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Harvested area did not increase abruptly-how advancements in satellite-based mapping led to erroneous conclusions / Johannes Breidenbach in Annals of Forest Science [en ligne], vol 79 n° 1 (December 2022)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 79 n° 1 (December 2022) . - n° 2 Titre : Harvested area did not increase abruptly-how advancements in satellite-based mapping led to erroneous conclusions Type de document : Article/Communication Auteurs : Johannes Breidenbach, Auteur ; David Ellison, Auteur ; Hans Petersson, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 2 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] changement climatique [Termes IGN] données spatiotemporelles [Termes IGN] Finlande [Termes IGN] image à haute résolution [Termes IGN] image Landsat [Termes IGN] inventaire forestier étranger (données) [Termes IGN] précision de l'estimation [Termes IGN] récolte de bois [Termes IGN] Suède [Termes IGN] surface forestière [Termes IGN] Union Européenne Résumé : (Auteur) Using satellite-based maps, Ceccherini et al. (Nature 583:72-77, 2020) report abruptly increasing harvested area estimates in several EU countries beginning in 2015. Using more than 120,000 National Forest Inventory observations to analyze the satellite-based map, we show that it is not harvested area but the map’s ability to detect harvested areas that abruptly increases after 2015 in Finland and Sweden. Numéro de notice : A2022-068 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s13595-022-01120-4 Date de publication en ligne : 22/02/2022 En ligne : https://doi.org/10.1186/s13595-022-01120-4 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100013 [article]

Combined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation / Narissara Nuthammachot in Geocarto international, vol 37 n° 2 ([15/01/2022])  

Public [article]  inGeocarto international > vol 37 n° 2 [15/01/2022] . - pp 366 - 376 Titre : Combined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation Type de document : Article/Communication Auteurs : Narissara Nuthammachot, Auteur ; Askar Askar, Auteur ; Dimitris Stratoulias, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 366 - 376 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] biomasse aérienne [Termes IGN] corrélation [Termes IGN] échantillonnage de données [Termes IGN] forêt privée [Termes IGN] fusion d'images [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] indice de végétation [Termes IGN] Indonésie [Termes IGN] précision de l'estimation Résumé : (auteur) Above-ground Biomass (AGB) represents the largest amount of biomass found on earth. Passive and active remote sensors have been a useful tool in estimating AGB for this purpose; nevertheless, both data sources suffer from saturation problems in dense vegetation. A combination of optical and radar data could potentially increase the accuracy of AGB estimation. In this study we evaluate the synergistic use of Sentinel-1 and Sentinel-2 for assessing AGB in a private forest in Yogyakarta, Indonesia. Forty five sample plots of 20 m x 20 m were used as ground truth data. AGB correlated with Sentinel-1 backscatter and Sentinel-2 derived variables with R2 = 0.34 and R2 = 0.82, respectively; nevertheless, the synergistic use of Sentinel-1 and Sentinel-2 yielded the highest accuracy (i.e., R2 = 0.84). The results indicate that AGB in Yogyakarta is most accurately estimated based on the synergy of optical and radar satellite images. Numéro de notice : A2022-049 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1726507 Date de publication en ligne : 13/02/2020 En ligne : https://doi.org/10.1080/10106049.2020.1726507 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99440 [article]

GPS satellite differential code bias estimation with current eleven low earth orbit satellites / Xingxing Li in Journal of geodesy, vol 95 n° 7 (July 2021)  

Public [article]  inJournal of geodesy > vol 95 n° 7 (July 2021) . - n° 76 Titre : GPS satellite differential code bias estimation with current eleven low earth orbit satellites Type de document : Article/Communication Auteurs : Xingxing Li, Auteur ; Wei Zhang, Auteur ; Keke Zhang, Auteur Année de publication : 2021 Article en page(s) : n° 76 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] erreur systématique de code différentiel [Termes IGN] orbite basse [Termes IGN] précision de l'estimation [Termes IGN] récepteur GPS [Termes IGN] teneur verticale totale en électrons [Termes IGN] trajet multiple Résumé : (auteur) Many low earth orbit (LEO) missions have been launched recently for different geoscience studying purposes such as ionosphere detecting and gravity recovering. The onboard observations from LEO satellites provide us a great opportunity to estimate the differential code bias (DCB) which is vital for precise applications of global navigation satellites system. This paper mainly focuses on the contribution of multi-LEO combination to the DCB estimation using onboard data collected by current eleven LEO satellites from day of year (DOY) 061, 2018 to DOY 120, 2018. The single-LEO solutions with different LEO and multi-LEO solutions with different LEO subsets are compared and analyzed in detail to fully exploit the potential of LEO onboard observations in the DCB estimation. We also evaluate and discuss the vertical total electron content (VTEC) results and posterior residuals to validate the estimation accuracy. Our results show that the average DCB standard deviation (STD) values are within 0.140 ns for all eleven single-LEO solutions with the best stability of 0.082 ns for Swarm-B solution. The evaluation of multi-LEO solutions indicates that with the increase in LEO satellites, the GPS DCB stability gets improved gradually. The 9-LEO solution can achieve the stability with STD value of 0.051 ns, better than that of DCB products from the German Aerospace Center (DLR) (0.055 ns) but slightly worse than that of DCB products from the Chinese Academy of Sciences (CAS) (0.048 ns). The results suggest that the GPS DCB stability based on the onboard observations of nine LEO satellites can be comparable to the ground-based solution derived from a global ground network with hundreds of stations. The LEO space-borne receiver DCB results illustrate that the inclusion of more LEO satellites can contribute to the stability improvement of receiver DCB. In addition, the VTEC estimation can benefit from the joint processing of multiple LEO observations and achieves a noticeable reduction in the percentage of negative VTEC values. Our results also reveal that the spherical symmetry ionosphere assumption might cause accuracy degradation in the DCB estimation at low latitudes. Numéro de notice : A2021-517 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01536-2 Date de publication en ligne : 22/06/2021 En ligne : https://doi.org/10.1007/s00190-021-01536-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97939 [article]

