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SMAP L-Band microwave radiometer: RFI mitigation prelaunch analysis and first year on-orbit observations / Priscilla N. Mohammed in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)
[article]
Titre : SMAP L-Band microwave radiometer: RFI mitigation prelaunch analysis and first year on-orbit observations Type de document : Article/Communication Auteurs : Priscilla N. Mohammed, Auteur ; Mustafa Aksoy, Auteur ; Jeffrey R. Piepmeier, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 6035 - 6047 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] acquisition de données
[Termes IGN] bande L
[Termes IGN] glace
[Termes IGN] humidité du sol
[Termes IGN] interférence
[Termes IGN] mission SMAP
[Termes IGN] mitigation
[Termes IGN] radiomètre à hyperfréquenceRésumé : (auteur) The National Aeronautics and Space Administration's (NASA) Soil Moisture Active and Passive (SMAP) mission, which was launched on January 31, 2015, is providing global measurements of soil moisture and freeze/thaw state. The SMAP radiometer operates within the protected Earth Exploration Satellite Service passive frequency allocation of 1400-1427 MHz. However, unauthorized in-band transmitters and out-of-band emissions from transmitters operating at frequencies adjacent to this allocated spectrum are known to cause interference to microwave radiometry in this band. Because measurement corruption by these terrestrial transmissions, which is referred to as radio-frequency interference (RFI), threatens mission success, the SMAP radiometer includes special flight hardware to enable the detection and filtering of RFI. Results from the first year of SMAP data show the presence of RFI with frequent occurrence over Asia and Europe. During the calibration/validation stage of the mission, the RFI detection and mitigation algorithms were modified to provide enhanced performance. Analysis of the L1B_TB products indicates good algorithmic performance with respect to RFI detection and removal. However, some regions of the globe (e.g., Japan) continue to experience complete data loss. This paper summarizes updates to the SMAP RFI processing algorithms based on prelaunch tests and on-orbit measurements, as well as RFI information obtained in SMAP's first year on orbit. Numéro de notice : A2016-867 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2580459 En ligne : https://doi.org/10.1109/TGRS.2016.2580459 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82907
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 10 (October 2016) . - pp 6035 - 6047[article]Vegetation effects modeling in soil moisture retrieval using MSVI / Mina Moradizadeh in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 10 (October 2016)
[article]
Titre : Vegetation effects modeling in soil moisture retrieval using MSVI Type de document : Article/Communication Auteurs : Mina Moradizadeh, Auteur ; Mohammad R. Saradjian, Auteur Année de publication : 2016 Article en page(s) : pp 803 - 810 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] humidité du sol
[Termes IGN] image multicapteur
[Termes IGN] indice de végétation
[Termes IGN] itération
[Termes IGN] température au sol
[Termes IGN] température de luminanceRésumé : (Auteur) Brightness temperature (BT) measured by passive microwave sensors is usually affected by soil moisture, vegetation cover, and soil roughness. Soil moisture estimates have been limited to regions that had either bare soil or low to moderate amounts of vegetation cover.
In this study, Simultaneous Land Parameters Retrieval Model (SLPRM) as an iterative least-squares minimization method has been used. This algorithm retrieves surface soil moisture, land surface temperature, and canopy temperature simultaneously using brightness temperature data in bare soil, low to moderate and higher amounts of vegetation cover.
Furthermore, a new index called MSVI (Multi Sensor Vegetation Index) has been introduced to approximate vegetation effects on properly observed brightness temperatures. The algorithm includes model construction, calibration, and validation using observations carried out for the SMEX03 (Soil Moisture Experiment 2003) region in the South and North of Oklahoma. The results indicated about 0.9 percent improvement on soil moisture estimation accuracy using the MSVI.Numéro de notice : A2016-935 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.10.803 En ligne : http://dx.doi.org/10.14358/PERS.82.10.803 Format de la ressource électronique : URL artilce Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83349
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 10 (October 2016) . - pp 803 - 810[article]Disaggregation of remotely sensed soil moisture in heterogeneous landscapes using holistic structure-based models / Subit Chakrabarti in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)
[article]
Titre : Disaggregation of remotely sensed soil moisture in heterogeneous landscapes using holistic structure-based models Type de document : Article/Communication Auteurs : Subit Chakrabarti, Auteur ; Jasmeet Judge, Auteur ; Tara Bongiovanni, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 4629 - 4641 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme d'apprentissage
[Termes IGN] cultures
[Termes IGN] désagrégation
[Termes IGN] Floride (Etats-Unis)
[Termes IGN] humidité du sol
[Termes IGN] modèle de régressionRésumé : (Auteur) In this paper, a novel machine learning algorithm is presented for disaggregation of satellite soil moisture (SM) based on self-regularized regressive models (SRRMs) using high-resolution correlated information from auxiliary sources. It includes regularized clustering that assigns soft memberships to each pixel at a fine scale followed by a kernel regression that computes the value of the desired variable at all pixels. Coarse-scale remotely sensed SM was disaggregated from 10 to 1 km using land cover (LC), precipitation, land surface temperature, leaf area index, and in situ observations of SM. This algorithm was evaluated using multiscale synthetic observations in NC Florida for heterogeneous agricultural LCs. It was found that the rmse for 96% of the pixels was less than 0.02 m 3/m3. The clusters generated represented the data well and reduced the rmse by up to 40% during periods of high heterogeneity in LC and meteorological conditions. The Kullback-Leibler divergence (KLD) between the true SM and the disaggregated estimates is close to zero, for both vegetated and bare-soil LCs. The disaggregated estimates were compared with those generated by the principle of relevant information (PRI) method. The rmse for the PRI disaggregated estimates is higher than the rmse for the SRRM on each day of the season. The KLD of the disaggregated estimates generated by the SRRM is at least four orders of magnitude lower than those for the PRI disaggregated estimates, whereas the computational time needed was reduced by three times. The results indicate that the SRRM can be used for disaggregating SM with complex nonlinear correlations on a grid with high accuracy. Numéro de notice : A2016-888 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2547389 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2547389 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83068
