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Disaster intensity-based selection of training samples for remote sensing building damage classification / Luis Moya in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)
[article]
Titre : Disaster intensity-based selection of training samples for remote sensing building damage classification Type de document : Article/Communication Auteurs : Luis Moya, Auteur ; Christian Geiss, Auteur ; Masakazu Hashimoto, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 8288 - 8304 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] déformation d'édifice
[Termes IGN] détection de changement
[Termes IGN] détection du bâti
[Termes IGN] dommage matériel
[Termes IGN] données de terrain
[Termes IGN] échantillonnage de données
[Termes IGN] image optique
[Termes IGN] inondation
[Termes IGN] séismeRésumé : (auteur) Previous applications of machine learning in remote sensing for the identification of damaged buildings in the aftermath of a large-scale disaster have been successful. However, standard methods do not consider the complexity and costs of compiling a training data set after a large-scale disaster. In this article, we study disaster events in which the intensity can be modeled via numerical simulation and/or instrumentation. For such cases, two fully automatic procedures for the detection of severely damaged buildings are introduced. The fundamental assumption is that samples that are located in areas with low disaster intensity mainly represent nondamaged buildings. Furthermore, areas with moderate to strong disaster intensities likely contain damaged and nondamaged buildings. Under this assumption, a procedure that is based on the automatic selection of training samples for learning and calibrating the standard support vector machine classifier is utilized. The second procedure is based on the use of two regularization parameters to define the support vectors. These frameworks avoid the collection of labeled building samples via field surveys and/or visual inspection of optical images, which requires a significant amount of time. The performance of the proposed method is evaluated via application to three real cases: the 2011 Tohoku-Oki earthquake–tsunami, the 2016 Kumamoto earthquake, and the 2018 Okayama floods. The resulted accuracy ranges between 0.85 and 0.89, and thus, it shows that the result can be used for the rapid allocation of affected buildings. Numéro de notice : A2021-711 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3046004 Date de publication en ligne : 13/01/2021 En ligne : https://doi.org/10.1109/TGRS.2020.3046004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98615
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 10 (October 2021) . - pp 8288 - 8304[article]Extracting 3D indoor maps with any shape accurately using building information modeling data / Qi Qiu in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)
[article]
Titre : Extracting 3D indoor maps with any shape accurately using building information modeling data Type de document : Article/Communication Auteurs : Qi Qiu, Auteur ; Mingjun Wang, Auteur ; Qingsheng Xie, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 700 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] carroyage
[Termes IGN] carte d'intérieur
[Termes IGN] carte en 3D
[Termes IGN] conception assistée par ordinateur
[Termes IGN] détection de contours
[Termes IGN] grille
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] service fondé sur la positionRésumé : (auteur) Indoor maps lay the foundation for most indoor location-based services (LBS). Building Information Modeling (BIM) data contains multiple dimensional computer-aided design information. Some studies have utilized BIM data to automatically extract 3D indoor maps. A complete 3D indoor map consists of both floor-level maps and cross-floor paths. Currently, the floor-level indoor maps are mainly either grid-based maps or topological maps, and the cross-floor path generation schemes are not adaptive to building elements with irregular 3D shapes. To address these issues, this study proposes a novel scheme to extract an accurate 3D indoor map with any shape using BIM data. Firstly, this study extracts grid-based maps from BIM data and generates the topological maps directly through the grid-based maps using image thinning. A novel hybrid indoor map, termed Grid-Topological map, is then formed by the grid-based maps and topological maps jointly. Secondly, this study obtains the cross-floor paths from cross-floor building elements by a four-step process, namely X-Z projection, boundary extraction, X-Z topological path generation, and path-BIM intersection. Finally, experiments on eight typical types of cross-floor building elements and three multi-floor real-world buildings were conducted to prove the effectiveness of the proposed scheme, the average accuracy rates of the evaluated paths are higher than 88%. This study will advance the 3D indoor maps generation and inspire the application of indoor maps in indoor LBS, indoor robots, and 3D geographic information systems. Numéro de notice : A2021-778 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10100700 Date de publication en ligne : 14/10/2021 En ligne : https://doi.org/10.3390/ijgi10100700 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98842
in ISPRS International journal of geo-information > vol 10 n° 10 (October 2021) . - n° 700[article]A feature based change detection approach using multi-scale orientation for multi-temporal SAR images / R. Vijaya Geetha in European journal of remote sensing, vol 54 sup 2 (2021)
[article]
Titre : A feature based change detection approach using multi-scale orientation for multi-temporal SAR images Type de document : Article/Communication Auteurs : R. Vijaya Geetha, Auteur ; S. Kalaivani, Auteur Année de publication : 2021 Article en page(s) : pp 248 - 264 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse de groupement
[Termes IGN] anisotropie
[Termes IGN] chatoiement
[Termes IGN] classification non dirigée
[Termes IGN] classification par nuées dynamiques
[Termes IGN] détection de changement
[Termes IGN] filtre de Gabor
[Termes IGN] image multitemporelle
[Termes IGN] image radar moirée
[Termes IGN] matrice de confusion
