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Évaluer un récepteur GNSS RTK pour la topographie / Florian Birot in XYZ, n° 169 (décembre 2021)

Public [article]  inXYZ > n° 169 (décembre 2021) . - pp 11 - 15 Titre : Évaluer un récepteur GNSS RTK pour la topographie Type de document : Article/Communication Auteurs : Florian Birot, Auteur Année de publication : 2021 Article en page(s) : pp 11 - 15 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] analyse comparative [Termes IGN] instrument de mesure [Termes IGN] mesure géodésique [Termes IGN] positionnement cinématique en temps réel [Termes IGN] positionnement par GNSS [Termes IGN] précision centimétrique [Termes IGN] qualité instrumentale [Termes IGN] récepteur GNSS [Termes IGN] topographie Résumé : (Auteur) L’arrivée de récepteurs bas-coût performants sur le marché a bousculé certains a priori sur ces matériels et remobilisé les utilisateurs autour de la notion de test d’un appareil de mesure GNSS. Dans ce contexte, nous proposons d’explorer plusieurs méthodes d’évaluation des récepteurs GNSS. Nous nous focalisons sur les performances de positionnement, même si, aujourd’hui, une composante importante de la qualité d’un récepteur se trouve aussi dans son accessibilité, sa facilité d’utilisation et la capacité à toucher différents métiers, notamment certaines corporations qui ne sont pas nécessairement formées aux spécificités de la précision, du traitement du signal, ou de la géodésie. Les performances de positionnement restent relativement simples à évaluer, car nous avons accès facilement à des grandeurs mesurables permettant de le faire, contrairement à d’autres critères importants pour l’utilisateur final, comme l’ergonomie ou la facilité d’utilisation. Numéro de notice : A2021-846 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99166 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
112-2021041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Bagging and boosting ensemble classifiers for classification of multispectral, hyperspectral and PolSAR data: A comparative evaluation / Hamid Jafarzadeh in Remote sensing, vol 13 n° 21 (November-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 21 (November-1 2021) . - n° 4405 Titre : Bagging and boosting ensemble classifiers for classification of multispectral, hyperspectral and PolSAR data: A comparative evaluation Type de document : Article/Communication Auteurs : Hamid Jafarzadeh, Auteur ; Masoud Mahdianpari, Auteur ; Eric Gill, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4405 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] analyse comparative [Termes IGN] apprentissage automatique [Termes IGN] arbre de décision [Termes IGN] boosting adapté [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] données polarimétriques [Termes IGN] ensachage [Termes IGN] Extreme Gradient Machine [Termes IGN] image hyperspectrale [Termes IGN] image multibande [Termes IGN] image radar moirée [Termes IGN] image ROSIS Résumé : (auteur) In recent years, several powerful machine learning (ML) algorithms have been developed for image classification, especially those based on ensemble learning (EL). In particular, Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM) methods have attracted researchers’ attention in data science due to their superior results compared to other commonly used ML algorithms. Despite their popularity within the computer science community, they have not yet been well examined in detail in the field of Earth Observation (EO) for satellite image classification. As such, this study investigates the capability of different EL algorithms, generally known as bagging and boosting algorithms, including Adaptive Boosting (AdaBoost), Gradient Boosting Machine (GBM), XGBoost, LightGBM, and Random Forest (RF), for the classification of Remote Sensing (RS) data. In particular, different classification scenarios were designed to compare the performance of these algorithms on three different types of RS data, namely high-resolution multispectral, hyperspectral, and Polarimetric Synthetic Aperture Radar (PolSAR) data. Moreover, the Decision Tree (DT) single classifier, as a base classifier, is considered to evaluate the classification’s accuracy. The experimental results demonstrated that the RF and XGBoost methods for the multispectral image, the LightGBM and XGBoost methods for hyperspectral data, and the XGBoost and RF algorithms for PolSAR data produced higher classification accuracies compared to other ML techniques. This demonstrates the great capability of the XGBoost method for the classification of different types of RS data. Numéro de notice : A2021-823 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13214405 Date de publication en ligne : 02/11/2021 En ligne : https://doi.org/10.3390/rs13214405 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98938 [article]