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4629 - 4641[article]Soil moisture retrieval in agricultural fields using adaptive model-based polarimetric decomposition of SAR data / Lian He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)
[article]
Titre : Soil moisture retrieval in agricultural fields using adaptive model-based polarimetric decomposition of SAR data Type de document : Article/Communication Auteurs : Lian He, Auteur ; Rocco Panciera, Auteur Année de publication : 2016 Article en page(s) : pp 4445 - 4460 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] biomasse
[Termes IGN] cultures
[Termes IGN] décomposition d'image
[Termes IGN] données polarimétriques
[Termes IGN] filtre adaptatif
[Termes IGN] humidité du sol
[Termes IGN] image radar moirée
[Termes IGN] polarimétrie radarRésumé : (Auteur) The aim of this paper was to estimate soil moisture in agricultural crop fields from fully polarimetric L-band synthetic aperture radar (SAR) data through the polarimetric decomposition of the SAR coherency matrix. A nonnegative-eigenvalue-decomposition scheme, together with an adaptive volume scattering model, is extended to an adaptive model-based decomposition (MBD) (Adaptive MBD) model for soil moisture retrieval. The Adaptive MBD can ensure nonnegative decomposed scattering components and allows two parameters (i.e., the mean orientation angle and a degree of randomness) to be determined to characterize the volume scattering. Its performance was tested using airborne SAR data and coincident ground measurements collected over agricultural fields in southeastern Australia and compared with previous MBD methods (i.e., the Freeman three-component decomposition using the extended Bragg model, the Yamaguchi three-component decomposition, and an iterative generalized hybrid decomposition). The results obtained with the newly proposed decomposition scheme agreed well with expectations based on observed plant structure and biomass levels. The new method was superior in tracking soil moisture dynamics with respect to previous decomposition methods in our study area, with root-mean-square error of soil moisture estimations being 0.10 and 0.14 m3/m3, respectively, for surface and double-bounce components. However, large variability in the achieved soil moisture accuracy was observed, depending on the presence of row structures in the underlying soil surface. Numéro de notice : A2016-884 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2542214 En ligne : https://doi.org/10.1109/TGRS.2016.2542214 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83048
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4445 - 4460[article]A spatial data infrastructure approach for the characterization of New Zealand's groundwater systems / Alexander Kmoch in Transactions in GIS, vol 20 n° 4 (August 2016)
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Titre : A spatial data infrastructure approach for the characterization of New Zealand's groundwater systems Type de document : Article/Communication Auteurs : Alexander Kmoch, Auteur ; Hermann Klug, Auteur ; Alistair B. H. Ritchie, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 626 - 641 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données environnementales
[Termes IGN] eau souterraine
[Termes IGN] infrastructure nationale des données localisées
[Termes IGN] Nouvelle-Zélande
[Termes IGN] Open geospatial consortium
[Termes IGN] service web
[Termes IGN] système d'information géographiqueRésumé : (auteur) The future information needs of stakeholders for hydrogeological and hydro-climate data management and assessment in New Zealand may be met with an Open Geospatial Consortium (OGC) standards-compliant publicly accessible web services framework which aims to provide integrated use of groundwater information and environmental observation data in general. The stages of the framework development described in this article are search and discovery as well as data collection and access with (meta)data services, which are developed in a community process. The concept and prototype implementation of OGC-compliant web services for groundwater and hydro-climate data include demonstration data services that present multiple distributed datasets of environmental observations. The results also iterate over the stakeholder community process and the refined profile of OGC services for environmental observation data sharing within the New Zealand Spatial Data Infrastructure (SDI) landscape, including datasets from the National Groundwater Monitoring Program and the New Zealand Climate Database along with datasets from affiliated regional councils at regional- and sub-regional scales. With the definition of the New Zealand observation data profile we show that current state-of-the-art standards do not necessarily need to be improved, but that the community has to agree upon how to use these standards in an iterative process. Numéro de notice : A2016-995 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12171 En ligne : http://dx.doi.org/10.1111/tgis.12171 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83773
in Transactions in GIS > vol 20 n° 4 (August 2016) . - pp 626 - 641[article]Assessment and validation of evapotranspiration using SEBAL algorithm and Lysimeter data of IARI agricultural farm, India / Anju Bala in Geocarto international, vol 31 n° 7 - 8 (July - August 2016)PermalinkGlobal sensitivity analysis of the L-MEB model for retrieving soil moisture / Zengyan Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 5 (May 2016)PermalinkGLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring / Erwan Motte in Sensors, vol 16 n° 5 (May 2016)PermalinkEau : la pression monte / Françoise de Blomac in DécryptaGéo le mag, n° 176 (avril 2016)PermalinkFaraday rotation correction for the SMAP radiometer / David M. Le Vine in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)PermalinkCartographie 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)PermalinkEffects of water and heat on growth of winter wheat in the North China Plain / Hongyan Wang in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)PermalinkPassive microwave remote sensing of soil moisture based on dynamic vegetation scattering properties for AMSR-E / Jinyang Du in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)PermalinkPlant community mycorrhization in temperate forests and grasslands: relations with edaphic properties and plant diversity / Maret Gerz in Journal of vegetation science, vol 27 n° 1 (January 2016)PermalinkInSAR assessment of surface deformations in urban coastal terrains associated with groundwater dynamics / Jonathan C. L. Normand in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)Permalink