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Deep learning method for Chinese multisource point of interest matching / Pengpeng Li in Computers, Environment and Urban Systems, vol 96 (September 2022)
[article]
Titre : Deep learning method for Chinese multisource point of interest matching Type de document : Article/Communication Auteurs : Pengpeng Li, Auteur ; Jiping Liu, Auteur ; An Luo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101821 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] appariement sémantique
[Termes IGN] apprentissage profond
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] inférence sémantique
[Termes IGN] information sémantique
[Termes IGN] point d'intérêt
[Termes IGN] représentation vectorielle
[Termes IGN] traitement du langage naturelRésumé : (auteur) Multisource point of interest (POI) matching refers to the pairing of POIs that refer to the same geographic entity in different data sources. This also constitutes the core issue in geospatial data fusion and update. The existing methods cannot effectively capture the complex semantic information from a text, and the manually defined rules largely affect matching results. This study developed a multisource POI matching method based on deep learning that transforms the POI pair matching problem into a binary classification problem. First, we used three different Chinese word segmentation methods to segment the POI text attributes and used the segmentation results to train the Word2Vec model to generate the corresponding word vector representation. Then, we used the text convolutional neural network (Text-CNN) and multilayer perceptron (MLP) to extract the POI attributes' features and generate the corresponding feature vector representation. Finally, we used the enhanced sequential inference model (ESIM) to perform local inference and inference combination on each attribute to realize the classification of POI pairs. We used the POI dataset containing Baidu Map, Tencent Map, and Gaode Map from Chengdu to train, verify, and test the model. The experimental results show that the matching precision, recall rate, and F1 score of the proposed method exceed 98% on the test set, and it is significantly better than the existing matching methods. Numéro de notice : A2022-513 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101821 Date de publication en ligne : 18/06/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101821 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101053
in Computers, Environment and Urban Systems > vol 96 (September 2022) . - n° 101821[article]Deflection of vertical effect on direct georeferencing in aerial mobile mapping systems: A case study in Sweden / Mohammad Bagherbandi in Photogrammetric record, vol 37 n° 179 (September 2022)
[article]
Titre : Deflection of vertical effect on direct georeferencing in aerial mobile mapping systems: A case study in Sweden Type de document : Article/Communication Auteurs : Mohammad Bagherbandi, Auteur ; Arash Jouybari, Auteur ; Faramarz Nilfouroushan, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 285 - 305 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie
[Termes IGN] couplage GNSS-INS
[Termes IGN] déviation de la verticale
[Termes IGN] Earth Gravity Model 2008
[Termes IGN] ellipsoïde de référence
[Termes IGN] géoréférencement direct
[Termes IGN] photogrammétrie aérienne
[Termes IGN] quasi-géoïde
[Termes IGN] Suède
[Termes IGN] système de numérisation mobileRésumé : (auteur) GNSS/INS applications are being developed, especially for direct georeferencing in airborne photogrammetry. Achieving accurately georeferenced products from the integration of GNSS and INS requires removing systematic errors in the mobile mapping systems. The INS sensor's uncertainty is decreasing; therefore, the influence of the deflection of verticals (DOV, the angle between the plumb line and normal to the ellipsoid) should be considered in the direct georeferencing. Otherwise, an error is imposed for calculating the exterior orientation parameters of the aerial images and aerial laser scanning. This study determines the DOV using the EGM2008 model and gravity data in Sweden. The impact of the DOVs on horizontal and vertical coordinates, considering different flight altitudes and camera field of view, is assessed. The results confirm that the calculated DOV components using the EGM2008 model are sufficiently accurate for aerial mapping system purposes except for mountainous areas because the topographic signal is not modelled correctly. Numéro de notice : A2022-937 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : 10.1111/phor.12421 Date de publication en ligne : 25/07/2022 En ligne : https://doi.org/10.1111/phor.12421 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102683
in Photogrammetric record > vol 37 n° 179 (September 2022) . - pp 285 - 305[article]Discontinuity interpretation and identification of potential rockfalls for high-steep slopes based on UAV nap-of-the-object photogrammetry / Wei Wang in Computers & geosciences, vol 166 (September 2022)
[article]
Titre : Discontinuity interpretation and identification of potential rockfalls for high-steep slopes based on UAV nap-of-the-object photogrammetry Type de document : Article/Communication Auteurs : Wei Wang ; Wenbo Zhao, Auteur ; Bo Chai, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 105191 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] Chine
