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Documents disponibles écrits par cet auteur (2731)
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Ionospheric irregularity layer height and thickness estimation with a GNSS receiver array / Seebany Datta-Barua in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
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Titre : Ionospheric irregularity layer height and thickness estimation with a GNSS receiver array Type de document : Article/Communication Auteurs : Seebany Datta-Barua, Auteur ; Yang Su, Auteur ; Aurora López Rubio, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 6198 - 6207 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] Alaska (Etats-Unis)
[Termes IGN] hauteur de la couche ionosphérique
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle ionosphérique
[Termes IGN] phase GNSS
[Termes IGN] rapport signal sur bruit
[Termes IGN] scintillation
[Termes IGN] série temporelle
[Termes IGN] signal GNSSRésumé : (auteur) This work develops a method by which a kilometer-spaced array of Global Navigation Satellite System (GNSS) scintillation receivers can be used to estimate the ionospheric irregularity layer height and thickness and associated uncertainties on those estimates. Spectra of filtered signal power and phase data are used to estimate these quantities by comparing the observed ratio of the log of the power spectrum to the phase spectrum with the Rytov weak scatter theoretical ratio. A Monte Carlo simulation of noise on the input signal and the irregularity drift velocity is used to quantify the error in estimates of height and thickness. The method is tested using data from the Scintillation Auroral Global Positioning System (GPS) Array (SAGA) sited in the auroral zone at Poker Flat Research Range, Alaska. For the 30-min scintillation period studied, the technique identifies ionospheric scattering from a thick F layer, which correlates well with on-site incoherent scatter radar measurements of peak electron density, for an event previously identified in the literature as likely due to F layer. Numéro de notice : A2021-539 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1109/TGRS.2020.3024173 Date de publication en ligne : 12/10/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3024173 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98013
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 7 (July 2021) . - pp 6198 - 6207[article]Machine learning for inference: using gradient boosting decision tree to assess non-linear effects of bus rapid transit on house prices / Linchuan Yang in Annals of GIS, vol 27 n° 3 (July 2021)
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Titre : Machine learning for inference: using gradient boosting decision tree to assess non-linear effects of bus rapid transit on house prices Type de document : Article/Communication Auteurs : Linchuan Yang, Auteur ; Yuan Liang, Auteur ; Qing Zhu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 273 - 284 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de la valeur
[Termes IGN] apprentissage automatique
[Termes IGN] arbre de décision
[Termes IGN] bien immobilier
[Termes IGN] boosting adapté
[Termes IGN] Chine
[Termes IGN] Extreme Gradient Machine
[Termes IGN] inférence
[Termes IGN] logement
[Termes IGN] transport publicRésumé : (auteur) The adoption of bus rapid transit (BRT) systems has gained worldwide popularity over the past several decades. China is no exception as it has long been aiming at promoting public transportation. Prior studies have provided extensive evidence that BRT has substantial effects on house prices with traditional econometric techniques, such as hedonic pricing models. However, few of those investigations have discussed the non-linear relationship between BRT and house prices. Using the Xiamen data, this study employs a machine learning technique, namely the gradient boosting decision tree (GBDT), to scrutinize the non-linear relationship between BRT and house prices. This study documents a positive association between accessibility to BRT stations and house prices and a negative association between proximity to the BRT corridor and house prices. Moreover, it suggests a non-linear relationship between BRT and house prices and indicates that GBDT has more substantial predictive power than hedonic pricing models. Numéro de notice : A2021-629 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1080/19475683.2021.1906746 Date de publication en ligne : 27/03/2021 En ligne : https://doi.org/10.1080/19475683.2021.1906746 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98270
in Annals of GIS > vol 27 n° 3 (July 2021) . - pp 273 - 284[article]Mapping sandy land using the new sand differential emissivity index from thermal infrared emissivity data / Shanshan Chen in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
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Titre : Mapping sandy land using the new sand differential emissivity index from thermal infrared emissivity data Type de document : Article/Communication Auteurs : Shanshan Chen, Auteur ; Huazhong Ren, Auteur ; Rongyuan Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 5464 - 5478 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] désertification
[Termes IGN] détection de changement
[Termes IGN] distribution spatiale
[Termes IGN] ensablement
[Termes IGN] image TASI
[Termes IGN] image Terra-ASTER
[Termes IGN] image thermique
[Termes IGN] sable
[Termes IGN] Sinkiang (Chine)Résumé : (auteur) On the basis of the spectral shape of thermal infrared (TIR) emissivity for sandy land, a remote sensing sand index called the sand differential emissivity index (SDEI) is proposed in this article to simply and conveniently detect sandy land over large areas. The SDEI is evaluated on ground, airborne, and spaceborne thermal emissivity data, and it shows good characterization of sandy land and performs better in sandy land identification than two previous indices. The SDEI was also evaluated in the transition zones of China’s four mega-sandy lands and was applied to long-term land surface emissivity to obtain the spatial distribution and variation in China’s sandy land from 2000 to 2016. The findings showed that a mean accuracy of 96% and a mean kappa coefficient of 0.83 were obtained in the transition zones, and the sandy land in the transition zone exhibited a decreasing trend over the past 17 years and a significant decline in the Mu Us sandy land. Meanwhile, the sandy land area in China decreased by 3.6×104 km 2 (1.53%) by the end of 2016 compared with that in early 2000. Numéro de notice : A2021-527 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3022772 Date de publication en ligne : 25/09/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3022772 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97977
