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Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation / Kathrin Maier in ISPRS Journal of photogrammetry and remote sensing, vol 186 (April 2022)
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[article]
Titre : Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation Type de document : Article/Communication Auteurs : Kathrin Maier, Auteur ; Andrea Nascetti, Auteur ; Ward van Pelt, Auteur ; Gunhild Rosqvist, Auteur Année de publication : 2022 Article en page(s) : pp 1 - 18 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes principales
[Termes IGN] bande infrarouge
[Termes IGN] épaisseur
[Termes IGN] erreur moyenne quadratique
[Termes IGN] géoréférencement direct
[Termes IGN] image captée par drone
[Termes IGN] image multibande
[Termes IGN] manteau neigeux
[Termes IGN] modèle numérique de surface
[Termes IGN] photogrammétrie aérienne
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] qualité du modèle
[Termes IGN] reconstruction 3D
[Termes IGN] structure-from-motion
[Termes IGN] SuèdeRésumé : (Auteur) More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high-resolution 3D snow-covered surface models (7 cm/pixel) of alpine areas up to eight hectares in a fast, reliable and affordable way. The test sites’ average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a significant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of closing the scale gap between discrete point measurements and regional-scale remote sensing and complements large-scale remote sensing data and snow model output with an adequate validation source. Numéro de notice : A2022-066 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.01.020 Date de publication en ligne : 09/02/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.01.020 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99783
in ISPRS Journal of photogrammetry and remote sensing > vol 186 (April 2022) . - pp 1 - 18[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2022041 SL Revue Centre de documentation Revues en salle Disponible 081-2022043 DEP-RECP Revue LaSTIG Dépôt en unité Exclu du prêt 081-2022042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt A mean-squared-error condition for weighting ionospheric delays in GNSS baselines / Peter J.G. Teunissen in Journal of geodesy, vol 95 n° 11 (November 2021)
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Titre : A mean-squared-error condition for weighting ionospheric delays in GNSS baselines Type de document : Article/Communication Auteurs : Peter J.G. Teunissen, Auteur ; Amir Khodabandeh, Auteur Année de publication : 2021 Article en page(s) : n° 118 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] erreur moyenne quadratique
[Termes IGN] ligne de base
[Termes IGN] pondération
[Termes IGN] propagation ionosphérique
[Termes IGN] retard ionosphèrique
[Vedettes matières IGN] Traitement de données GNSSRésumé : (auteur) Although ionosphere-weighted GNSS parameter estimation is a popular technique for strengthening estimator performance in the presence of ionospheric delays, no provable rules yet exist that specify the needed weighting in dependence on ionospheric circumstances. The goal of the present contribution is therefore to develop and present the ionospheric conditions that need to be satisfied in order for the ionosphere-weighted solution to be mean squared error (MSE) superior to the ionosphere-float solution. When satisfied, the presented conditions guarantee from an MSE performance view, when (a) the ionosphere-fixed solution can be used, (b) the ionosphere-float solution must be used, or (c) an ionosphere-weighted solution can be used. Numéro de notice : A2021-777 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01569-7 Date de publication en ligne : 10/10/2021 En ligne : https://doi.org/10.1007/s00190-021-01569-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98840
in Journal of geodesy > vol 95 n° 11 (November 2021) . - n° 118[article]Exploring fuzzy local spatial information algorithms for remote sensing image classification / Anjali Madhu in Remote sensing, vol 13 n° 20 (October-2 2021)
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Titre : Exploring fuzzy local spatial information algorithms for remote sensing image classification Type de document : Article/Communication Auteurs : Anjali Madhu, Auteur ; Anil Kumar, Auteur ; Peng Jia, Auteur Année de publication : 2021 Article en page(s) : n° 4163 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] classification dirigée
[Termes IGN] classification floue
[Termes IGN] classification pixellaire
[Termes IGN] distance euclidienne
[Termes IGN] erreur moyenne quadratique
[Termes IGN] Inde
[Termes IGN] matrice d'erreur
