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Comparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY / Dunya Alraddawi in Atmospheric measurement techniques, vol 11 n° 5 (May 2018)  

Public [article]  inAtmospheric measurement techniques > vol 11 n° 5 (May 2018) . - pp 2949 - 2965 Titre : Comparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY Type de document : Article/Communication Auteurs : Dunya Alraddawi, Auteur ; Alain Sarkissian, Auteur ; Philippe Keckhut, Auteur ; Olivier Bock , Auteur ; Stefan Noël, Auteur ; Slimane Bekki, Auteur ; Abdanour Irbah, Auteur ; Mustapha Meftah, Auteur ; Chantal Claud, Auteur Année de publication : 2018 Article en page(s) : pp 2949 - 2965 Note générale : bibliographie This work was developed in the framework of the VEGA project and supported by the French program LEFE/INSU. This work is a contribution to the European COST Action ES1206 GNSS4SWEC (GNSS for Severe Weather and Climate monitoring; http://www.cost.eu/COST_Actions/essem/ES1206, last access: 15 May 2018) aiming at the development of the global GNSS network for atmospheric research and climate change monitoring. Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] Arctique [Termes descripteurs IGN] Atmospheric Infrared Sounder [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] image Aqua-MODIS [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] nébulosité [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] teneur en vapeur d'eau Résumé : (auteur) Atmospheric water vapour plays a key role in the Arctic radiation budget, hydrological cycle and hence climate, but its measurement with high accuracy remains an important challenge. Total column water vapour (TCWV) datasets derived from ground-based GNSS measurements are used to assess the quality of different existing satellite TCWV datasets, namely from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Atmospheric Infrared Sounder (AIRS) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The comparisons between GNSS and satellite data are carried out for three reference Arctic observation sites (Sodankylä, Ny-Ålesund and Thule) where long homogeneous GNSS time series of more than a decade (2001–2014) are available. We select hourly GNSS data that are coincident with overpasses of the different satellites over the three sites and then average them into monthly means that are compared with monthly mean satellite products for different seasons. The agreement between GNSS and satellite time series is generally within 5 % at all sites for most conditions. The weakest correlations are found during summer. Among all the satellite data, AIRS shows the best agreement with GNSS time series, though AIRS TCWV is often slightly too high in drier atmospheres (i.e. high-latitude stations during autumn and winter). SCIAMACHY TCWV data are generally drier than GNSS measurements at all the stations during the summer. This study suggests that these biases are associated with cloud cover, especially at Ny-Ålesund and Thule. The dry biases of MODIS and SCIAMACHY observations are most pronounced at Sodankylä during the snow season (from October to March). Regarding SCIAMACHY, this bias is possibly linked to the fact that the SCIAMACHY TCWV retrieval does not take accurately into account the variations in surface albedo, notably in the presence of snow with a nearby canopy as in Sodankylä. The MODIS bias at Sodankylä is found to be correlated with cloud cover fraction and is also expected to be affected by other atmospheric or surface albedo changes linked for instance to the presence of forests or anthropogenic emissions. Overall, the results point out that a better estimation of seasonally dependent surface albedo and a better consideration of vertically resolved cloud cover are recommended if biases in satellite measurements are to be reduced in the polar regions. Numéro de notice : A2018-240 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/amt-11-2949-2018 date de publication en ligne : 18/05/2018 En ligne : https://doi.org/10.5194/amt-11-2949-2018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90215 [article]

Enhanced MODIS atmospheric total water vapour content trends in response to Arctic amplification / Dunya Alraddawi in Atmosphere, vol 8 n° 12 (December 2017)  

Public [article]  inAtmosphere > vol 8 n° 12 (December 2017) Titre : Enhanced MODIS atmospheric total water vapour content trends in response to Arctic amplification Type de document : Article/Communication Auteurs : Dunya Alraddawi, Auteur ; Philippe Keckhut, Auteur ; Alain Sarkissian, Auteur ; Olivier Bock , Auteur ; Abdanour Irbah, Auteur ; Slimane Bekki, Auteur ; Chantal Claud, Auteur ; Mustapha Meftah, Auteur Année de publication : 2017 Projets : VEGA (LEFE/INSU) / Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] Arctique [Termes descripteurs IGN] Arctique, océan [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] Groenland [Termes descripteurs IGN] image Aqua-MODIS [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] Svalbard [Termes descripteurs IGN] température de surface de la mer [Termes descripteurs IGN] teneur en vapeur d'eau Résumé : (auteur) In order to assess the strength of the water vapour feedback within Arctic climate change, 15 years of the total column-integrated density of water vapour (TCWV) from the moderate resolution imaging spectrometer (MODIS) are analysed. Arctic TCWV distribution, trends, and anomalies for the 2001–2015 period, broken down into seasons and months, are analysed. Enhanced local spring TCWV trends above the terrestrial Arctic regions are discussed in relation to land snow cover and vegetation changes. Upward TCWV trends above the oceanic areas are discussed in lien with sea ice extent and sea surface temperature changes. Increased winter TCWV (up to 40%) south of the Svalbard archipelago are observed; these trends are probably driven by a local warming and sea ice extent decline. Similarly, the Barents/Kara regions underwent wet trends (up to 40%), also associated with winter/fall local sea ice loss. Positive late summer TCWV trends above the western Greenland and Beaufort seas (about 20%) result from enhanced upper ocean warming and thereby a local coastal decline in ice extent. The Mackenzie and Siberia enhanced TCWV trends (about 25%) during spring are found to be associated with coincident decreased snow cover and increased vegetation, as a result of the earlier melt onset. Results show drier summers in the Eurasia and western Alaska regions, thought to be affected by changes in albedo from changing vegetation. Other TCWV anomalies are also presented and discussed in relation to the dramatic decline in sea ice extent and the exceptional rise in sea surface temperature. Numéro de notice : A2017-858 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/atmos8120241 date de publication en ligne : 02/12/2017 En ligne : https://doi.org/10.3390/atmos8120241 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89835 [article]

