numéro de notice : A2019-317 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2019.08.007 Date de publication en ligne : 09/08/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.08.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93355 [article]

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Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images / Jie Wang in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 189 - 201 Titre : Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images Type de document : Article/Communication Auteurs : Jie Wang, Auteur ; Xiangming Xiao, Auteur ; Rajen Bajgain, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 189 - 201 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse aérienne [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image Landsat-8 [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] indice de végétation [Termes IGN] Leaf Area Index [Termes IGN] Oklahoma (Etats-Unis) [Termes IGN] paturage [Termes IGN] phénologie [Termes IGN] régression multiple Résumé : (Auteur) Grassland degradation has accelerated in recent decades in response to increased climate variability and human activity. Rangeland and grassland conditions directly affect forage quality, livestock production, and regional grassland resources. In this study, we examined the potential of integrating synthetic aperture radar (SAR, Sentinel-1) and optical remote sensing (Landsat-8 and Sentinel-2) data to monitor the conditions of a native pasture and an introduced pasture in Oklahoma, USA. Leaf area index (LAI) and aboveground biomass (AGB) were used as indicators of pasture conditions under varying climate and human activities. We estimated the seasonal dynamics of LAI and AGB using Sentinel-1 (S1), Landsat-8 (LC8), and Sentinel-2 (S2) data, both individually and integrally, applying three widely used algorithms: Multiple Linear Regression (MLR), Support Vector Machine (SVM), and Random Forest (RF). Results indicated that integration of LC8 and S2 data provided sufficient data to capture the seasonal dynamics of grasslands at a 10–30-m spatial resolution and improved assessments of critical phenology stages in both pluvial and dry years. The satellite-based LAI and AGB models developed from ground measurements in 2015 reasonably predicted the seasonal dynamics and spatial heterogeneity of LAI and AGB in 2016. By comparison, the integration of S1, LC8, and S2 has the potential to improve the estimation of LAI and AGB more than 30% relative to the performance of S1 at low vegetation cover (LAI  2 m2/m2, AGB > 500 g/m2). These results demonstrate the potential of combining S1, LC8, and S2 monitoring grazing tallgrass prairie to provide timely and accurate data for grassland management. Numéro de notice : A2019-269 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.06.007 Date de publication en ligne : 21/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.06.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93086 [article]

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Land cover characterization for hydrological modelling using thermal infrared emissivities / A. French in International Journal of Remote Sensing IJRS, vol 31 n° 14 (July 2010)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 31 n° 14 (July 2010) . - pp 3867 - 3883 Titre : Land cover characterization for hydrological modelling using thermal infrared emissivities Type de document : Article/Communication Auteurs : A. French, Auteur ; A. Inamdar, Auteur Année de publication : 2010 Article en page(s) : pp 3867 - 3883 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] caractérisation [Termes IGN] couvert végétal [Termes IGN] emissivité [Termes IGN] évapotranspiration [Termes IGN] image infrarouge [Termes IGN] image Terra-MODIS [Termes IGN] image thermique [Termes IGN] Kansas (Etats-Unis ; état) [Termes IGN] modèle hydrographique [Termes IGN] Oklahoma (Etats-Unis) Résumé : (Auteur) Remote sensing with multispectral thermal infrared can improve regional estimation of evapotranspiration (ET) by providing new constraints on land surface energy balance. Current models use visible and near infrared bands to obtain vegetative cover, and sometimes use thermal infrared data for land surface temperature. Together these can yield good ET estimates. However, it may be possible to do even better by using remotely sensed thermal infrared emissivity, a surface property related to fractional vegetative cover but independent of plant greenness. Emissivities derived from clear-sky Moderate Resolution Imaging Spectroradiometer (MODIS) observations obtained in 2007 over the Southern Great Plains (Oklahoma and Kansas), USA, were compared with changes in Normalized Difference Vegetation Index (NDVI) for winter wheat and grazing land. Emissivity changes were independent of NDVI and sensitive to standing canopies, regardless of growth stage or senescence. Thus emissivities were seasonally dynamic, able to detect wheat harvest timing, and helpful for modelling ET. Numéro de notice : A2010-371 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2010.483491 En ligne : https://doi.org/10.1080/01431161.2010.483491 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30565 [article]

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Assessing spatial uncertainty of LIDAR-derived building model: a case study in downtown Oklahoma city / M. Cheuk in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 3 (March 2009)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 3 (March 2009) . - pp 257 - 269 Titre : Assessing spatial uncertainty of LIDAR-derived building model: a case study in downtown Oklahoma city Type de document : Article/Communication Auteurs : M. Cheuk, Auteur ; M. Yuan, Auteur Année de publication : 2009 Article en page(s) : pp 257 - 269 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] estimation de précision [Termes IGN] incertitude géométrique [Termes IGN] milieu urbain [Termes IGN] modèle numérique du bâti [Termes IGN] Oklahoma (Etats-Unis) [Termes IGN] reconstruction 3D du bâti Résumé : (Auteur) Light Detection and Ranging (lidar) technology enables cost-effective rapid production of digital models that capture topography and vertical structures of surface features at a fine spatial resolution. The capability has promoted lidar applications for mapping terrain, buildings, forest stands, and coastal features that cannot be adequately captured by other remote sensing means over a large area. However, in complex terrain, lidar data and lidar-derived products may contain significant uncertainty. This research provides a simple method to assess the spatial uncertainty of lidar-derived building model, using downtown Oklahoma City, Oklahoma as an example. Results indicate that significant uncertainty could be found in urban environment where: (a) building structures are complex, (b) buildings are constructed with reflective materials, and (c) vegetation grows near-by. In addition, cities under rapid development also challenge the accuracy assessment of 3D building models. To conclude, we suggest: (a) careful pre-flight planning before data collection, (b) improve the feature extraction algorithm if possible, (c) use of other remote sensing data, and (d) accuracy assessment on suggested urban environments to reduce the spatial uncertainty of lidar data and lidar-derived products. Copyright ASPRS Numéro de notice : A2009-036 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.3.257 En ligne : https://doi.org/10.14358/PERS.75.3.257 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29666 [article]

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Using ENVISAT ASAR global mode data for surface soil moisture retrieval over Oklahoma, USA / Carsten Pathe in IEEE Transactions on geoscience and remote sensing, vol 47 n° 2 (February 2009)  

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Representing complex geographic phenomena in GIS / M. Yuan in Cartography and Geographic Information Science, vol 28 n° 2 (April 2001)  

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Automated approaches for displaying spatially oriented time-series data through image processing techniques / I.E. Von Essen in Geocarto international, vol 4 n° 4 (December 1989 - February 1990)  

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Estimating soil wetness using satellite data / B.J. Choudhury in International Journal of Remote Sensing IJRS, vol 9 n° 7 (July 1988)  

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Recognition and assessment of error in geographic information systems / S.J. Walsh in Photogrammetric Engineering & Remote Sensing, PERS, vol 53 n° 10 Tome 1 (october 1987)  

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Comparison of NOAA AVHRR data to meteorologic drought indices / S.J. Walsh in Photogrammetric Engineering & Remote Sensing, PERS, vol 53 n° 8 (august 1987)  

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