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A novel method based on deep learning, GIS and geomatics software for building a 3D city model from VHR satellite stereo imagery / Massimiliano Pepe in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)
[article]
Titre : A novel method based on deep learning, GIS and geomatics software for building a 3D city model from VHR satellite stereo imagery Type de document : Article/Communication Auteurs : Massimiliano Pepe, Auteur ; Domenica Costantino, Auteur ; Vincenzo Saverio Alfio, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 697 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de Gram-Schmidt
[Termes IGN] apprentissage profond
[Termes IGN] ArcGIS
[Termes IGN] détection du bâti
[Termes IGN] empreinte
[Termes IGN] hauteur du bâti
[Termes IGN] image à très haute résolution
[Termes IGN] image Worldview
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle numérique de surface
[Termes IGN] Oman
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] reconnaissance automatique
[Termes IGN] système d'information géographiqueRésumé : (auteur) The aim of the paper is to identify a suitable method for the construction of a 3D city model from stereo satellite imagery. In order to reach this goal, it is necessary to build a workflow consisting of three main steps: (1) Increasing the geometric resolution of the color images through the use of pan-sharpening techniques, (2) identification of the buildings’ footprint through deep-learning techniques and, finally, (3) building an algorithm in GIS (Geographic Information System) for the extraction of the elevation of buildings. The developed method was applied to stereo imagery acquired by WorldView-2 (WV-2), a commercial Earth-observation satellite. The comparison of the different pan-sharpening techniques showed that the Gram–Schmidt method provided better-quality color images than the other techniques examined; this result was deduced from both the visual analysis of the orthophotos and the analysis of quality indices (RMSE, RASE and ERGAS). Subsequently, a deep-learning technique was applied for pan sharpening an image in order to extract the footprint of buildings. Performance indices (precision, recall, overall accuracy and the F1measure) showed an elevated accuracy in automatic recognition of the buildings. Finally, starting from the Digital Surface Model (DSM) generated by satellite imagery, an algorithm built in the GIS environment allowed the extraction of the building height from the elevation model. In this way, it was possible to build a 3D city model where the buildings are represented as prismatic solids with flat roofs, in a fast and precise way. Numéro de notice : A2021-801 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10100697 Date de publication en ligne : 14/10/2021 En ligne : https://doi.org/10.3390/ijgi10100697 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98853
in ISPRS International journal of geo-information > vol 10 n° 10 (October 2021) . - n° 697[article]Phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation / Peng Liu in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)
[article]
Titre : Phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation Type de document : Article/Communication Auteurs : Peng Liu, Auteur ; Zhenhong Li, Auteur ; Shisheng Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 14 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] chevauchement
[Termes IGN] Chine
[Termes IGN] discontinuité
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] modèle numérique de surface
[Termes IGN] ombre
[Termes IGN] segmentation
[Termes IGN] semis de pointsRésumé : (auteur) Staring spotlight images with a spatial resolution of up to tens of centimeters are good data sources for urban applications including displacement mapping. However, phase discontinuities, layover, and shadowing effect are also associated with staring spotlight interferograms, adding to the difficulties in height estimation and spatial phase unwrapping. The scattering mechanism of the staring spotlight images in the urban environment is complicated, thus it is difficult to simulate and remove the reference height of staring spotlight interferograms directly. In addition, global spatial phase unwrapping networks tend to smooth phase discontinuities. With the aim of implementing height estimation and phase unwrapping for TerraSAR-X Staring Spotlight interferograms, a workflow for phase unmixing of TerraSAR-X staring spotlight interferograms is proposed in this paper. The PS height is estimated in the baseline domain rather than the spatial domain. Taking into account the length and height change of each connection, the spatial phase unwrapping network is adjusted and segmented into isolated networks. The connected components of the adjusted spatial phase unwrapping network can be identified using graph theory. Spatial phase unwrapping is implemented in individual networks. The unfolded height phase is separated from the unwrapped phase, and the remaining phase is deformation dominated. Compared with the traditional global spatial phase unwrapping method, this study demonstrates the feasibility of the proposed least squares parameter search and graph partition based workflow in urban area, for phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation, as evidenced by external LiDAR DSM and temperature records. Numéro de notice : A2021-652 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.08.007 Date de publication en ligne : 14/08/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.08.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98382
