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Pourquoi le rendu des zones rocheuses sur les nouvelles cartes IGN est-il si différent de l’ancien ? / Paul Courbon in XYZ, n° 172 (septembre 2022)
[article]
Titre : Pourquoi le rendu des zones rocheuses sur les nouvelles cartes IGN est-il si différent de l’ancien ? Type de document : Article/Communication Auteurs : Paul Courbon, Auteur ; Dominique Foubert, Auteur Année de publication : 2022 Article en page(s) : pp 27 - 30 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Rédaction cartographique
[Termes IGN] BD Topo
[Termes IGN] carte Top 25
[Termes IGN] carte topographique
[Termes IGN] courbe de niveau
[Termes IGN] falaise
[Termes IGN] géoportail
[Termes IGN] représentation cartographique
[Termes IGN] rocher
[Termes IGN] visualisation cartographiqueRésumé : (Auteur) La rédaction de XYZ est alertée par Paul Courbon, l'un de nos auteurs, sur le rendu des zones rocheuses sur les nouvelles cartes IGN. Il compare les anciennes cartes au 1:25000 et les nouvelles, que l’on peut également visualiser sur le Géoportail. Excès d’automatisation du dessin, mauvais choix dans les méthodes de restitution, économie des moyens en personnels, Paul essaie de comprendre pourquoi il ne retrouve plus les falaises d’antan, leurs courbes de niveau et leurs ombrages. Sollicité, Dominique Foubert, ancien topographe du service de la cartographie à l’IGN, nous déroule des pistes de réflexion liées à l’historique de la production des cartes. Effectivement, grâce à l’appui de Christophe Pécot, les souvenirs se précisent et Dominique nous explique “pourquoi et comment” on en est arrivé là. Numéro de notice : A2022-673 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Date de publication en ligne : 01/09/2022 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101637
in XYZ > n° 172 (septembre 2022) . - pp 27 - 30[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 112-2022031 RAB Revue Centre de documentation En réserve L003 Disponible Rapid source models of the 2021 Mw 7.4 Maduo, China, earthquake inferred from high-rate BDS3/2, GPS, Galileo and GLONASS observations / Jianfei Zang in Journal of geodesy, vol 96 n° 9 (September 2022)
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Titre : Rapid source models of the 2021 Mw 7.4 Maduo, China, earthquake inferred from high-rate BDS3/2, GPS, Galileo and GLONASS observations Type de document : Article/Communication Auteurs : Jianfei Zang, Auteur ; Yangmao Wen, Auteur ; Zhicai Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 58 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] Chine
[Termes IGN] données GNSS
[Termes IGN] magnitude
[Termes IGN] positionnement par GNSS
[Termes IGN] positionnement ponctuel précis
[Termes IGN] prévention des risques
[Termes IGN] séisme
[Termes IGN] temps réel
[Termes IGN] tenseurRésumé : (auteur) On May 21, 2021, a Mw 7.4 earthquake struck the Maduo County in Qinghai province of China. The earthquake was well recorded by the surrounding high-rate Global Navigation Satellite System (GNSS) stations. In addition to GPS, GLONASS and BDS2 observations, these stations also recorded the latest BDS3 and Galileo observations. The performance of high-rate single-GNSS and fusion of multi-GNSS on warning magnitude calculation, rapid centroid moment tensor inversion and static fault slip inversion are well investigated in this study. The results demonstrate that within a short period of time (5 min), Precise Point Positioning (PPP) displacements of BDS3 alone are better than those of BDS2 alone, while the individual displacement accuracies of BDS3, GPS and Galileo are comparable. When BDS3 and BDS2 data are combined, the combined BDS accuracy is slightly better than that of GPS or Galileo alone. Compared with the single-GNSS displacements, the fusion of GPS + GLONASS + Galileo + BDS3/2 (GREC) can achieve the highest accuracy with standard deviation values of 0.25 cm, 0.22 cm and 0.53 cm in north, east and up components, respectively. For the warning magnitude estimation, BDS3 alone, BDS2 alone, combined BDS3/2, combined GPS + BDS3/2, Galileo alone and GREC all show comparable performance. The results of centroid moment tensor inversion and static fault slip inversion are related to the station distribution. When the same stations are used, the inverted centroid moment tensors and static fault slips of a single GNSS are very similar to the multi-GNSS inversion results, but the multi-GNSS centroid moment tensor series and fault slips appear to be more stable when the observation quality of a single GNSS such as GLONASS, is relatively low. The results obtained in this study imply that GPS, BDS3, Galileo and combined multi-GNSS have the potential to be used for the earthquake early warning and rapid earthquake source modeling. Numéro de notice : A2022-603 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-022-01641-w Date de publication en ligne : 24/08/2022 En ligne : https://doi.org/10.1007/s00190-022-01641-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101556
in Journal of geodesy > vol 96 n° 9 (September 2022) . - n° 58[article]Simulation of land use/land cover changes and urban expansion in Estonia by a hybrid ANN-CA-MCA model and utilizing spectral-textural indices / Najmeh Mozaffaree Pour in Environmental Monitoring and Assessment, vol 194 n° 9 (September 2022)
