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PPP rapid ambiguity resolution using Android GNSS raw measurements with a low-cost helical antenna / Xingxing Li in Journal of geodesy, vol 96 n° 10 (October 2022)
[article]
Titre : PPP rapid ambiguity resolution using Android GNSS raw measurements with a low-cost helical antenna Type de document : Article/Communication Auteurs : Xingxing Li, Auteur ; Hao Wang, Auteur ; Xin Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 65 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] Androïd
[Termes IGN] antenne
[Termes IGN] données GNSS
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] positionnement ponctuel précis
[Termes IGN] précision du positionnement
[Termes IGN] rapport signal sur bruit
[Termes IGN] résolution d'ambiguïté
[Termes IGN] téléphone intelligentRésumé : (auteur) The release of GNSS raw measurement acquisition privileges on Google Android makes high-precision positioning on the low-cost smart devices possible. However, influenced by the inner linearly polarized antenna, the pseudorange and carrier phase noises of the smart device are much larger than those of the geodetic receiver. As a result, only meter-level positioning accuracy can be obtained based on the smart device’s original antenna. With the external survey-grade antenna enhancing, positioning accuracy of decimeter-level to centimeter-level can be obtained, but it still takes tens of minutes to converge and fix the ambiguity. However, a PPP-RTK method is proposed to achieve rapid integer ambiguity resolution (AR) with the regional atmospheric augmentation. In this contribution, an uncombined PPP-RTK model is developed using Android GNSS raw measurements with an external antenna, after carefully considering the coexistence of single- and dual-frequency signals on smart devices. A low-cost helical antenna is employed to enhance the Android GNSS data as it is capable to provide observation data of comparable quality with the survey-grade antenna and has several advantages of low weight, low-power consumption, and portability. Moreover, a series of quality control methods in the data preprocessing and ambiguity resolution are proposed for smartphone-based PPP-RTK to enhance the positioning results. To validate the proposed method, several experiments are carried out using raw measurements of Xiaomi Mi8 with an external low-cost helical antenna. The result shows that the ambiguity fixed solution can be obtained within 3 min in both static and kinematic scenarios. After the ambiguity resolution, centimeter-level positioning accuracy of (1.7, 2.1, 4.1) cm and (7.2, 4.5, 8.1) cm for the east, north, and up components can be achieved in static and kinematic scenarios, respectively. Numéro de notice : A2022-735 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01661-6 Date de publication en ligne : 27/09/2022 En ligne : https://doi.org/10.1007/s00190-022-01661-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101706
in Journal of geodesy > vol 96 n° 10 (October 2022) . - n° 65[article]Pyeo: A Python package for near-real-time forest cover change detection from Earth observation using machine learning / J.F. Roberts in Computers & geosciences, vol 167 (October 2022)
[article]
Titre : Pyeo: A Python package for near-real-time forest cover change detection from Earth observation using machine learning Type de document : Article/Communication Auteurs : J.F. Roberts, Auteur ; R. Mwangi, Auteur ; F. Mukabi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 105192 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] carte thématique
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] image Sentinel-MSI
[Termes IGN] informatique en nuage
[Termes IGN] Kenya
[Termes IGN] langage de programmation
[Termes IGN] observation de la Terre
[Termes IGN] Python (langage de programmation)
