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Atmospheric correction to passive microwave brightness temperature in snow cover mapping over china / Yubao Qiu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)
[article]
Titre : Atmospheric correction to passive microwave brightness temperature in snow cover mapping over china Type de document : Article/Communication Auteurs : Yubao Qiu, Auteur ; Lijuan Shi, Auteur ; Juha Lemmetyinen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 6482 - 6495 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] capteur passif
[Termes IGN] Chine
[Termes IGN] correction atmosphérique
[Termes IGN] image NOAA
[Termes IGN] image SSMIS
[Termes IGN] image Terra-MODIS
[Termes IGN] manteau neigeux
[Termes IGN] modèle atmosphérique
[Termes IGN] neige
[Termes IGN] série temporelle
[Termes IGN] télédétection en hyperfréquence
[Termes IGN] température de luminance
[Termes IGN] teneur en vapeur d'eauRésumé : (auteur) Variable atmospheric conditions are typically ignored in the retrieval of geophysical parameters of the Earth’s surface when using spaceborne passive microwave observations. However, high frequencies, for example, 91.7 GHz, are sensitive to variable atmospheric absorption, even in winter’s dry conditions. In this article, the influence of variable atmospheric absorption on snow cover extent (SCE) mapping was quantitatively investigated. A physical method was derived to enable atmospheric correction for variable atmospheric conditions. The total column precipitable water vapor (TPWV) from Moderate Resolution Imaging Spectroradiometer (MODIS) was parametrized into transmittances in this correction method. The corrected brightness temperature at 19 and 91.7 GHz from the Special Sensor Microwave Imager Sounder (SSMIS) was applied to the threshold algorithm for snow mapping over China. Compared with the Interactive Multisensor Snow and Ice Mapping System (IMS) data in winter from 2012 to 2013, for Qinghai–Tibet plateau (QTP), a significant improvement after correction was obtained from February to March over ephemeral and shallow snow, where the largest daily improvement of accuracy is up to 20%. The accuracy (incl. precision, recall, and F1 index) improved on average is from 0.77 (0.60, 0.68, and 0.63) to 0.79 (0.69, 0.7, and 0.68) over the full winter time from December to March. Over forest-rich Northeast China, where snow in winter is thicker, small improvement was observed at the onset of the snow season and over snow margin area. It was evidenced that high frequency is a promising way of snow cover mapping with the proposed atmospheric correction method. Numéro de notice : A2021-630 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3031837 Date de publication en ligne : 02/11/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3031837 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98279
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 8 (August 2021) . - pp 6482 - 6495[article]Multi-GNSS PPP/INS tightly coupled integration with atmospheric augmentation and its application in urban vehicle navigation / Shengfeng Gu in Journal of geodesy, vol 95 n° 6 (June 2021)
[article]
Titre : Multi-GNSS PPP/INS tightly coupled integration with atmospheric augmentation and its application in urban vehicle navigation Type de document : Article/Communication Auteurs : Shengfeng Gu, Auteur ; Chunqi Dai, Auteur ; Wentao Fang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 64 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] centrale inertielle
[Termes IGN] correction atmosphérique
[Termes IGN] couplage GNSS-INS
[Termes IGN] milieu urbain
[Termes IGN] navigation automobile
[Termes IGN] positionnement ponctuel précis
[Termes IGN] retard ionosphèrique
[Termes IGN] teneur verticale totale en électrons
[Termes IGN] Wuhan (Chine)Résumé : (auteur) Precise point positioning (PPP) is receiving increasing interest due to its cost-effectiveness, global coverage and high accuracy. However, its application in the urban environment is still full of challenges due to the satellite tracking sky-view. Thus, we presented a comprehensive positioning model by fusing the multi-GNSS (global navigation satellite system) combination, GNSS/INS (inertial navigation system) tightly coupled integration as well as the ionospheric and tropospheric augmentation in the undifferenced and uncombined PPP. The performance of this model in dual-frequency and single-frequency positioning was assessed with two experiments that denoted as T019 and T023, respectively, and both the experiments were carried out in a real urban environment. Particularly, the experiment T023 was carried out in the Second Ring Road of Wuhan city, which can be regarded as a typical downtown environment. Concerning the regional atmospheric augmentation, observations from 5 reference stations with an inter-station distance of about 40 km were also collected during the experimental time. The comparison between reference stations suggested that the regional tropospheric model had a precision