[article]
Titre : Simulation of land use/land cover changes and urban expansion in Estonia by a hybrid ANN-CA-MCA model and utilizing spectral-textural indices Type de document : Article/Communication Auteurs : Najmeh Mozaffaree Pour, Auteur ; Oleksandr Karasov, Auteur ; Iuliia Burdun, Auteur ; Tõnu Oja, Auteur Année de publication : 2022 Article en page(s) : n° 584 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] chaîne de Markov
[Termes IGN] croissance urbaine
[Termes IGN] Estonie
[Termes IGN] Google Earth Engine
[Termes IGN] image Landsat-8
[Termes IGN] modèle de simulation
[Termes IGN] occupation du sol
[Termes IGN] réseau neuronal artificielRésumé : (auteur) Over the recent two decades, land use/land cover (LULC) drastically changed in Estonia. Even though the population decreased by 11%, noticeable agricultural and forest land areas were turned into urban land. In this work, we analyzed those LULC changes by mapping the spatial characteristics of LULC and urban expansion in the years 2000–2019 in Estonia. Moreover, using the revealed spatiotemporal transitions of LULC, we simulated LULC and urban expansion for 2030. Landsat 5 and 8 data were used to estimate 147 spectral-textural indices in the Google Earth Engine cloud computing platform. After that, 19 selected indices were used to model LULC changes by applying the hybrid artificial neural network, cellular automata, and Markov chain analysis (ANN-CA-MCA). While determining spectral-textural indices is quite common for LULC classifications, utilization of these continues indices in LULC change detection and examining these indices at the landscape scale is still in infancy. This country-wide modeling approach provided the first comprehensive projection of future LULC utilizing spectral-textural indices. In this work, we utilized the hybrid ANN-CA-MCA model for predicting LULC in Estonia for 2030; we revealed that the predicted changes in LULC from 2019 to 2030 were similar to the observed changes from 2011 to 2019. The predicted change in the area of artificial surfaces was an increased rate of 1.33% to reach 787.04 km2 in total by 2030. Between 2019 and 2030, the other significant changes were the decrease of 34.57 km2 of forest lands and the increase of agricultural lands by 14.90 km2 and wetlands by 9.31 km2. These findings can develop a proper course of action for long-term spatial planning in Estonia. Therefore, a key policy priority should be to plan for the stable care of forest lands to maintain biodiversity. Numéro de notice : A2022-458 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Article DOI : 10.1007/s10661-022-10266-7 Date de publication en ligne : 13/07/2022 En ligne : http://dx.doi.org/10.1007/s10661-022-10266-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101258
in Environmental Monitoring and Assessment > vol 194 n° 9 (September 2022) . - n° 584[article]Structured binary neural networks for image recognition / Bohan Zhuang in International journal of computer vision, vol 130 n° 9 (September 2022)
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Titre : Structured binary neural networks for image recognition Type de document : Article/Communication Auteurs : Bohan Zhuang, Auteur ; Chunhua Shen, Auteur ; Mingkui Tan, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2081 - 2102 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] décomposition
[Termes IGN] détection d'objet
[Termes IGN] implémentation (informatique)
[Termes IGN] logique binaire
[Termes IGN] segmentation sémantiqueRésumé : (auteur) In this paper, we propose to train binarized convolutional neural networks (CNNs) that are of significant importance for deploying deep learning to mobile devices with limited power capacity and computing resources. Previous works on quantizing CNNs often seek to approximate the floating-point information of weights and/or activations using a set of discrete values. Such methods, termed value approximation here, typically are built on the same network architecture of the full-precision counterpart. Instead, we take a new “structured approximation” view for network quantization — it is possible and valuable to exploit flexible architecture transformation when learning low-bit networks, which can achieve even better performance than the original networks in some cases. In particular, we propose a “group decomposition” strategy, termed GroupNet, which divides a network into desired groups. Interestingly, with our GroupNet strategy, each full-precision group can be effectively reconstructed by aggregating a set of homogeneous binary branches. We also propose to learn effective connections among groups to improve the representation capability. To improve the model capacity, we propose to dynamically execute sparse binary branches conditioned on input features while preserving the computational cost. More importantly, the proposed GroupNet shows strong flexibility for a few vision tasks. For instance, we extend the GroupNet for accurate semantic segmentation by embedding the rich context into the binary structure. The proposed GroupNet also shows strong performance on object detection. Experiments on image classification, semantic segmentation, and object detection tasks demonstrate the superior performance of the proposed methods over various quantized networks in the literature. Moreover, the speedup and runtime memory cost evaluation comparing with related quantization strategies is analyzed on GPU platforms, which serves as a strong benchmark for further research. Numéro de notice : A2022-637 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-022-01638-0 Date de publication en ligne : 22/06/2022 En ligne : https://doi.org/10.1007/s11263-022-01638-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101443