[Termes IGN] discontinuité
[Termes IGN] éboulement
[Termes IGN] extraction de données
[Termes IGN] front rocheux
[Termes IGN] image à haute résolution
[Termes IGN] image captée par drone
[Termes IGN] matrice
[Termes IGN] pente
[Termes IGN] photogrammétrie aérienne
[Termes IGN] profondeur
[Termes IGN] risque naturel
[Termes IGN] semis de points
[Termes IGN] texture d'imageRésumé : (auteur) Discontinuity extraction and interpretation of fractured masses is of high importance when analyzing rock slope stability. Regarding high-steep slopes, which are areas that are difficult to reach, traditional methods to obtain discontinuities, such as the sample window method (SWM), are unlikely to be implemented, resulting in challenges for the identification of potential rockfalls. With the development of the unmanned ariel vehicle (UAV) technology, discontinuity extraction can overcome by noncontact photogrammetry. However, there is still a lack of comprehensive and practical solutions to fulfill rockfall identification from field investigation to in-door analysis. For this purpose, a practical case study was carried out in Wanzhou, Chongqing, China, where a 400 m vertical rock slope prone to rockfall was collected as a typical example. The centimeter-level 3D Textured Digital Outcrop Model (TDOM) and dense Point Cloud (PC) were established using high-resolution photos acquired by nap-of-the-object photogrammetry. The discontinuity of the fractured mass was interpreted by fully taking advantage of both 2D images (texture information-dominated) and 3D PCs (depth information-dominated). Furthermore, a new parameter rock cavity rate (RCR) and the corresponding semiautomatic extraction method based on point clouds are proposed. Subsequently, the possibility of various failure modes and their joint combinations were determined by kinematic analysis. Finally, the rock slope stability was determined using a matrix that considers the slope mass rating (SMR) value and the parameter RCR. The proposed process flow and relevant techniques in this study provide an operable and practical solution for further application regarding discontinuity interpretation and potential rockfall identification on high-steep slopes. Numéro de notice : A2022-655 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2022.105191 Date de publication en ligne : 08/07/2022 En ligne : https://doi.org/10.1016/j.cageo.2022.105191 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101504
in Computers & geosciences > vol 166 (September 2022) . - n° 105191[article]A high-resolution gravimetric geoid model for Kingdom of Saudi Arabia / Ahmed Zaki in Survey review, vol 54 n° 386 (September 2022)
[article]
Titre : A high-resolution gravimetric geoid model for Kingdom of Saudi Arabia Type de document : Article/Communication Auteurs : Ahmed Zaki, Auteur ; Saad Mogren, Auteur Année de publication : 2022 Article en page(s) : pp 375 - 390 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] Arabie Saoudite
[Termes IGN] géoïde altimétrique
[Termes IGN] géoïde gravimétrique
[Termes IGN] geoïde marin
[Termes IGN] intégrale de Stokes
[Termes IGN] modèle de géopotentiel
[Termes IGN] modèle numérique de surface
[Termes IGN] nivellement avec assistance GPS
[Termes IGN] transformation rapide de FourierRésumé : (auteur) A high-resolution gravimetric geoid model for the Kingdom of Saudi Arabia area was determined. A data set of 459,848 land gravity, 80,632 shipborne marine gravity data, DTU17 altimetry gravity model, and XGM2019e global geopotential model. The computation strategy followed for modelling of the gravimetric geoid is based on the Remove-Compute-Restore with Residual Terrain Model reduction and the 1D- Fast Fourier Transform approach technique. The geoid heights have been determined by using the Stokes integral with Wong–Gore modification. The accuracy of the resulting geoid models was evaluated by comparing them with 5385 GPS/levelling points. The geoid accuracy over all the kingdom is better than 11 cm in STD sense and the comparison in sub-areas obtained accuracy range from 2.8 to 11.9 cm according to the density of gravity observations. Numéro de notice : A2022-657 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2021.1944544 Date de publication en ligne : 29/06/2021 En ligne : https://doi.org/10.1080/00396265.2021.1944544 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101508
in Survey review > vol 54 n° 386 (September 2022) . - pp 375 - 390[article]Historical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine / Luis Carrasco in ISPRS Journal of photogrammetry and remote sensing, vol 191 (September 2022)
[article]
Titre : Historical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine Type de document : Article/Communication Auteurs : Luis Carrasco, Auteur ; Go Fujita, Auteur ; Kensuke Kito, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 277 - 289 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] cartographie historique
[Termes IGN] détection de changement
[Termes IGN] Google Earth
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] indice de végétation
[Termes IGN] Japon
[Termes IGN] phénologie
[Termes IGN] photographie aérienne
[Termes IGN] réflectance de surface
[Termes IGN] rizière