in ISPRS Journal of photogrammetry and remote sensing > vol 180 (October 2021) . - pp 14 - 28[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2021101 SL Revue Centre de documentation Revues en salle Disponible 081-2021103 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021102 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Quantifying historical landscape change with repeat photography: an accuracy assessment of geospatial data obtained through monoplotting / Ulrike Bayr in International journal of geographical information science IJGIS, vol 35 n° 10 (October 2021)
[article]
Titre : Quantifying historical landscape change with repeat photography: an accuracy assessment of geospatial data obtained through monoplotting Type de document : Article/Communication Auteurs : Ulrike Bayr, Auteur Année de publication : 2021 Article en page(s) : pp 2026 - 2046 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse diachronique
[Termes IGN] analyse du paysage
[Termes IGN] angle d'incidence
[Termes IGN] détection de changement
[Termes IGN] données anciennes
[Termes IGN] données multitemporelles
[Termes IGN] image oblique
[Termes IGN] modèle numérique de terrain
[Termes IGN] monorestitution
[Termes IGN] Norvège
[Termes IGN] orthoimage géoréférencée
[Termes IGN] photographie aérienne
[Termes IGN] photographie terrestre
[Termes IGN] point d'appui
[Termes IGN] précision des donnéesRésumé : (auteur) Traditional landscape photographs reaching back until the second half of the nineteenth century represent a valuable image source for the study of long-term landscape change. Due to the oblique perspective and the lack of geographical reference, landscape photographs are hardly used for quantitative research. In this study, oblique landscape photographs from the Norwegian landscape monitoring program are georeferenced using the WSL Monoplotting Tool with the aim of evaluating the accuracy of point and polygon features. In addition, the study shows how the resolution of the chosen digital terrain model and other factors affect accuracy. Points mapped on the landscape photograph had a mean displacement of 1.52 m from their location on a corresponding aerial photograph, while mapped areas deviated on average 5.6% in size. The resolution of the DTM, the placement of GCPs and the angle of incidence were identified as relevant factors to achieve accurate geospatial data. An example on forest expansion at the abandoned mountain farm Flysetra in Mid-Norway demonstrates how repeat photography facilitates the georectification process in the absence of reliable ground control points (GCPs) in very old photographs. Numéro de notice : A2021-656 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1871910 Date de publication en ligne : 20/01/2021 En ligne : https://doi.org/10.1080/13658816.2021.1871910 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98392
in International journal of geographical information science IJGIS > vol 35 n° 10 (October 2021) . - pp 2026 - 2046[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)
[article]
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'imageRésumé : (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
in Transactions in GIS > vol 25 n° 5 (October 2021) . - pp 2529 - 2552[article]Automatic building detection with polygonizing and attribute extraction from high-resolution images / Samitha Daranagama in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)
[article]
Titre : Automatic building detection with polygonizing and attribute extraction from high-resolution images Type de document : Article/Communication Auteurs : Samitha Daranagama, Auteur ; Apichon Witayangkurn, Auteur Année de publication : 2021 Article en page(s) : n° 606 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de Douglas-Peucker
[Termes IGN] apprentissage profond
[Termes IGN] détection du bâti
[Termes IGN] image à haute résolution
[Termes IGN] image captée par drone
[Termes IGN] lissage de courbe
[Termes IGN] orthophotoplan numérique
[Termes IGN] polygonation