[Termes IGN] transformation en ondelettesRésumé : (auteur) Excellent operation regardless of weather conditions and superior resolution independent of sensor light are the most attractive and desired features of synthetic aperture radar (SAR) imagery. This paper proposes an exclusive multi-scale with multiple orientation approach for multi-temporal SAR images. This approach integrates pre-processing and change detection. Pre-processing is performed on the SAR imagery through speckle reducing anisotropic diffusion and discrete wavelet transform. The processed speckle-free images are designed by Log-Gabor filter bank in terms of multi-scale with multiple orientations. The maximum magnitude of multiple orientations is concatenated to obtain feature-based scale representation. Each scale is dealt with multiple orientations and is compared by band-wise subtraction to retrieve difference image (DI) coefficient. The series of the difference coefficients from each scale are add-on together to estimate a DI. Thus, the resultant image of multi-scale orientation gives perception of detailed information with specific contour. Constrained k-means clustering algorithm is preferred to achieve change and un-change map. Performance of the proposed approach is validated on three real SAR image datasets. The effective change detection is examined by using confusion matrix parameters. Experimental results are described to show the efficacy of the proposed approach. Numéro de notice : A2021-819 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2020.1759457 Date de publication en ligne : 12/06/2020 En ligne : https://doi.org/10.1080/22797254.2020.1759457 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98924
in European journal of remote sensing > vol 54 sup 2 (2021) . - pp 248 - 264[article]Geomorphological mapping and anthropogenic landform change in an urbanizing watershed using structure-from-motion photogrammetry and geospatial modeling techniques / Peter G. Chirico in Journal of maps, vol 17 n° 4 (October 2021)
[article]
Titre : Geomorphological mapping and anthropogenic landform change in an urbanizing watershed using structure-from-motion photogrammetry and geospatial modeling techniques Type de document : Article/Communication Auteurs : Peter G. Chirico, Auteur ; Sarah E. Bergstresser, Auteur ; Jessica D. DeWitt, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 241 - 252 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] aménagement du territoire
[Termes IGN] archives
[Termes IGN] bassin hydrographique
[Termes IGN] cartographie géomorphologique
[Termes IGN] croissance urbaine
[Termes IGN] détection de changement
[Termes IGN] érosion anthropique
[Termes IGN] modèle numérique de surface
[Termes IGN] modélisation spatiale
[Termes IGN] photogrammétrie numérique
[Termes IGN] photographie aérienne
[Termes IGN] structure-from-motion
[Termes IGN] Virginie (Etats-Unis)Résumé : (auteur) Increasing urbanization and suburban growth in cities globally has highlighted the importance of land planning using detailed geomorphologic maps that depict anthropogenic landform changes. Such mapping provides information crucial for land management, hazard identification, and the management of the challenges arising from urbanization. The development and use of quantitative and repeatable methods to map anthropogenic and natural processes are required to advance the science of urban geomorphological mapping. This study investigated the application of geospatial modeling, structure-from-motion (SfM) photogrammetric methods and DEM differencing as means of quantifying anthropogenic landform changes from archival aerial imagery. Anthropogenic landforms were incorporated into a detailed geomorphologic map in an urbanizing watershed located in the Washington, D.C. metropolitan suburb of Vienna, Virginia. Numéro de notice : A2021-813 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1080/17445647.2020.1746419 Date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.1080/17445647.2020.1746419 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98887
in Journal of maps > vol 17 n° 4 (October 2021) . - pp 241 - 252[article]GPRInvNet: Deep learning-based ground-penetrating radar data inversion for tunnel linings / Bin Liu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)
[article]
Titre : GPRInvNet: Deep learning-based ground-penetrating radar data inversion for tunnel linings Type de document : Article/Communication Auteurs : Bin Liu, Auteur ; Yuxiao Ren, Auteur ; Hanchi Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 8305 - 8325 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] apprentissage profond
[Termes IGN] cible cachée
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] géolocalisation par radar pénétrant GPR
[Termes IGN] reconstruction d'image
[Termes IGN] revêtement
[Termes IGN] tunnelRésumé : (auteur) A DNN architecture referred to as GPRInvNet was proposed to tackle the challenges of mapping the ground-penetrating radar (GPR) B-Scan data to complex permittivity maps of subsurface structures. The GPRInvNet consisted of a trace-to-trace encoder and a decoder. It was specially designed to take into account the characteristics of GPR inversion when faced with complex GPR B-Scan data, as well as addressing the spatial alignment issues between time-series B-Scan data and spatial permittivity maps. It displayed the ability to fuse features from several adjacent traces on the B-Scan data to enhance each trace, and then further condense the features of each trace separately. As a result, the sensitive zones on the permittivity maps spatially aligned to the enhanced trace could be reconstructed accurately. The GPRInvNet has been utilized to reconstruct the permittivity map of tunnel linings. A diverse range of dielectric models of tunnel linings containing complex defects has been reconstructed using GPRInvNet. The results have demonstrated that the GPRInvNet is capable of effectively reconstructing complex tunnel lining defects with clear boundaries. Comparative results with existing baseline methods also demonstrated the superiority of the GPRInvNet. For the purpose of generalizing the GPRInvNet to real GPR data, some background noise patches recorded from practical model testing were integrated into the synthetic GPR data to retrain the GPRInvNet. The model testing has been conducted for validation, and experimental results revealed that the GPRInvNet had also achieved satisfactory results with regard to the real data. Numéro de notice : A2021-710 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3046454 Date de publication en ligne : 13/01/2021 En ligne : https://doi.org/10.1109/TGRS.2020.3046454 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98610
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 10 (October 2021) . - pp 8305 - 8325[article]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)PermalinkPhase 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)PermalinkQuantifying 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)PermalinkRecognition 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)PermalinkAutomatic 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)PermalinkClassification 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)Permalink