[Termes IGN] signature spectraleRésumé : (auteur) Mapping the expansion or reduction of rice fields is fundamental for food and water security, greenhouse gas emission accounting, and environmental management. The historical mapping of rice fields with satellite images is challenging because of the limited availability of remote sensing and training data from past decades. The use of phenology-based algorithms has been proposed for mapping rice fields because they can take advantage of rice fields’ characteristic spectral signature during the transplanting phase and do not need training data. However, in order to employ phenology-based algorithms effectively for the historical rice mapping of large areas, we need to incorporate automatized methods able to deal with non-usable data (e.g., cloud cover) and with spatial inconsistencies in the number of available images for each pixel. Here we propose the combination of a pixel-based, phenological algorithm with the temporal aggregation of all available Landsat images to produce national level historical maps of rice fields in Japan from the 1980s onwards. We used temporally aggregated metrics (median, percentiles, etc.), derived from spectral indices of a large number of images within the Google Earth Engine, to minimize the issue of inconsistent image availability and reduce the effects of outliers in phenology-based algorithms. We produced seven rice field maps, for the periods 1985–89, 1990–94, 1995–99, 2000–04, 2005–09, 2010–14, and 2015–19. The overall map accuracies ranged from 83% to 95% when validated with visually interpreted aerial photography. We detected a 23% decrease in the area of rice fields at a country level, although the changes varied greatly among prefectures. Here we present the first freely available historical rice field maps of Japan from the 1980s onwards, together with the source code, and a web application that enables the exploration of the maps and data relating to the derived rice field area changes. The application of temporal aggregation is promising for dealing with the gap-filling of large amounts of satellite data, reducing the issue of data outliers and providing an effective use of the historical Landsat archive for phenology-based crop detection algorithms. Our maps could greatly help researchers, conservationists and policymakers studying the drivers and consequences of rice field changes, and our methods could be extrapolated to map rice fields at large scales in other regions of the world. Numéro de notice : A2022-665 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.07.018 Date de publication en ligne : 08/08/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.07.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101527
in ISPRS Journal of photogrammetry and remote sensing > vol 191 (September 2022) . - pp 277 - 289[article]Human perception evaluation system for urban streetscapes based on computer vision algorithms with attention mechanisms / Yunhao Li in Transactions in GIS, vol 26 n° 6 (September 2022)PermalinkLearning indoor point cloud semantic segmentation from image-level labels / Youcheng Song in The Visual Computer, vol 38 n° 9 (September 2022)PermalinkMapping annual urban evolution process (2001–2018) at 250 m: A normalized multi-objective deep learning regression / Haoyu Wang in Remote sensing of environment, vol 278 (September 2022)PermalinkMapping individual abandoned houses across cities by integrating VHR remote sensing and street view imagery / Shengyuan Zou in International journal of applied Earth observation and geoinformation, vol 113 (September 2022)PermalinkPKS: A photogrammetric key-frame selection method for visual-inertial systems built on ORB-SLAM3 / Arash Azimi in ISPRS Journal of photogrammetry and remote sensing, vol 191 (September 2022)PermalinkPoint-of-interest detection from Weibo data for map updating / Xue Yang in Transactions in GIS, vol 26 n° 6 (September 2022)PermalinkStructured binary neural networks for image recognition / Bohan Zhuang in International journal of computer vision, vol 130 n° 9 (September 2022)PermalinkTowards a global seasonal and permanent reference water product from Sentinel-1/2 data for improved flood mapping / Sandro Martinis in Remote sensing of environment, vol 278 (September 2022)PermalinkDetection of potential gold mineralization areas using MF-fuzzy approach on multispectral data / Tohid Nouri in Geocarto international, Vol 37 n° 17 ([20/08/2022])PermalinkComparison of PBIA and GEOBIA classification methods in classifying turbidity in reservoirs / Douglas Stefanello Facco in Geocarto international, vol 37 n° 16 ([15/08/2022])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)PermalinkAssessing structural complexity of individual scots pine trees by comparing terrestrial laser scanning and photogrammetric point clouds / Noora Tienaho in Forests, Vol 13 n° 8 (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)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)PermalinkDetection and characterization of slow-moving landslides in the 2017 Jiuzhaigou earthquake area by combining satellite SAR observations and airborne Lidar DSM / Jiehua Cai in Engineering Geology, vol 305 (August 2022)PermalinkEffective CBIR based on hybrid image features and multilevel approach / D. Latha in Multimedia tools and applications, vol 81 n° 20 (August 2022)PermalinkGround surface elevation changes over permafrost areas revealed by multiple GNSS interferometric reflectometry / Yufeng Hu in Journal of geodesy, vol 96 n° 8 (August 2022)PermalinkHyperspectral unmixing using transformer network / Preetam