[Termes IGN] surveillance forestièreRésumé : (auteur) Monitoring forest cover change from Earth observation data streams in near-real-time presents a challenge for automated change detection by way of a continuously updated big dataset. Even though deforestation is a significant global problem, forest cover changes in pairs of subsequent images happen relatively infrequently. Detecting a change can require the download and processing of tens, hundreds or even thousands of images. In geoscientific applications of Earth observation, machine learning algorithms are increasingly used. Once trained, a machine learning model can be applied to new images automatically. This paper introduces the open-access Python 3 package Pyeo - “Python for Earth Observation”. Pyeo provides a set of portable, extensible and modular Python functions for the automation of machine learning applications from Earth observation data streams, including automated search and download functionality, pre-processing and atmospheric correction, re-projection, creation of thematic base layers and machine learning classification or regression. Pyeo enables users to train their own machine learning models and then apply the models to newly downloaded imagery over their area of interest. This paper describes in detail how Pyeo works, its requirements, benefits, and a description of the libraries used. An application to the automated forest cover change detection in a region in Kenya is given. Pyeo can be used on cloud computing architectures such as Amazon Web Services, Microsoft Azure and Google Colab to provide scalable applications and processing solutions for the geosciences. Numéro de notice : A2022-706 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2022.105192 Date de publication en ligne : 09/07/2022 En ligne : https://doi.org/10.1016/j.cageo.2022.105192 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101575
in Computers & geosciences > vol 167 (October 2022) . - n° 105192[article]A relation-augmented embedded graph attention network for remote sensing object detection / Shu Tian in IEEE Transactions on geoscience and remote sensing, vol 60 n° 10 (October 2022)
[article]
Titre : A relation-augmented embedded graph attention network for remote sensing object detection Type de document : Article/Communication Auteurs : Shu Tian, Auteur ; Lihong Kang, Auteur ; Xiangwei Xing, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1000718 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] graphe
[Termes IGN] image à haute résolution
[Termes IGN] information sémantique
[Termes IGN] relation sémantique
[Termes IGN] relation spatiale
[Termes IGN] réseau neuronal de graphes
[Termes IGN] SIFT (algorithme)Résumé : (auteur) Multiclass geospatial object detection in high spatial resolution remote sensing imagery (HSRI) is still a challenging task. The main reason is that the objects in HRSI are location-variable and semantic-confusable, which results in the difficulties in differentiating the complicated spatial patterns and deriving the implicitly semantic labels among different categories of objects. In this article, we propose a relation-augmented embedded graph attention network (EGAT), which enables the full exploitation of the underlying spatial and semantic relations among objects for improving the detection performance. Specifically, we first construct two sets of spatial and semantic graphs of objects–objects for object relations modeling. Second, a Siamese architecture-based embedding spatial and semantic graph attention network is designed for relations reasoning, which is implemented by introducing the long short-term memory (LSTM) mechanism into the EGAT, for learning the relations among different categories of intraobjects and interobjects. Driven by the spatial and semantic LSTM, the EGAT-LSTM can adaptively focus on the critical information of reason graphs for spatial–semantic correlation discrimination in the embedding non-Euclidean feature space. By this way, the EGAT-LSTM can effectively capture the global and local spatial–semantic relationships of objects–objects, and then produce relations-augmented features for improving the performance of object detection. We conduct comprehensive experiments on three public datasets for multiclass geospatial object detection. Our method achieves state-of-the-art performance, which demonstrates the superiority and effectiveness of the proposed method. Numéro de notice : A2022-766 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3073269 Date de publication en ligne : 18/05/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3073269 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101788