A comparison of a gradient boosting decision tree, random forests, and artificial neural networks to model urban land use changes: the case of the Seoul metropolitan area / Myung-Jin Jun in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2149 - 2167 Titre : A comparison of a gradient boosting decision tree, random forests, and artificial neural networks to model urban land use changes: the case of the Seoul metropolitan area Type de document : Article/Communication Auteurs : Myung-Jin Jun, Auteur Année de publication : 2021 Article en page(s) : pp 2149 - 2167 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse comparative [Termes IGN] arbre de décision [Termes IGN] changement d'utilisation du sol [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] Extreme Gradient Machine [Termes IGN] modèle de simulation [Termes IGN] réseau neuronal artificiel [Termes IGN] Séoul [Termes IGN] zone urbaine Résumé : (auteur) This study compares the performance of gradient boosting decision tree (GBDT), artificial neural networks (ANNs), and random forests (RF) methods in LUC modeling in the Seoul metropolitan area. The results of this study showed that GBDT and RF have higher predictive power than ANN, indicating that tree-based ensemble methods are an effective technique for LUC prediction. Along with the outstanding predictive performance, the DT-based ensemble models provide insights for understanding which factors drive LUCs in complex urban dynamics with the relative importance and nonlinear marginal effects of predictor variables. The GBDT results indicate that distance to the existing residential site has the highest contribution to urban land use conversion (30.4% of the relative importance), while other significant predictor variables were proximity to industrial and public sites (combined 32.3% of relative importance). New residential development is likely to be adjacent to existing residential sites, but nonresidential development occurs at a distance (about 600 m) from such sites. The distance to the central business district (CBD) had increasing marginal effects on residential land use conversion, while no significant pattern was found for nonresidential land use conversion, indicating that Seoul has experienced more population suburbanization than employment decentralization. Numéro de notice : A2021-756 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1887490 Date de publication en ligne : 01/03/2021 En ligne : https://doi.org/10.1080/13658816.2021.1887490 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98771 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2021111	SL	Revue	Centre de documentation	Revues en salle	Disponible

Comparison of digital elevation models through the analysis of geomorphic surface remnants in the Desatoya Mountains, Nevada / Bernadett Dobre in Transactions in GIS, vol 25 n° 5 (October 2021)  

Public [article]  inTransactions in GIS > vol 25 n° 5 (October 2021) . - pp 2262 - 2282 Titre : Comparison of digital elevation models through the analysis of geomorphic surface remnants in the Desatoya Mountains, Nevada Type de document : Article/Communication Auteurs : Bernadett Dobre, Auteur ; Istvan P. Kovács, Auteur ; Titusz Bugya, Auteur Année de publication : 2021 Article en page(s) : pp 2262 - 2282 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse comparative [Termes IGN] bassin hydrographique [Termes IGN] carte géologique [Termes IGN] données lidar [Termes IGN] géomorphologie [Termes IGN] GRASS [Termes IGN] MNS ASTER [Termes IGN] MNS SRTM [Termes IGN] modèle numérique de surface [Termes IGN] Nevada (Etats-Unis) [Termes IGN] semis de points [Termes IGN] sommet (relief) [Termes IGN] zone semi-aride Résumé : (auteur) This article explores the advantages and limitations of open-source digital elevation models (DEMs) generated from various acquisition methods and at various spatial resolutions, through extracting geomorphic surface remnants in a semi-arid, mountainous topographic environment. Even if the tested models have well-known vertical accuracy and precision, their reliability for peak detection is still waiting to be studied. In this research, we investigate peaks as remnants of degraded geomorphic surfaces. Peaks of surface remnants can help to reconstruct geomorphic surfaces and evaluate DEM applicabilities, since they can enhance the identification of overall accuracy. Our methodology uses a well-known open-source GRASS GIS Geomorphons module (r.geomorphon) on several recently released and widely used DEMs covering the Desatoya Mountains study area. We conclude that, despite the characteristic differences in the accuracy of the analyzed DEMs, all of those examined proved to be appropriate to detect surface remnants. Numéro de notice : A2021-121 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/tgis.12819 Date de publication en ligne : 10/08/2021 En ligne : https://doi.org/10.1111/tgis.12819 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99301 [article]

Recognition of crevasses with high-resolution digital elevation models: Application of geomorphometric modeling and texture analysis / Olga T. Ishalina in Transactions in GIS, vol 25 n° 5 (October 2021)  