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 7 (July 2021) . - pp 5464 - 5478[article]Multi-scale coal fire detection based on an improved active contour model from Landsat-8 satellite and UAV images / Yanyan Gao in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)
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Titre : Multi-scale coal fire detection based on an improved active contour model from Landsat-8 satellite and UAV images Type de document : Article/Communication Auteurs : Yanyan Gao, Auteur ; Ming Hao, Auteur ; Yunjia Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 449 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] charbon
[Termes IGN] classification floue
[Termes IGN] classification par nuées dynamiques
[Termes IGN] détection de contours
[Termes IGN] image captée par drone
[Termes IGN] image Landsat-8
[Termes IGN] incendie
[Termes IGN] Sinkiang (Chine)
[Termes IGN] température au solRésumé : (auteur) Underground coal fires can increase surface temperature, cause surface cracks and collapse, and release poisonous and harmful gases, which significantly harm the ecological environment and humans. Traditional methods of extracting coal fires, such as global threshold, K-mean and active contour model, usually produce many false alarms. Therefore, this paper proposes an improved active contour model by introducing the distinguishing energies of coal fires and others into the traditional active contour model. Taking Urumqi, Xinjiang, China as the research area, coal fires are detected from Landsat-8 satellite and unmanned aerial vehicle (UAV) data. The results show that the proposed method can eliminate many false alarms compared with some traditional methods, and achieve detection of small-area coal fires by referring field survey data. More importantly, the results obtained from UAV data can help identify not only burning coal fires but also potential underground coal fires. This paper provides an efficient method for high-precision coal fire detection and strong technical support for reducing environmental pollution and coal energy use. Numéro de notice : A2021-552 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10070449 Date de publication en ligne : 30/06/2021 En ligne : https://doi.org/10.3390/ijgi10070449 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98084
in ISPRS International journal of geo-information > vol 10 n° 7 (July 2021) . - n° 449[article]Multisensor data fusion for cloud removal in global and all-season Sentinel-2 imagery / Patrick Ebel in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
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Titre : Multisensor data fusion for cloud removal in global and all-season Sentinel-2 imagery Type de document : Article/Communication Auteurs : Patrick Ebel, Auteur ; Andrea Meraner, Auteur ; Michael Schmitt, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 5866 - 5878 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] détection des nuages
[Termes IGN] données multicapteurs
[Termes IGN] image Sentinel-MSI
[Termes IGN] nuage
[Termes IGN] reconstruction d'image
[Termes IGN] réseau antagoniste génératifRésumé : (auteur) The majority of optical observations acquired via spaceborne Earth imagery are affected by clouds. While there is numerous prior work on reconstructing cloud-covered information, previous studies are, oftentimes, confined to narrowly defined regions of interest, raising the question of whether an approach can generalize to a diverse set of observations acquired at variable cloud coverage or in different regions and seasons. We target the challenge of generalization by curating a large novel data set for training new cloud removal approaches and evaluate two recently proposed performance metrics of image quality and diversity. Our data set is the first publically available to contain a global sample of coregistered radar and optical observations, cloudy and cloud-free. Based on the observation that cloud coverage varies widely between clear skies and absolute coverage, we propose a novel model that can deal with either extreme and evaluate its performance on our proposed data set. Finally, we demonstrate the superiority of training models on real over synthetic data, underlining the need for a carefully curated data set of real observations. To facilitate future research, our data set is made available online. Numéro de notice : A2021-529 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3024744 Date de publication en ligne : 02/10/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3024744 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97980
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 7 (July 2021) . - pp 5866 - 5878[article]Phenotypic variability and differences in the drought response of Norway spruce pendula and pyramidalis half-sib families / Marius Budeanu in Forests, vol 12 n° 7 (July 2021)
PermalinkRemote sensing image colorization using symmetrical multi-scale DCGAN in YUV color space / Min Wu in The Visual Computer, vol 37 n° 7 (July 2021)
PermalinkReview of spectral indices for urban remote sensing / Akib Javed in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 7 (July 2021)
PermalinkRoad-network-based fast geolocalization / Yongfei Li in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
PermalinkA scalable method to construct compact road networks from GPS trajectories / Yuejun Guo in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)
PermalinkSemantic-aware label placement for augmented reality in street view / Jianqing Jia in The Visual Computer, vol 37 n° 7 (July 2021)
PermalinkSemiCDNet: A semisupervised convolutional neural network for change detection in high resolution remote-sensing images / Daifeng Peng in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
PermalinkTarget-constrained interference-minimized band selection for hyperspectral target detection / Xiaodi Shang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
PermalinkThe point-descriptor-precedence representation for point configurations and movements / Amna Qayyum in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)
PermalinkThree-dimensional reconstruction of single input image based on point cloud / Yu Hou in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 7 (July 2021)
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