[Termes IGN] occupation du sol
[Termes IGN] théorie des possibilitésRésumé : (auteur) Fuzzy c-means (FCM) and possibilistic c-means (PCM) are two commonly used fuzzy clustering algorithms for extracting land use land cover (LULC) information from satellite images. However, these algorithms use only spectral or grey-level information of pixels for clustering and ignore their spatial correlation. Different variants of the FCM algorithm have emerged recently that utilize local spatial information in addition to spectral information for clustering. Such algorithms are seen to generate clustering outputs that are more enhanced than the classical spectral-based FCM algorithm. Nonetheless, the scope of integrating spatial contextual information with the conventional PCM algorithm, which has several advantages over the FCM algorithm for supervised classification, has not been explored much. This study proposed integrating local spatial information with the PCM algorithm using simpler but proven approaches from available FCM-based local spatial information algorithms. The three new PCM-based local spatial information algorithms: Possibilistic c-means with spatial constraints (PCM-S), possibilistic local information c-means (PLICM), and adaptive possibilistic local information c-means (ADPLICM) algorithms, were developed corresponding to the available fuzzy c-means with spatial constraints (FCM-S), fuzzy local information c-means (FLICM), and adaptive fuzzy local information c-means (ADFLICM) algorithms. Experiments were conducted to analyze and compare the FCM and PCM classifier variants for supervised LULC classifications in soft (fuzzy) mode. The quantitative assessment of the soft classification results from fuzzy error matrix (FERM) and root mean square error (RMSE) suggested that the new PCM-based local spatial information classifiers produced higher accuracies than the PCM, FCM, or its local spatial variants, in the presence of untrained classes and noise. The promising results from PCM-based local spatial information classifiers suggest that the PCM algorithm, which is known to be naturally robust to noise, when integrated with local spatial information, has the potential to result in more efficient classifiers capable of better handling ambiguities caused by spectral confusions in landscapes. Numéro de notice : A2021-806 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13204163 Date de publication en ligne : 18/10/2021 En ligne : https://doi.org/10.3390/rs13204163 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98864
in Remote sensing > vol 13 n° 20 (October-2 2021) . - n° 4163[article]Observable quality assessment of broadband very long baseline interferometry system / Ming H. Xu in Journal of geodesy, vol 95 n° 5 (May 2021)
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Titre : Observable quality assessment of broadband very long baseline interferometry system Type de document : Article/Communication Auteurs : Ming H. Xu, Auteur ; James M. Anderson, Auteur ; Robert Heinkelmann, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 51 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] données VGOS
[Termes IGN] erreur moyenne quadratique
[Termes IGN] interférométrie à très grande base
[Termes IGN] pondération
[Termes IGN] propagation ionosphérique
[Termes IGN] retard ionosphèrique
[Termes IGN] teneur totale en électronsRésumé : (auteur) The next-generation, broadband geodetic very long baseline interferometry system, named VGOS, is developing its global network, and VGOS networks with a small size of 3–7 stations have already made broadband observations from 2017 to 2019. We made quality assessments for two kinds of observables in the 21 VGOS sessions currently available: group delay and differential total electron content (δTEC). Our study reveals that the random measurement noise of VGOS group delays is at the level of less than 2 ps (1ps=10−12 s), while the contributions from systematic error sources, mainly source structure related, are at the level of 20 ps. Due to the significant improvement in measurement noise, source structure effects with relatively small magnitudes that are not overwhelming in the S/X VLBI system, for instance 10 ps, are clearly visible in VGOS observations. Another critical error source in VGOS observations is discrete delay jumps, for instance, a systematic offset of about 310 ps or integer multiples of that. The predominant causative factor is found to be related to source structure. The measurement noise level of δTEC observables is about 0.07 TECU, but the systematic effects are five times larger than that. A strong correlation between group delay and δTEC observables is discovered with a trend of 40 ps/TECU for observations with large structure effects; there is a second trend in the range 60–70 ps/TECU when the measurement noise is dominant. Numéro de notice : A2021-346 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01496-7 Date de publication en ligne : 13/04/2021 En ligne : https://doi.org/10.1007/s00190-021-01496-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97590