Public [article]  inTransactions in GIS > vol 25 n° 5 (October 2021) . - pp 2529 - 2552 Titre : Recognition of crevasses with high-resolution digital elevation models: Application of geomorphometric modeling and texture analysis Type de document : Article/Communication Auteurs : Olga T. Ishalina, Auteur ; Dimitri P. Bliakharskii, Auteur ; Igor V. Florinsky, Auteur Année de publication : 2021 Article en page(s) : pp 2529 - 2552 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] analyse texturale [Termes IGN] Antarctique [Termes IGN] crevasse [Termes IGN] glacier [Termes IGN] image à haute résolution [Termes IGN] image captée par drone [Termes IGN] modèle numérique de surface [Termes IGN] texture d'image Résumé : (auteur) Crevasses—cracks in glaciers and ice sheets—pose a danger to polar researchers and glaciologists. We compare the capabilities of two techniques—geomorphometric modeling and texture analysis—to recognize open and hidden crevasses using high-resolution digital elevation models (DEMs) generated from images collected by an unmanned aerial system (UAS). The first technique includes derivation of local morphometric variables; the second includes calculation of the Haralick texture features. The study area is represented by the first 30 km of a sledge route between the Progress and Vostok polar stations, East Antarctica. The UAS survey was performed by a Geoscan 201 Geodesy UAS. For the sledge route area, DEMs with resolutions of 0.25, 0.5, and 1 m were generated. Models of 12 morphometric variables and 11 texture features were derived from the DEMs. In terms of crevasse recognition, the most informative morphometric variable and texture feature was horizontal curvature and inverse difference moment, respectively. In most cases, derivation and mapping of these variables allow one to recognize crevasses wider than 3 m; narrower crevasses can be recognized for lengths from 500 m. For crevasse recognition, the geomorphometric modeling and the Haralick texture analysis can complement each other. Numéro de notice : A2021-122 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/tgis.12790 Date de publication en ligne : 06/07/2021 En ligne : https://doi.org/10.1111/tgis.12790 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99303 [article]

Spatial interpolation of mobile positioning data for population statistics / Anto Aasa in Journal of location-based services, vol 15 n° 4 ([01/10/2021])  

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The real potential of current passive satellite data to map aboveground biomass in tropical forests / Nidhi Jha in Remote sensing in ecology and conservation, vol 7 n° 3 (September 2021)  

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Quantifying coherence between TDM90, SRTM90 and ASTER90 / Umut Gunes Sefercik in Geocarto international, vol 36 n° 15 ([15/08/2021])  

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Digital building-height preparation from satellite stereo images / P.S. Prakash in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 8 (August 2021)  

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Vehicle detection in very-high-resolution remote sensing images based on an anchor-free detection model with a more precise foveal area / Xungen Li in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)  

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Anomalous variations of air temperature prior to earthquakes / Irfan Mahmood in Geocarto international, vol 36 n° 12 ([01/07/2021])  

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Detecting high-temperature anomalies from Sentinel-2 MSI images / Yongxue Liu in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)  

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Evaluation of sum-NDVI values to estimate wheat grain yields using multi-temporal Landsat OLI data / Asadollah Mirasi in Geocarto international, vol 36 n° 12 ([01/07/2021])  

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An innovative and automated method for characterizing wood defects on trunk surfaces using high-density 3D terrestrial LiDAR data / Van-Tho Nguyen in Annals of Forest Science, vol 78 n° 2 (June 2021)  

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On the relationship between normalized difference vegetation index and land surface temperature: MODIS-based analysis in a semi-arid to arid environment / Salahuddin M. Jaber in Geocarto international, vol 36 n° 10 ([01/06/2021])  

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Récepteurs GNSS bas coût pour la surveillance des grands ponts / Nicolas Manzini in XYZ, n° 167 (juin 2021)

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Reconnaissance automatique d’objets pour le jumeau numérique ferroviaire à partir d’imagerie aérienne / Valentin Desbiolles in XYZ, n° 167 (juin 2021)

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Simulating multi-exit evacuation using deep reinforcement learning / Dong Xu in Transactions in GIS, Vol 25 n° 3 (June 2021)  

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A topology-preserving simplification method for 3D building models / Biao Wang in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)  

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Delineation of cities based on scaling properties of urban patterns: a comparison of three methods / Gaëtan Montero in International journal of geographical information science IJGIS, vol 35 n° 5 (May 2021)  

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What is the difference between augmented reality and 2D navigation electronic maps in pedestrian wayfinding? / Weihua Dong in Cartography and Geographic Information Science, vol 48 n° 3 (May 2021)  

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DEM resolution influences on peak flow prediction: a comparison of two different based DEMs through various rescaling techniques / Ali H. Ahmed Suliman in Geocarto international, vol 36 n° 7 ([15/04/2021])  

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Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC4A / Pierre Bosser in Earth System Science Data, vol 13 n° 4 (April 2021)  

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Models for integrating and identifying the effect of senescence on individual tree survival probability for Norway spruce / Jouni Siipilehto in Silva fennica, vol 55 n° 2 (April 2021)  

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Parsing of urban facades from 3D point clouds based on a novel multi-view domain / Wei Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 4 (April 2021)  

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