of better than 0.6 cm in terms of zenith tropospheric delay, while the regional ionospheric model had a precision of around 0.5 total electron content unit in terms of Vertical Total Electron Content. It can be concluded that the GPS-only PPP can be improved significantly for urban vehicle navigation with these techniques, i.e., the multi-GNSS, INS tightly coupled integration and the atmospheric augmentation, through the positioning analysis, while INS tightly coupled integration makes the most contributions under the downtown environment, and the improvement of the regional atmospheric augmentation in single-frequency PPP is more significant since that single frequency is more sensitive to the ionospheric delay. In addition, it is proved that the regional atmospheric augmentation accelerates positioning convergence. The 3D positioning root-mean-square (RMS) with the comprehensive positioning model for dual frequency are 0.22 m and 0.77 m for T019 and T023, respectively. Concerning single-frequency PPP, the 3D RMS is 0.45 m and 1.17 m for T019 and T023, respectively. Moreover, taking the lane-level navigation under the downtown environment of T023 into consideration, we further presented the cumulative frequency of the horizontal positioning error less than 1 m, i.e., P(dN2+dE2−−−−−−−−−√ Numéro de notice : A2021-429 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01514-8 Date de publication en ligne : 26/05/2021 En ligne : https://doi.org/10.1007/s00190-021-01514-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97789
in Journal of geodesy > vol 95 n° 6 (June 2021) . - n° 64[article]Atmospheric correction of Sentinel-3/OLCI data for mapping of suspended particulate matter and chlorophyll-a concentration in Belgian turbid coastal waters / Quinten Vanhellemont in Remote sensing of environment, Vol 256 (April 2020)
[article]
Titre : Atmospheric correction of Sentinel-3/OLCI data for mapping of suspended particulate matter and chlorophyll-a concentration in Belgian turbid coastal waters Type de document : Article/Communication Auteurs : Quinten Vanhellemont, Auteur ; Kevin Ruddick, Auteur Année de publication : 2021 Article en page(s) : n° 112284 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Belgique
[Termes IGN] chlorophylle
[Termes IGN] correction atmosphérique
[Termes IGN] eaux côtières
[Termes IGN] image Sentinel-OLCI
[Termes IGN] particule
[Termes IGN] rayonnement infrarouge
[Termes IGN] réflectance
[Termes IGN] turbidité des eauxRésumé : (auteur) The performance of different atmospheric correction algorithms for the Ocean and Land Colour Instrument (OLCI) on board of Sentinel-3 (S3) is evaluated for retrieval of water-leaving radiance reflectance, and derived parameters chlorophyll-a concentration and turbidity in turbid coastal waters in the Belgian Coastal Zone (BCZ). This is performed using in situ measurements from an autonomous pan-and-tilt hyperspectral radiometer system (PANTHYR). The PANTHYR provides validation data for any satellite band between 400 and 900 nm, with the deployment in the BCZ of particular interest due to the wide range of observed Near-InfraRed (NIR) reflectance. The Dark Spectrum Fitting (DSF) atmospheric correction algorithm is adapted for S3/OLCI processing in ACOLITE, and its performance and that of 5 other processing algorithms (L2-WFR, POLYMER, C2RCC, SeaDAS, and SeaDAS-ALT) is compared to the in situ measured reflectances. Water turbidities across the matchups in the Belgian Coastal Zone are about 20–100 FNU, and the overall performance is best for ACOLITE and L2-WFR, with the former providing lowest relative (Mean Absolute Relative Difference, MARD 7–27%) and absolute errors (Mean Average Difference, MAD -0.002, Root Mean Squared Difference, RMSD 0.01–0.016) in the bands between 442 and 681 nm. L2-WFR provides the lowest errors at longer NIR wavelengths (754–885 nm). The algorithms that assume a water reflectance model, i.e. POLYMER and C2RCC, are at present not very suitable for processing imagery over the turbid Belgian coastal waters, with especially the latter introducing problems in the 665 and 709 nm bands, and hence the chlorophyll-a and turbidity retrievals. This may be caused by their internal model and/or training dataset not being well adapted to the waters encountered in the BCZ. The 1020 nm band is used most frequently by ACOLITE/DSF for the estimation of the atmospheric path reflectance (67% of matchups), indicating its usefulness for turbid water atmospheric correction. Turbidity retrieval using a single band algorithm showed good performance for L2-WFR and ACOLITE compared to PANTHYR for e.g. the 709 nm band (MARD 15 and 17%), where their reflectances were also very close to the in situ observations (MARD 11%). For the retrieval of chlorophyll-a, all methods except C2RCC gave similar performance, due to the RedEdge band-ratio algorithm being robust to typical spectrally flat atmospheric correction errors. C2RCC does not retain the spectral relationship in the Red and RedEdge bands, and hence its chlorophyll-a