[Termes IGN] segmentation sémantiqueRésumé : (auteur) Buildings can be introduced as a fundamental element for forming a city. Therefore, up-to-date building maps have become vital for many applications, including urban mapping and urban expansion analysis. With the development of deep learning, segmenting building footprints from high-resolution remote sensing imagery has become a subject of intense study. Here, a modified version of the U-Net architecture with a combination of pre- and post-processing techniques was developed to extract building footprints from high-resolution aerial imagery and unmanned aerial vehicle (UAV) imagery. Data pre-processing with the logarithmic correction image enhancing algorithm showed the most significant improvement in the building detection accuracy for aerial images; meanwhile, the CLAHE algorithm improved the most concerning UAV images. This study developed a post-processing technique using polygonizing and polygon smoothing called the Douglas–Peucker algorithm, which made the building output directly ready to use for different applications. The attribute information, land use data, and population count data were applied using two open datasets. In addition, the building area and perimeter of each building were calculated as geometric attributes. Numéro de notice : A2021-684 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/ijgi10090606 Date de publication en ligne : 14/09/2021 En ligne : https://doi.org/10.3390/ijgi10090606 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98410
in ISPRS International journal of geo-information > vol 10 n° 9 (September 2021) . - n° 606[article]Classification of tree species in a heterogeneous urban environment using object-based ensemble analysis and World View-2 satellite imagery / Simbarashe Jombo in Applied geomatics, vol 13 n° 3 (September 2021)PermalinkConiferous and broad-leaved forest distinguishing using L-band polarimetric SAR data / Fang Shang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)PermalinkA deep translation (GAN) based change detection network for optical and SAR remote sensing images / Xinghua Li in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)PermalinkDouble adaptive intensity-threshold method for uneven Lidar data to extract road markings / Chengming Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)PermalinkMetaheuristics for the positioning of 3D objects based on image analysis of complementary 2D photographs / Arnaud Flori in Machine Vision and Applications, vol 32 n° 5 (September 2021)PermalinkThree-dimensional building change detection using object-based image analysis (case study: Tehran) / Fatemeh Tabib Mahmoudi in Applied geomatics, vol 13 n° 3 (September 2021)PermalinkUtilisation de l'apprentissage profond dans la modélisation 3D urbaine [Partie 1] / Hamza Ben Addou in Géomatique expert, n° 135 (septembre 2021)PermalinkConnecting images through sources: Exploring low-data, heterogeneous instance retrieval / Dimitri Gominski in Remote sensing, vol 13 n° 16 (August-2 2021)PermalinkMonitoring forest disturbance using time-series MODIS NDVI in Michoacán, Mexico / Yao Gao in Geocarto international, vol 36 n° 15 ([15/08/2021])PermalinkBackground segmentation in multicolored illumination environments / Nikolas Ladas in The Visual Computer, vol 37 n° 8 (August 2021)PermalinkMapping essential urban land use categories with open big data: Results for five metropolitan areas in the United States of America / Bin Chen in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkRapid and large-scale mapping of flood inundation via integrating spaceborne synthetic aperture radar imagery with unsupervised deep learning / Xin Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkComNet: combinational neural network for object detection in UAV-borne thermal images / Minglei Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)PermalinkComparison of classification methods for urban green space extraction using very high resolution worldview-3 imagery / S. Vigneshwaran in Geocarto international, vol 36 n° 13 ([15/07/2021])PermalinkDetecting structural changes induced by Heterobasidion root rot on Scots pines using terrestrial laser scanning / Timo P Pitkänen in Forest ecology and management, vol 492 (July-15 2021)PermalinkCNN-based RGB-D salient object detection: Learn, select, and fuse / Hao Chen in International journal of computer vision, vol 129 n° 7 (July 2021)PermalinkDigital camera calibration for cultural heritage documentation: the case study of a mass digitization project of religious monuments in Cyprus / Evagoras Evagorou in European journal of remote sensing, vol 54 sup 1 (2021)PermalinkFlood depth mapping in street photos with image processing and deep neural networks / Bahareh Alizadeh Kharazi in Computers, Environment and Urban Systems, vol 88 (July 2021)PermalinkFluvial gravel bar mapping with spectral signal mixture analysis / Liza Stančič in European journal of remote sensing, vol 54 sup 1 (2021)PermalinkGlacier elevation change in the Western Qilian mountains as observed by TerraSAR-X/TanDEM-X images / Qibing Zhang in Geocarto international, vol 36 n° 12 ([01/07/2021])Permalink