in International journal of computer vision > vol 130 n° 9 (September 2022) . - pp 2081 - 2102[article]Study on city digital twin technologies for sustainable smart city design: A review and bibliometric analysis of geographic information system and building information modeling integration / Haishan Xia in Sustainable Cities and Society, vol 84 (September 2022)
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Titre : Study on city digital twin technologies for sustainable smart city design: A review and bibliometric analysis of geographic information system and building information modeling integration Type de document : Article/Communication Auteurs : Haishan Xia, Auteur ; Zishuo Liu, Auteur ; Maria Efremochkina, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 104009 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] bibliométrie
[Termes IGN] CityGML
[Termes IGN] format Industry foudation classes IFC
[Termes IGN] intégration de données
[Termes IGN] jumeau numérique
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] ontologie
[Termes IGN] planification urbaine
[Termes IGN] système d'information géographique
[Termes IGN] ville durable
[Termes IGN] ville intelligenteRésumé : (auteur) Geographic information system (GIS) data provide geospatial data on cities and spatial analysis functions that are essential for urban design. Building information modeling (BIM) includes a digital entity of construction, a passive presentation of micro-digital information on real entities, and an active application of models in the entire life cycle realization of the architecture, engineering, and construction industries. A combination of these technologies could provide a core technology for the urban digital twin to support sustainable smart city design. Through an insightful literature review, this paper summarizes the different disciplinary classifications of GIS and BIM functional integration, distills the value of data, and discusses the ontology-based data integration approach that GIS and BIM should take in the future to conduct research on integration applications in smart cities. To verify this view, keyword analysis, co-country analysis, and co-citation and coupling analyses are conducted using CiteSpace. GIS and BIM integration has attracted much attention. However, a professional disconnect and fragmented composition pose challenges in the field of GIS and BIM integration. Future research should focus on smart city planning, updating, management; ontology-based GIS and BIM data integration platform; and operation; and the collaborative management of urban rail transportation engineering. Numéro de notice : A2022-543 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2022.104009 Date de publication en ligne : 18/06/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101118
in Sustainable Cities and Society > vol 84 (September 2022) . - n° 104009[article]Evapotranspiration mapping of cotton fields in Brazil: comparison between SEBAL and FAO-56 method / Juan Vicente Liendro Moncada in Geocarto international, Vol 37 n° 17 ([20/08/2022])Permalink3D building reconstruction from single street view images using deep learning / Hui En Pang in International journal of applied Earth observation and geoinformation, vol 112 (August 2022)Permalink3D semantic scene completion: A survey / Luis Roldão in International journal of computer vision, vol 130 n° 8 (August 2022)PermalinkAn automatic approach for tree species detection and profile estimation of urban street trees using deep learning and Google street view images / Kwanghun Choi in ISPRS Journal of photogrammetry and remote sensing, vol 190 (August 2022)PermalinkChange detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach / Joachim Gehrung in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 5 (August 2022)PermalinkComparative analysis of real-time precise point positioning method in terms of positioning and zenith tropospheric delay estimation / Omer Faruk Atiz in Survey review, vol 55 n° 388 (January 2023)PermalinkDeep learning feature representation for image matching under large viewpoint and viewing direction change / Lin Chen in ISPRS Journal of photogrammetry and remote sensing, vol 190 (August 2022)PermalinkExperiencing virtual geographic environment in urban 3D participatory e-planning: A user perspective / Thibaud Chassin in Landscape and Urban Planning, vol 224 (August 2022)PermalinkFull-waveform classification and segmentation-based signal detection of single-wavelength bathymetric LiDAR / Xue Ji in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)PermalinkGenerating impact maps from bomb craters automatically detected in aerial wartime images using marked point processes / Christian Kruse in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 5 (August 2022)Permalink