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 10 (October 2022) . - n° 1000718[article]Remote sensing and GIS based Soil Loss Estimation for Bhutan, using RUSLE model / Sangay Gyeltshen in Geocarto international, Vol 37 n° 21 ([01/10/2022])
[article]
Titre : Remote sensing and GIS based Soil Loss Estimation for Bhutan, using RUSLE model Type de document : Article/Communication Auteurs : Sangay Gyeltshen, Auteur ; Rabindra Adhikarib, Auteur ; Padam Bahadur Budha, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 6331 - 6350 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Bhoutan
[Termes IGN] distribution spatiale
[Termes IGN] effondrement de terrain
[Termes IGN] érosion
[Termes IGN] modèle RUSLE
[Termes IGN] système d'information géographique
[Termes IGN] télédétection
[Termes IGN] utilisation du solRésumé : (auteur) The repository of soil by water at a national and basin scale was estimated using the RUSLE empirical model which is the first of its kind in Bhutan. The annual soil loss is estimated and categorized into five categories: very low (800 t/yr). Sakteng and Jaldakha basins contributed the highest soil loss rate of 0.04 and 0.039 t/ha/yr, while considering on landuse pattern, non-built-up and landslide category encountered the highest soil loss of 4.09 and 0.7 t/ha/yr among others. Similarly, Tsirang, Samtse and Haa contributed the major soil loss of 0.03, 0.0298 and 0.02 t/ha/yr, respectively. The research can be used as an authentic instrument enabling the soil conservationist and the policymakers to evaluate the adverse impacts, prioritize the conservation efforts and investigate further to narrow down the causes of soil erosion. Numéro de notice : A2022-718 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.1080/10106049.2021.1936210 Date de publication en ligne : 22/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1936210 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101646
in Geocarto international > Vol 37 n° 21 [01/10/2022] . - pp 6331 - 6350[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2022211 RAB Revue Centre de documentation En réserve L003 Disponible Result of the MICROSCOPE weak equivalence principle test / Pierre Touboul in Classical and Quantum Gravity, vol 39 n° 20 (October 2022)
[article]
Titre : Result of the MICROSCOPE weak equivalence principle test Type de document : Article/Communication Auteurs : Pierre Touboul, Auteur ; Gilles Métris, Auteur ; Manuel Rodrigues, Auteur ; et al., Auteur ; Isabelle Panet , Auteur Année de publication : 2022 Article en page(s) : n° 2004009 Note générale : bibliographie
Pierre Touboul, Gilles Métris, Manuel Rodrigues, Joel Bergé, Alain Robert, Quentin Baghi, Yves André, Judicael Bedouet, Damien Boulanger, Stefanie Bremer, Patrice Carle, Ratana Chhun, Bruno Christophe, Valerio Cipolla, Thibault Damour, Pascale Danto, Louis Demange, Hansjoerg Dittus, Océane Dhuicque, Pierre Fayet, Bernard Foulon, Pierre-Yves Guidotti, Daniel Hagedorn, Emilie Hardy, Phuong-Anh Huynh, Patrick Kayser, Stephanie Lala, Claus Lämmerzah, Vincent Lebat, Françoise Liorzou, Meike List, Frank Löffler, Isabelle Panet, Martin Pernot-Borràs, Laurent Perraud, Sandrine Pires, Benjamin Pouilloux, Pascal Prieur, Alexandre Rebray, Serge Reynaud, Benny Rievers, Hanns Selig, Laura Serron, Timothy Sumner, Nicolas Tanguy, Patrizia Torresi and Pieter Visser.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] accéléromètre
[Termes IGN] MICROSCOPE (mission)
[Termes IGN] mission spatiale
[Termes IGN] principe d'équivalenceRésumé : (auteur) The space mission MICROSCOPE dedicated to the test of the equivalence principle (EP) operated from April 25, 2016 until the deactivation of the satellite on October 16, 2018. In this analysis we compare the free-fall accelerations (aA and aB) of two test masses in terms of the Eötvös parameter $\eta (\text{A,B})=2\frac{{a}_{\mathrm{A}}-{a}_{\mathrm{B}}}{{a}_{\mathrm{A}}+{a}_{\mathrm{B}}}$. No EP violation has been detected for two test masses, made from platinum and titanium alloys, in a sequence of 19 segments lasting from 13 to 198 h down to the limit of the statistical error which is smaller than 10−14 for η(Ti, Pt). Accumulating data from all segments leads to η(Ti, Pt) = [−1.5 ± 2.3 (stat) ± 1.5 (syst)] × 10−15 showing no EP violation at the level of 2.7 × 10−15 if we combine stochastic and systematic errors quadratically. This represents an improvement of almost two orders of magnitude with respect to the previous best such test performed by the Eöt-Wash group. The reliability of this limit has been verified by comparing the free falls of two test masses of the same composition (platinum) leading to a null Eötvös parameter with a statistical uncertainty of 1.1 × 10−15. Numéro de notice : A2022-690 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1088/1361-6382/ac84be En ligne : https://doi.org/10.1088/1361-6382/ac84be Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101804