Ghosh in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)PermalinkIdentification of urban agglomeration spatial range based on social and remote-sensing data - For evaluating development level of urban agglomerations / Shuai Zhang in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)PermalinkIncorporation of digital elevation model, normalized difference vegetation index, and Landsat-8 data for land use land cover mapping / Jwan Al-Doski in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 8 (August 2022)PermalinkIntegrating post-processing kinematic (PPK) structure-from-motion (SfM) with unmanned aerial vehicle (UAV) photogrammetry and digital field mapping for structural geological analysis / Daniele Cirillo in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)PermalinkA pipeline for automated processing of Corona KH-4 (1962-1972) stereo imagery / Sajid Ghuffar in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)PermalinkSpatial–spectral attention network guided with change magnitude image for land cover change detection using remote sensing images / Zhiyong Lv in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)PermalinkTracking annual dynamics of mangrove forests in mangrove National Nature Reserves of China based on time series Sentinel-2 imagery during 2016–2020 / Rong Zhang in International journal of applied Earth observation and geoinformation, vol 112 (August 2022)PermalinkTransfer learning from citizen science photographs enables plant species identification in UAV imagery / Salim Soltani in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 5 (August 2022)PermalinkUAV-borne, LiDAR-based elevation modelling: a method for improving local-scale urban flood risk assessment / Katerina Trepekli in Natural Hazards, vol 113 n° 1 (August 2022)PermalinkUncertainty interval estimates for computing slope and aspect from a gridded digital elevation model / Carlos López-Vázquez in International journal of geographical information science IJGIS, vol 36 n° 8 (August 2022)PermalinkPS-InSAR based validated landslide susceptibility modelling: a case study of Ghizer valley, Northern Pakistan / Sajid Hussain in Geocarto international, vol 37 n° 13 ([15/07/2022])PermalinkValidation of a corner reflector installation at Côte d’Azur multi-technique geodetic observatory / Xavier Collilieux in Advances in space research, vol 70 n° 2 (15 July 2022)PermalinkAdaptive transfer of color from images to maps and visualizations / Mingguang Wu in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)PermalinkAdvancements in underground mine surveys by using SLAM-enabled handheld laser scanners / Artu Ellmann in Survey review, vol 54 n° 385 (July 2022)PermalinkDiscriminative information restoration and extraction for weakly supervised low-resolution fine-grained image recognition / Tiantian Yan in Pattern recognition, vol 127 (July 2022)PermalinkExploring the vertical dimension of street view image based on deep learning: a case study on lowest floor elevation estimation / Huan Ning in International journal of geographical information science IJGIS, vol 36 n° 7 (juillet 2022)PermalinkFusing Sentinel-2 and Landsat 8 satellite images using a model-based method / Jakob Sigurdsson in Remote sensing, vol 14 n° 13 (July-1 2022)PermalinkFusion of GNSS and InSAR time series using the improved STRE model: applications to the San Francisco bay area and Southern California / Huineng Yan in Journal of geodesy, vol 96 n° 7 (July 2022)PermalinkGANmapper: geographical data translation / Abraham Noah Wu in International journal of geographical information science IJGIS, vol 36 n° 7 (juillet 2022)PermalinkGeographic knowledge graph attribute normalization: Improving the accuracy by fusing optimal granularity clustering and co-occurrence analysis / Chuan Yin in ISPRS International journal of geo-information, vol 11 n° 7 (July 2022)PermalinkInvestigating the ability to identify new constructions in urban areas using images from unmanned aerial vehicles, Google Earth, and Sentinel-2 / Fahime Arabi Aliabad in Remote sensing, vol 14 n° 13 (July-1 2022)PermalinkInvestigating the role of image retrieval for visual localization / Martin Humenberger in International journal of computer vision, vol 130 n° 7 (July 2022)PermalinkLidar point-to-point correspondences for rigorous registration of kinematic scanning in dynamic networks / Aurélien Brun in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)PermalinkQuantifying the influence of plot-level uncertainty in above ground biomass up scaling using remote sensing data in central Indian dry deciduous forest / Thangavelu Mayamanikandan in Geocarto international, vol 37 n° 12 ([01/07/2022])PermalinkA second-order attention network for glacial lake segmentation from remotely sensed imagery / Shidong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)PermalinkSemantic feature-constrained multitask siamese network for building change detection in high-spatial-resolution remote sensing imagery / Qian Shen in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)PermalinkSimulation-driven 3D forest growth forecasting based on airborne topographic LiDAR data and shading / Štefan Kohek in International journal of applied Earth observation and geoinformation, vol 111 (July 2022)PermalinkStreet-view imagery guided street furniture inventory from mobile laser scanning point clouds / Yuzhou Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)Permalink