Fusing microwave and optical satellite observations to simultaneously retrieve surface soil moisture, vegetation water content, and surface soil roughness / Yohei Sawada in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 11 (November 2017) . - pp 6195 - 6206 Titre : Fusing microwave and optical satellite observations to simultaneously retrieve surface soil moisture, vegetation water content, and surface soil roughness Type de document : Article/Communication Auteurs : Yohei Sawada, Auteur ; Toshio Koike, Auteur ; Kentaro Aida, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 6195 - 6206 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image Aqua-AMSR [Termes descripteurs IGN] image Aqua-MODIS [Termes descripteurs IGN] image optique [Termes descripteurs IGN] image radar [Termes descripteurs IGN] rugosité du sol [Termes descripteurs IGN] teneur en eau de la végétation Résumé : (Auteur) Uncertainty in surface soil roughness strongly degrades the performance of surface soil moisture (SSM) and vegetation water content (VWC) retrieval from passive microwave observations. This paper proposes an algorithm to objectively determine the surface soil roughness parameter of the radiative transfer model by fusing microwave and optical satellite observations. It is then demonstrated in a semiarid in situ observation site. The roughness correction of this new algorithm positively impacted the performance of SSM (root-mean-square error reduced from 0.088 to 0.070) and VWC retrieval from the Advanced Microwave Scanning Radiometer 2 and Moderate Resolution Imaging Spectroradiometer. Since this surface soil roughness correction may be transferrable to other microwave satellite retrieval algorithms such as those for the Soil Moisture and Ocean Salinity and Soil Moisture Active Passive satellites, this new algorithm can contribute to many microwave earth surface observation satellite missions. Numéro de notice : A2017-746 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2722468 En ligne : https://doi.org/10.1109/TGRS.2017.2722468 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88781 [article]

Atmospheric correction over coastal waters using multilayer neural networks / Yongzhen Fan in Remote sensing of environment, vol 199 (15 September 2017)  

Public [article]  inRemote sensing of environment > vol 199 (15 September 2017) . - pp 218 - 240 Titre : Atmospheric correction over coastal waters using multilayer neural networks Type de document : Article/Communication Auteurs : Yongzhen Fan, Auteur ; Wei Li, Auteur ; Charles K. Gatebe, Auteur ; Cédric Jamet, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 218 - 240 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] correction atmosphérique [Termes descripteurs IGN] couleur de l'océan [Termes descripteurs IGN] eaux côtières [Termes descripteurs IGN] image Aqua-MODIS [Termes descripteurs IGN] Perceptron multicouche [Termes descripteurs IGN] transfert radiatif Résumé : (auteur) Standard atmospheric correction (AC) algorithms work well in open ocean areas where the water inherent optical properties (IOPs) are correlated with pigmented particles. However, the IOPs of turbid coastal waters may independently vary with pigmented particles, suspended inorganic particles, and colored dissolved organic matter (CDOM). In turbid coastal waters standard AC algorithms often exhibit large inaccuracies that may lead to negative water-leaving radiances (Lw) or remote sensing reflectance (Rrs). We introduce a new atmospheric correction algorithm for coastal waters based on a multilayer neural network (MLNN) method. We use a coupled atmosphere-ocean radiative transfer model to simulate the Rayleigh-corrected radiance (Lrc) at the top of the atmosphere (TOA) and the Rrs just above the surface simultaneously, and train a MLNN to derive the aerosol optical depth (AOD) and Rrs directly from the TOA Lrc. The method is validated using both a synthetic dataset and Aerosol Robotic Network – Ocean Color (AERONET–OC) measurements. The SeaDAS NIR algorithm, the SeaDAS NIR/SWIR algorithm, and the MODIS version of the Case 2 regional water - CoastColour (C2RCC) algorithm are also included in the comparison with AERONET–OC measurements. The performance of the AC algorithms is evaluated with four statistical metrics: the Pearson correlation coefficient (R), the average percentage difference (APD), the mean percentage bias, and the root mean square difference (RMSD). The comparison with AERONET–OC measurements shows that the MLNN algorithm significantly improves retrieval of normalized Lw in blue bands (412 nm and 443 nm) and yields minor improvements in green and red bands compared with the other three algorithms. On a global scale, the MLNN algorithm reduces APD in normalized Lw by up to 13% in blue bands and by 2–7% in green and red bands when compared with the standard SeaDAS NIR algorithm. In highly absorbing coastal waters, such as the Baltic Sea, the MLNN algorithm reduces APD in normalized Lw by more than 60% in blue bands compared to the standard SeaDAS NIR algorithm, while in highly scattering coastal waters, such as the Black Sea, the MLNN algorithm reduces APD by more than 25%. These results indicate that the MLNN algorithm is suitable for application in turbid coastal waters. Application of the MLNN algorithm to MODIS Aqua images in several coastal areas also shows that it is robust and resilient to contamination due to sunglint or adjacency effects of land and cloud edges. The MLNN algorithm is very fast once the neural network has been properly trained and is therefore suitable for operational use. A significant advantage of the MLNN algorithm is that it does not need SWIR bands. Numéro de notice : A2017-417 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : https://doi.org/10.1016/j.rse.2017.07.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86310 [article]

