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A high-resolution satellite DEM filtering method assisted with building segmentation / Yihui Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 6 (June 2021)
[article]
Titre : A high-resolution satellite DEM filtering method assisted with building segmentation Type de document : Article/Communication Auteurs : Yihui Li, Auteur ; Fang Gao, Auteur ; Wentao Li, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 421 - 430 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection du bâti
[Termes IGN] filtrage numérique d'image
[Termes IGN] filtre adaptatif
[Termes IGN] image à haute résolution
[Termes IGN] Kappa de Cohen
[Termes IGN] modèle numérique de surface
[Termes IGN] orthoimage
[Termes IGN] point d'appui
[Termes IGN] segmentation d'imageRésumé : (Auteur) Digital elevation model (DEM) filtering is critical in DEM production, and large-area meter-level resolution DEM is mainly generated from high-resolution satellite images. However, the current DEM filtering methods are mostly aimed at laser scanning data and tend to excessively remove ground points when processing a satellite digital surface model (DSM). To accurately filter out buildings and preserve terrain, we propose a DEM filtering algorithm using building segmentation results of orthophoto. Based on morphological filtering, our method estimates the probability of being a built-up area or mountains for DSM, and according to this probability the filtering parameters are adaptively adjusted. For robustness, our method performs the above filtering operation on DSM through a sliding-window approach, and finally the nonground points are determined by the votes of multiple filtering. Experiments against six representative data sets have shown that our method achieved superior performance than classical algorithms and commercial software. Numéro de notice : A2021-374 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.6.421 Date de publication en ligne : 01/06/2021 En ligne : https://doi.org/10.14358/PERS.87.6.421 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97827
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 6 (June 2021) . - pp 421 - 430[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2021061 SL Revue Centre de documentation Revues en salle Disponible Mask R-CNN-based building extraction from VHR satellite data in operational humanitarian action: An example related to Covid-19 response in Khartoum, Sudan / Dirk Tiede in Transactions in GIS, Vol 25 n° 3 (June 2021)
[article]
Titre : Mask R-CNN-based building extraction from VHR satellite data in operational humanitarian action: An example related to Covid-19 response in Khartoum, Sudan Type de document : Article/Communication Auteurs : Dirk Tiede, Auteur ; Gina Schwendemann, Auteur ; Ahmad Alobaidi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1213-1227 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection du bâti
[Termes IGN] échantillonnage
[Termes IGN] épidémie
[Termes IGN] gestion de crise
[Termes IGN] HRV (capteur)
[Termes IGN] image à très haute résolution
[Termes IGN] image Pléiades-HR
[Termes IGN] itération
[Termes IGN] SoudanRésumé : Auteur) Within the constraints of operational work supporting humanitarian organizations in their response to the Covid-19 pandemic, we conducted building extraction for Khartoum, Sudan. We extracted approximately 1.2 million dwellings and buildings, using a Mask R-CNN deep learning approach from a Pléiades very high-resolution satellite image with 0.5 m pixel resolution. Starting from an untrained network, we digitized a few hundred samples and iteratively increased the number of samples by validating initial classification results and adding them to the sample collection. We were able to strike a balance between the need for timely information and the accuracy of the result by combining the output from three different models, each aiming at distinctive types of buildings, in a post-processing workflow. We obtained a recall of 0.78, precision of 0.77 and F1 score of 0.78, and were able to deliver first results in only 10 days after the initial request. The procedure shows the great potential of convolutional neural network frameworks in combination with GIS routines for dwelling extraction even in an operational setting. Numéro de notice : A2021-464 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12766 Date de publication en ligne : 06/05/2021 En ligne : https://doi.org/10.1111/tgis.12766 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98060
in Transactions in GIS > Vol 25 n° 3 (June 2021) . - pp 1213-1227[article]A novel class-specific object-based method for urban change detection using high-resolution remote sensing imagery / Ting Bai in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 4 (April 2021)
[article]
Titre : A novel class-specific object-based method for urban change detection using high-resolution remote sensing imagery Type de document : Article/Communication Auteurs : Ting Bai, Auteur ; Kaimin Sun, Auteur ; Wenzhuo Li, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 249-262 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement d'occupation du sol
[Termes IGN] classe d'objets
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] détection de changement
[Termes IGN] détection du bâti
[Termes IGN] image à haute résolution
[Termes IGN] milieu urbain
[Termes IGN] segmentation multi-échelleRésumé : (Auteur) A single-scale object-based change-detection classifier can distinguish only global changes in land cover, not the more granular and local changes in urban areas. To overcome this issue, a novel class-specific object-based change-detection method is proposed. This method includes three steps: class-specific scale selection, class-specific classifier selection, and land cover change detection. The first step combines multi-resolution segmentation and a random forest to select the optimal scale for each change type in land cover. The second step links multi-scale hierarchical sampling with a classifier such as random forest, support vector machine, gradient-boosting decision tree, or Adaboost; the algorithm automatically selects the optimal classifier for each change type in land cover. The final step employs the optimal classifier to detect binary changes and from-to changes for each change type in land cover. To validate the proposed method, we applied it to two high-resolution data sets in urban areas and compared the change-detection results of our proposed method with that of principal component analysis k-means, object-based change vector analysis, and support vector machine. The experimental results show that our proposed method is more accurate than the other methods. The proposed method can address the high levels of complexity found in urban areas, although it requires historical land cover maps as auxiliary data. Numéro de notice : A2021-332 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.4.249 Date de publication en ligne : 01/04/2021 En ligne : https://doi.org/10.14358/PERS.87.4.249 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97528