in Journal of geodesy > vol 95 n° 5 (May 2021) . - n° 51[article]Integrity investigation of global ionospheric TEC maps for high-precision positioning / Jiaojiao Zhao in Journal of geodesy, vol 95 n° 3 (March 2021)
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Titre : Integrity investigation of global ionospheric TEC maps for high-precision positioning Type de document : Article/Communication Auteurs : Jiaojiao Zhao, Auteur ; Manuel Hernández-Pajares, Auteur ; Ningbo Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] carte ionosphérique mondiale
[Termes IGN] erreur moyenne quadratique
[Termes IGN] International GNSS Service
[Termes IGN] modèle ionosphérique
[Termes IGN] modèle stochastique
[Termes IGN] positionnement ponctuel précis
[Termes IGN] tempête magnétique
[Termes IGN] teneur totale en électronsRésumé : (auteur) Aside from the ionospheric total electron content (TEC) information, root-mean-square (RMS) maps are also provided as the standard deviations of the corresponding TEC errors in global ionospheric maps (GIMs). As the RMS maps are commonly used as the accuracy indicator of GIMs to optimize the stochastic model of precise point positioning algorithms, it is of crucial importance to investigate the reliability of RMS maps involved in GIMs of different Ionospheric Associated Analysis Centers (IAACs) of the International GNSS Service (IGS), i.e., the integrity of GIMs. We indirectly analyzed the reliability of RMS maps by comparing the actual error of the differential STEC (dSTEC) with the RMS of the dSTEC derived from the RMS maps. With this method, the integrity of seven rapid IGS GIMs (UQRG, CORG, JPRG, WHRG, EHRG, EMRG, and IGRG) and six final GIMs (UPCG, CODG, JPLG, WHUG, ESAG and IGSG) was examined under the maximum and minimum solar activity conditions as well as the geomagnetic storm period. The results reveal that the reliability of the RMS maps is significantly different for the GIMs from different IAACs. Among these GIMs, the values in the RMS maps of UQRG are large, which can be used as ionospheric protection level, while the RMS values in EHRG and ESAG are significantly lower than the realistic RMS. The rapid and final GIMs from CODE, JPL and WHU provide quite reasonable RMS maps. The bounding performance of RMS maps can be influenced by the location of the stations, while the influence of solar activity and the geomagnetic storm is not obvious. Numéro de notice : A2021-220 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01487-8 Date de publication en ligne : 22/02/2021 En ligne : https://doi.org/10.1007/s00190-021-01487-8 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97188
in Journal of geodesy > vol 95 n° 3 (March 2021) . - n° 35[article]Adjusting the regular network of squares resolution to the digital terrain model surface shape / Dariusz Gościewski in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)
PermalinkDense stereo matching strategy for oblique images that considers the plane directions in urban areas / Jianchen Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)
PermalinkEstimation of tropospheric wet refractivity using tomography method and artificial neural networks in Iranian case study / Mir Reza Ghaffari Razin in GPS solutions, Vol 24 n° 3 (July 2020)
PermalinkPrognostic evaluation of the impact of restricted horizon visibility on the accuracy of position (coordinates) obtained with GNSS based on empirical data / Oleksandr Yanchuk in Geodesy and cartography, vol 46 n° 2 (July 2020)
PermalinkUnder-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (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)
PermalinkSoil moisture estimation with SVR and data augmentation based on alpha approximation method / Wei Xu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)
PermalinkGeneration of digital terrain model for forest areas using a new particle swarm optimization on LiDAR data / Behnaz Bigdeli in Survey review, vol 52 n° 371 (March 2020)
PermalinkAn OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data / Xiaogang Guo in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)
PermalinkUsing Ranked Probability Skill Score (RPSS) as Nonlocal Root-Mean-Square Errors (RMSEs) for Mitigating Wet Bias of Soil Moisture Ocean Salinity (SMOS) Soil Moisture / Ju Hyoung Lee in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 2 (February 2020)
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