An adaptive weighted tensor completion method for the recovery of remote sensing images with missing data / Michael Kwok-Po Ng in IEEE Transactions on geoscience and remote sensing, vol 55 n° 6 (June 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 6 (June 2017) . - pp 3367 - 3381 Titre : An adaptive weighted tensor completion method for the recovery of remote sensing images with missing data Type de document : Article/Communication Auteurs : Michael Kwok-Po Ng, Auteur ; Qiangqiang Yuan, Auteur ; Li Yan, Auteur ; Jing Sun, Auteur Année de publication : 2017 Article en page(s) : pp 3367 - 3381 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] bande spectrale [Termes descripteurs IGN] complétion [Termes descripteurs IGN] détection de partie cachée [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] image Aqua-MODIS [Termes descripteurs IGN] spectroradiométrie [Termes descripteurs IGN] tenseur Résumé : (Auteur) Missing information, such as dead pixel values and cloud effects, is very common image quality degradation problems in remote sensing. Missing information can reduce the accuracy of the subsequent image processing, in applications such as classification, unmixing, and target detection, and even the quantitative retrieval process. The main aim of this paper is to study an adaptive weighted tensor completion (AWTC) method for the recovery of remote sensing images with missing data. Our idea is to collectively make use of the spatial, spectral, and temporal information to build a new weighted tensor low-rank regularization model for recovering the missing data. In the model, the weights are determined adaptively by considering the contribution of the spatial, spectral, and temporal information in each dimension. Experimental results based on both simulated and real data sets are presented to verify that the proposed method can recover missing data, and its performance is found to be better than the other tested methods. In the simulated experiments, the peak signal-to-noise ratio is improved by more than 3 dB, compared with the original tensor completion model. In the real data experiments, the proposed AWTC model can better recover the dead line problem in Aqua Moderate Resolution Imaging Spectroradiometer band 6 and the scan-line corrector-off problem in enhanced thematic mapper plus images, with the smallest spectral distortion. Numéro de notice : A2017-476 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1109/TGRS.2017.2670021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86401 [article]

The MODIS cloud optical and microphysical products : collection 6 updates and examples from terra and aqua / Steven Platnick in IEEE Transactions on geoscience and remote sensing, vol 55 n° 1 (January 2017)  

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A robust fixed rank kriging method for improving the spatial completeness and accuracy of satellite SST products / Yuxin Zhu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)  

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Measuring the directional variations of land surface reflectance from MODIS / François-Marie Bréon in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)

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Land cover dynamics monitoring with Landsat data in Kunming, China: a cost-effective sampling and modelling scheme using Google Earth imagery and random forests / Ning Lu in Geocarto international, vol 30 n° 1 - 2 (January - February 2015)

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MODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests / Tomáš Hlásny in Annals of Forest Science [en ligne], vol 72 n° 1 (January 2015)  

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Satellite data as indicators of tree biomass growth and forest dieback in a Mediterranean holm oak forest / Romà Ogaya in Annals of Forest Science [en ligne], vol 72 n° 1 (January 2015)  

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Spatiotemporally characterizing urban temperatures based on remote sensing and GIS analysis: a case study in the city of Saskatoon (SK, Canada) / Li Shen in Open geosciences, vol 7 n° 1 (January 2015)  

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An improved dark object method to retrieve 500 m-resolution AOT (Aerosol Optical Thickness) image from MODIS data: A case study in the Pearl River Delta area, China / Lili Li in ISPRS Journal of photogrammetry and remote sensing, vol 89 (March 2014)

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Multi sensor study of hydrological changes in Caspian Sea / Ayoub Moradi (sept 2014)

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Characterization of Terra and Aqua MODIS VIS, NIR, and SWIR spectral bands' calibration stability / Aisheng Wu in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 2 (July 2013)  

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