Recurrent neural network for rain estimation using commercial microwave links / Hai Victor Habi in IEEE Transactions on geoscience and remote sensing, vol 59 n° 5 (May 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 5 (May 2021) . - pp 3672 - 3681 Titre : Recurrent neural network for rain estimation using commercial microwave links Type de document : Article/Communication Auteurs : Hai Victor Habi, Auteur ; Hagit Messer, Auteur Année de publication : 2021 Article en page(s) : pp 3672 - 3681 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] dégradation du signal [Termes IGN] eau pluviale [Termes IGN] méthode robuste [Termes IGN] précision de l'estimation [Termes IGN] réseau neuronal récurrent Résumé : (Auteur) The use of recurrent neural networks (RNNs) to utilize measurements from commercial microwave links (CMLs) has recently gained attention. Whereas previous studies focused on the performance of methods for wet–dry classification, here we propose an RNN algorithm for estimating the rain-rate. We empirically analyzed the proposed algorithm, using real data, and compared it with the traditional power-law (PL)-based algorithm, commonly used for estimating rain from CML attenuation measurements. Our analysis shows that the data-driven RNN algorithm, when properly trained, outperforms the PL algorithm in terms of accuracy. On the other hand, the PL algorithm is simpler and more robust when dealing with a large variety of corruptions and adverse conditions. We then introduced a time normalization (TN) layer for controlling the trade-off between performance and robustness of the RNN methods, and demonstrated its performance. Numéro de notice : A2021-337 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3010305 Date de publication en ligne : 30/07/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3010305 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97568 [article]

Receiver DCB analysis and calibration in geomagnetic storm-time using IGS products / Jianfeng Li in Survey review, Vol 53 n° 377 (February 2021)  

Public [article]  inSurvey review > Vol 53 n° 377 (February 2021) . - pp 122 - 135 Titre : Receiver DCB analysis and calibration in geomagnetic storm-time using IGS products Type de document : Article/Communication Auteurs : Jianfeng Li, Auteur ; Dingfa Huang, Auteur ; Yinghao Zhao, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 122 - 135 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] erreur systématique de code différentiel [Termes IGN] international GPS service for geodynamics [Termes IGN] modèle ionosphérique [Termes IGN] perturbation ionosphérique [Termes IGN] positionnement différentiel [Termes IGN] positionnement par GNSS [Termes IGN] précision de l'estimation [Termes IGN] récepteur GNSS [Termes IGN] tempête magnétique [Termes IGN] teneur totale en électrons Résumé : (auteur) Solar activity and geomagnetic storm cause ionospheric disturbance and affect the GNSS positioning accuracy, which this effect cannot be ignored. The reliability depends mainly on differential code bias (DCB), when estimating the total electron content (TEC) with GNSS pseudorange observations. This study analyzes the variation characteristics of receiver DCB (RDCB) during a strong geomagnetic storm to determine whether the RDCB estimation is affected by space weather. Results show that the RDCB dispersion of low-latitude stations is larger than that of other areas. On the storm day, the RDCB standard deviation (STD) exhibits a peak characteristic and the number of RDCB abnormal stations is significantly more than that on quiet day. Analysis shows that the RDCB abnormality is caused by the ionospheric model misalignment during the ionospheric disturbance. By correcting the RDCB, the RDCB STD is reduced by 43.10%. Thus, the model correction can improve the estimation accuracy of RDCB during geomagnetic storm. Numéro de notice : A2021-194 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1702369 Date de publication en ligne : 15/12/2019 En ligne : https://doi.org/10.1080/00396265.2019.1702369 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97128 [article]

The effect of different sampling schemes on estimation precision of snow water equivalent (SWE) using geostatistics techniques in a semi-arid region of Iran / Hojatolah Ganjkhanlo in Geocarto international, vol 35 n° 16 ([01/12/2020])  

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High-resolution models of tropospheric delays and refractivity based on GNSS and numerical weather prediction data for alpine regions in Switzerland / Karina Wilgan in Journal of geodesy, vol 93 n°6 (June 2019)  

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Méthodes d'inventaire multisource : améliorer la précision des estimations de l'IFN et atteindre l'échelle des territoires [diaporama] / Cédric Vega (2018)  

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Modèle d'interaction et performances du traitement du signal multimodal / Saloua Chlaily (2018)  

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Per-pixel bias-variance decomposition of continuous errors in data-driven geospatial modeling : A case study in environmental remote sensing / Jing Gao in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)  

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Second iteration of photogrammetric pipeline to enhance the accuracy of image pose estimation / Truong Giang Nguyen (2017)  

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