concentration retrieval is not at all reliable in Belgian coastal waters. L2-WFR and ACOLITE show similar performance compared to in situ radiometry, but due to the assumption of spatially consistent aerosols, ACOLITE provides less noisy products. With the superior performance of ACOLITE in the 490–681 nm wavelength range, and smoother output products, it can be recommended for processing of S3/OLCI data in turbid waters similar to those encountered in the BCZ. The ACOLITE processor for OLCI and the in situ matchup dataset used here are made available under an open source license. Numéro de notice : A2021-476 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112284 Date de publication en ligne : 12/02/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112284 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97116
in Remote sensing of environment > Vol 256 (April 2020) . - n° 112284[article]Automatic atmospheric correction for shortwave hyperspectral remote sensing data using a time-dependent deep neural network / Jian Sun in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)
[article]
Titre : Automatic atmospheric correction for shortwave hyperspectral remote sensing data using a time-dependent deep neural network Type de document : Article/Communication Auteurs : Jian Sun, Auteur ; Fangcao Xu, Auteur ; Guido Cervone, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 117 - 131 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] correction atmosphérique
[Termes IGN] détection de cible
[Termes IGN] image hyperspectrale
[Termes IGN] modèle de transfert radiatif
[Termes IGN] rayonnement solaire
[Termes IGN] réflectivitéRésumé : (auteur) Atmospheric correction is an essential step in hyperspectral imaging and target detection from spectrometer remote sensing data. State-of-the-art atmospheric correction approaches either require extensive filed experiments or prior knowledge of atmospheric characteristics to improve the predicted accuracy, which are computational expensive and unsuitable for real time application. To take full advantages of remote sensing observation in quickly and reliably acquiring data for a large area, an automatic and efficient processing tool is required for atmospheric correction. In this paper, we propose a time-dependent neural network for automatic atmospheric correction and target detection using multi-scan hyperspectral data under different elevation angles. In addition to the total radiance, the collection day and time are also incorporated to improve the time-dependency of the network and represent the seasonal and diurnal characteristics of atmosphere and solar radiation. Results show that the proposed network has the capacity to accurately provide atmospheric characteristics and estimate precise reflectivity spectra with 95,72% averaged accuracy for different materials, including vegetation, sea ice, and ocean. Additional experiments are designed to investigate the network’s temporal dependency and performance on missing data. The error analysis confirms that our proposed network is capable of estimating atmospheric characteristics under both seasonally and diurnally varying environments and handling the influence of missing data. Both the predicted results and error analysis are promising and demonstrate that our network has the ability of providing accurate atmospheric correction and target detection in real time. Numéro de notice : A2021-208 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.02.007 Date de publication en ligne : 24/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.02.007 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97186
in ISPRS Journal of photogrammetry and remote sensing > vol 174 (April 2021) . - pp 117 - 131[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2021041 SL Revue Centre de documentation Revues en salle Disponible 081-2021043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Impact of atmospheric correction on spatial heterogeneity relations between land surface temperature and biophysical compositions / Xin-Ming Zhu in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)
[article]
Titre : Impact of atmospheric correction on spatial heterogeneity relations between land surface temperature and biophysical compositions Type de document : Article/Communication Auteurs : Xin-Ming Zhu, Auteur ; Xiao-Ning Song, Auteur ; Pei Leng, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2680 - 2697 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Chine
[Termes IGN] correction atmosphérique
[Termes IGN] hétérogénéité spatiale
[Termes IGN] image Landsat-8
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] régression
[Termes IGN] température au sol