in Classical and Quantum Gravity > vol 39 n° 20 (October 2022) . - n° 2004009[article]Semi-supervised adversarial recognition of refined window structures for inverse procedural façade modelling / Han Hu in ISPRS Journal of photogrammetry and remote sensing, vol 192 (October 2022)PermalinkSingle-image super-resolution for remote sensing images using a deep generative adversarial network with local and global attention mechanisms / Yadong Li in IEEE Transactions on geoscience and remote sensing, vol 60 n° 10 (October 2022)PermalinkSpatial regression graph convolutional neural networks: A deep learning paradigm for spatial multivariate distributions / Di Zhu in Geoinformatica, vol 26 n° 4 (October 2022)PermalinkSpatio-temporal graph convolutional networks for road network inundation status prediction during urban flooding / Faxi Yuan in Computers, Environment and Urban Systems, vol 97 (October 2022)PermalinkThe fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas / Jun Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 10 (October 2022)PermalinkToward BDS/Galileo/GPS/QZSS triple-frequency PPP instantaneous integer ambiguity resolutions without atmosphere corrections / Jun Tao in GPS solutions, vol 26 n° 4 (October 2022)Permalink3D LiDAR aided GNSS/INS integration fault detection, localization and integrity assessment in urban canyons / Zhipeng Wang in Remote sensing, vol 14 n° 18 (September-2 2022)PermalinkComparison of deep neural networks in detecting field grapevine diseases using transfer learning / Antonios Morellos in Remote sensing, vol 14 n° 18 (September-2 2022)PermalinkDevelopment of a novel hybrid multi-boosting neural network model for spatial prediction of urban flood / Amid Darabi in Geocarto international, vol 37 n° 19 ([15/09/2022])PermalinkEstimation of swell height using spaceborne GNSS-R data from eight CYGNSS satellites / Yanli Zheng in Remote sensing, vol 14 n° 18 (September-2 2022)PermalinkForest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics / Jakob Wernicke in Remote sensing of environment, vol 279 (September-15 2022)PermalinkIncreasing and widespread vulnerability of intact tropical rainforests to repeated droughts / Shengli Tao in Proceedings of the National Academy of Sciences of the United States of America PNAS, vol 119 n° 37 (2022)PermalinkRegional climate moderately influences species-mixing effect on tree growth-climate relationships and drought resistance for beech and pine across Europe / Géraud de Streel in Forest ecology and management, vol 520 (September-15 2022)PermalinkThe FIRST model: Spatiotemporal fusion incorrporting spectral autocorrelation / Shuaijun Liu in Remote sensing of environment, vol 279 (September-15 2022)PermalinkTree regeneration in models of forest dynamics – Suitability to assess climate change impacts on European forests / Louis A. König in Forest ecology and management, vol 520 (September-15 2022)PermalinkAmbiguity resolution for smartphone GNSS precise positioning: effect factors and performance / Bofeng Li in Journal of geodesy, vol 96 n° 9 (September 2022)PermalinkAttention mechanisms in computer vision: A survey / Meng-Hao Guo in Computational Visual Media, vol 8 n° 3 (September 2022)PermalinkBenchmarking laser scanning and terrestrial photogrammetry to extract forest inventory parameters in a complex temperate forest / Daniel Kükenbrink in International journal of applied Earth observation and geoinformation, vol 113 (September 2022)PermalinkCharacteristics of augmented map research from a cartographic perspective / Yi Cheng in Cartography and Geographic Information Science, Vol 49 n° 5 (September 2022)PermalinkDeep image deblurring: A survey / Kaihao Zhang in International journal of computer vision, vol 130 n° 9 (September 2022)Permalink