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 4 (April 2021) . - pp 249-262[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2021041 SL Revue Centre de documentation Revues en salle Disponible L'oeil de l'espace / Anonyme in Géomètre, n° 2190 (avril 2021)
[article]
Titre : L'oeil de l'espace Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2021 Article en page(s) : pp 45 - 45 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] acquisition d'images
[Termes IGN] détection de changement
[Termes IGN] détection du bâti
[Termes IGN] données localisées
[Termes IGN] droit foncier
[Termes IGN] image aérienneRésumé : (Auteur) Plus rien n'échappe à la télédétection. S'il est envisageable de se cacher derrière une clôture, ce n'est plus possible depuis le ciel ou l'espace. Numéro de notice : A2021-325 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 07/04/2021 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97483
in Géomètre > n° 2190 (avril 2021) . - pp 45 - 45[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 063-2021041 RAB Revue Centre de documentation En réserve L003 Disponible Characterizing urban land changes of 30 global megacities using nighttime light time series stacks / Qiming Zheng in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)
[article]
Titre : Characterizing urban land changes of 30 global megacities using nighttime light time series stacks Type de document : Article/Communication Auteurs : Qiming Zheng, Auteur ; Qihao Weng, Auteur ; Ke Wang, Auteur Année de publication : 2021 Article en page(s) : pp 10 - 23 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse harmonique
[Termes IGN] cartographie urbaine
[Termes IGN] changement d'utilisation du sol
[Termes IGN] croissance urbaine
[Termes IGN] détection de changement
[Termes IGN] détection du bâti
[Termes IGN] éclairage public
[Termes IGN] image infrarouge
[Termes IGN] image NPP-VIIRS
[Termes IGN] mégalopole
[Termes IGN] série temporelle
[Termes IGN] zone urbaineRésumé : (auteur) Worldwide urbanization has brought about diverse types of urban land use and land cover (LULC) changes. The diversity of urban land changes, however, have been greatly under studied, since the major focus of past research has been on urban growth. In this study, we proposed a framework to characterize diverse urban land changes of 30 global megacities using monthly nighttime light time series from VIIRS data. First, we developed a Logistic-Harmonic model to fit VIIRS time series. Second, by leveraging the uniqueness of urban land change and nighttime light data, we incorporated temporal information of VIIRS time series and proposed a new classification scheme to produce monthly maps of built-up areas and to disentangle urban land changes into five categories. Third, we provided an in-depth analysis and comparison of urban land change patterns of the selected megacities. Results demonstrated that the Logistic-Harmonic model yielded a robust performance in fitting VIIRS time series. Temporal features based classification can not only significantly improve the mapping accuracy of built-up areas, especially for regions with heterogeneous built-up and non-built-up landscapes, but also promoted temporal consistency and classification efficiency. Urban land changes occurred in 51% of the built-up pixels of the megacities. Compared with urban growth, other types of urban land change, particularly land use intensification, contributed to an unexpectedly large proportion of the changes (83%). The findings of this study offer an insightful understanding on global urbanization processes in megacities, and evoke further investigation on the environmental and ecological implications of urban land changes. Numéro de notice : A2021-101 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.002 Date de publication en ligne : 16/01/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.002 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96873
in ISPRS Journal of photogrammetry and remote sensing > vol 173 (March 2021) . - pp 10 - 23[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2021031 SL Revue Centre de documentation Revues en salle Disponible 081-2021033 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021032 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Automatic filtering and 2D modeling of airborne laser scanning building point cloud / Fayez Tarsha-Kurdi in Transactions in GIS, Vol 25 n° 1 (February 2021)PermalinkAutomatic object extraction from airborne laser scanning point clouds for digital base map production / Elyta Widyaningrum (2021)PermalinkBuilding extraction from Lidar data using statistical methods / Haval Abdul-Jabbar Sadeq in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 1 (January 2021)PermalinkGeometric and semantic joint approach for the reconstruction of digital models of buildings / Pierre-Alain Langlois (2021)PermalinkPermalinkAutomatic building footprint extraction from UAV images using neural networks / Zoran Kokeza in Geodetski vestnik, vol 64 n° 4 (December 2020 - February 2021)PermalinkBuilding change detection using a shape context similarity model for LiDAR data / Xuzhe Lyu in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)PermalinkA graph convolutional network model for evaluating potential congestion spots based on local urban built environments / Kun Qin in Transactions in GIS, Vol 24 n° 5 (October 2020)PermalinkSemi-automatic building extraction from WorldView-2 imagery using taguchi optimization / Hasan Tonbul in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 9 (September 2020)PermalinkObject-based automatic multi-index built-up areas extraction method for WorldView-2 satellite imagery / Zhenhui Sun in Geocarto international, Vol 35 n° 8 ([01/06/2020])Permalink