[Termes IGN] variable biophysique (végétation)Résumé : (Auteur) Investigating the relations between land surface temperature (LST) and biophysical compositions can help the understanding of the surface biophysical process. However, there are still uncertainties in determining the impacts of biophysical compositions on LST due to the atmospheric effects. In this article, four atmospheric correction algorithms were used to correct 12 Landsat 8 images in Xi’an, Beijing, Wuhan, and Guangzhou, China, including the Atmospheric Correction for Flat Terrain (ATCOR2), Quick Atmospheric Correction (QUAC), Fast Line-of-sight Atmospheric Analysis of Spectral Hypercube (FLAASH), and Second Simulation of Satellite Signal in the Solar Spectrum (6S). Then, geodetector was used to investigate the atmospheric correction differences in the spatial heterogeneity relationships between LST and normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), and bare soil index (BSI). Results indicate that the selected composition factors were greatly improved after atmospheric correction, and the relations between LST and three factors were characterized by obvious atmospheric correction differences in four study areas. On the whole, the 6S algorithm performed the best in improving the factor values and impacting the spatial heterogeneity relations between LST and biophysical compositions, followed by FLAASH, QUAC, and ATCOR2 algorithms. Except for Wuhan, 6S, FLAASH, and QUAC algorithms significantly enhanced the correlation between LST and NDVI. However, all algorithms weakened the correlations between LST, NDVI, and BSI, except Guangzhou. These findings have been verified using the regression analysis. In addition, with geodetector, combinations of any two composition factors all had strongly enhanced impacts on LST, and a combination between NDVI and NDBI performed the strongest in most cases. Numéro de notice : A2021-219 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3002821 Date de publication en ligne : 26/06/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3002821 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97211
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 3 (March 2021) . - pp 2680 - 2697[article]Coastal water remote sensing from sentinel-2 satellite data using physical, statistical, and neural network retrieval approach / Frank S. Marzano in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)PermalinkPerformance of 6 different global navigation satellite system receivers at low latitude under moderate and strong scintillation / E.R. de Paula in Earth and space science, vol 8 n° 2 (February 2021)PermalinkEvaluation of multipath mitigation performance using signal-to-noise ratio (SNR) based signal selection methods / Valanon Uaratanawong in Journal of applied geodesy, vol 15 n° 1 (January 2021)PermalinkPermalinkHigh accuracy terrestrial positioning based on time delay and carrier phase using wideband radio signals / Han Dun (2021)PermalinkA new method for improving the performance of an ionospheric model developed by multi-instrument measurements based on artificial neural network / Wang Li in Advances in space research, vol 67 n° 1 (January 2021)PermalinkSBAS-aided GPS positioning with an extended ionosphere map at the boundaries of WAAS service area / Mingyu Kim in Remote sensing, vol 13 n° 1 (January-1 2021)PermalinkEvaluation of single-frequency receivers for studying crustal deformation at the longitudinal Valley fault, eastern Taiwan / Horng-Yue Chen in Survey review, vol 52 n° 374 (August 2020)PermalinkRaytracing atmospheric delays in ground-based GNSS reflectometry / T. Nicolaidou in Journal of geodesy, vol 94 n° 8 (August 2020)PermalinkComplete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China / Kun Tan in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)PermalinkStochastic modeling for VRS network-based GNSS RTK with residual interpolation uncertainty / Thanate Jongrujinan in Journal of applied geodesy, vol 14 n° 3 (July 2020)PermalinkThe geometric imaging model for high-resolution optical remote sensing satellites considering light aberration and atmospheric refraction errors / Mi Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 6 (June 2020)PermalinkValidation of Sentinel-3A SRAL coastal sea level data at high posting rate: 80 Hz / Ana Aldarias in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkA water identification method basing on grayscale Landsat 8 OLI images / Zhitian Deng in Geocarto international, vol 35 n° 7 ([15/05/2020])PermalinkAntenna phase center correction differences from robot and chamber calibrations: the case study LEIAR25 / Grzegorz Krzan in GPS solutions, vol 24 n° 2 (April 2020)PermalinkEstimation and representation of regional atmospheric corrections for augmenting real-time single-frequency PPP / Peiyuan Zhou in GPS solutions, vol 24 n° 1 (January 2020)PermalinkPermalinkSimulation d’éclairements des surfaces ombrées en zone urbaine par transfert radiatif 3D (modèle DART) / Yulu Xi (2020)PermalinkAnalysis of higher-order ionospheric effects on GNSS precise point positioning in the China area / Yaozong Zhou in Survey review, vol 51 n° 368 (September 2019)PermalinkEvaluating the impact of higher-order ionospheric corrections on multi-GNSS ultra-rapid orbit determination / Xinghan Chen in Journal of geodesy, vol 93 n° 9 (September 2019)Permalink