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Improving drainage conditions of forest roads using the GIS and forest road simulator / Mehran Nasiri in Journal of forest science, vol 66 n° 9 (September 2020)
[article]
Titre : Improving drainage conditions of forest roads using the GIS and forest road simulator Type de document : Article/Communication Auteurs : Mehran Nasiri, Auteur Année de publication : 2020 Article en page(s) : pp 361 - 367 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] chemin forestier
[Termes IGN] drainage
[Termes IGN] écoulement des eaux
[Termes IGN] effondrement de terrain
[Termes IGN] hydrologie
[Termes IGN] Iran
[Termes IGN] modèle numérique de surface
[Termes IGN] réseau de drainage
[Termes IGN] système d'information géographiqueRésumé : (auteur) In this study a new method of locating culverts is presented with the composition of achieved discharge from hydrological analysis and simulated forest roads in RoadEng 3D simulator to improve drainage condition. Locating culverts was performed on a small scale (1:20 000, using GIS) and large scale (1:2 000, road geometric design simulator). The small-scale study regarding the achieved discharge from streams shows that the installation of some culverts is not necessary. The large-scale study also showed that the geometric design of forest road has a significant effect on locating culverts and its accuracy. To improve drainage conditions 6 culverts and 2 waterfronts taking into account the geometric design of forest road, hydrological conditions and appropriate intervals (155 m) have been proposed. No installation or lack of accuracy to find the best location of culverts may result in the occurrence of creep and landslide, so the cost of destruction would be several times higher than the cost of technical buildings construction. Numéro de notice : A2020-693 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.17221/16/2020-JFS Date de publication en ligne : 01/09/2020 En ligne : https://doi.org/10.17221/16/2020-JFS Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96238
in Journal of forest science > vol 66 n° 9 (September 2020) . - pp 361 - 367[article]Post‐filtering with surface orientation constraints for stereo dense image matching / Xu Huang in Photogrammetric record, vol 35 n° 171 (September 2020)
[article]
Titre : Post‐filtering with surface orientation constraints for stereo dense image matching Type de document : Article/Communication Auteurs : Xu Huang, Auteur ; Rongjun Qin, Auteur Année de publication : 2020 Article en page(s) : pp 375-401 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] filtrage numérique d'image
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle stéréoscopique
[Termes IGN] orientation d'imageRésumé : (Auteur) Dense image matching (DIM) is a critical technique when computing accurate 3D geometric information for many photogrammetric applications. Most DIM methods adopt first‐order regularisation priors for efficient matching, which often introduce stepped biases (also called fronto‐parallel biases) into the matching results. To remove these biases and compute more accurate matching results, this paper proposes a novel post‐filtering method by adjusting the surface orientation of each pixel in the matching process. The core algorithm formulates the post‐filtering as the optimisation of a global energy function with second‐order regularisation priors. A compromise solution of the energy function is computed by breaking the optimisation into a collection of sub‐optimisations of each pixel in a local adaptive window. The proposed method was compared with several state‐of‐the‐art post‐filtering methods on indoor, aerial and satellite datasets. The comparisons demonstrate that the proposed method obtains the highest post‐filtering accuracies on all datasets. Numéro de notice : A2020-437 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12333 Date de publication en ligne : 20/09/2020 En ligne : https://doi.org/10.1111/phor.12333 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95843
in Photogrammetric record > vol 35 n° 171 (September 2020) . - pp 375-401[article]Precise extraction of citrus fruit trees from a Digital Surface Model using a unified strategy: detection, delineation, and clustering / Ali Ozgun Ok in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 9 (September 2020)
[article]
Titre : Precise extraction of citrus fruit trees from a Digital Surface Model using a unified strategy: detection, delineation, and clustering Type de document : Article/Communication Auteurs : Ali Ozgun Ok, Auteur ; Asli Ozdarici-Ok, Auteur Année de publication : 2020 Article en page(s) : pp 557-569 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse de groupement
[Termes IGN] Citrus limon
[Termes IGN] détection de contours
[Termes IGN] état de l'art
[Termes IGN] extraction d'arbres
[Termes IGN] image captée par drone
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle stochastique
[Termes IGN] TurquieRésumé : (Auteur) In this study, we present an original unified strategy for the precise extraction of individual citrus fruit trees from single digital surface model (DSM) input data. A probabilistic method combining the circular shape information with the knowledge of the local maxima in the DSM has been used for the detection of the candidate trees. An active contour is applied within each detected region to extract the borders of the objects. Thereafter, all extracted objects are seamlessly divided into clusters considering a new feature data set formed by (1) the properties of trees, (2) planting parameters, and (3) neighborhood relations. This original clustering stage has led to two new contributions: (1) particular objects or clustered structures having distinctive characters and relationships other than the citrus objects can be identified and eliminated, and (2) the information revealed by clustering can be used to recover missing citrus objects within and/or nearby each cluster. The main finding of this research is that a successful clustering can provide valuable input for identifying incorrect and missing information in terms of citrus tree extraction. The proposed strategy is validated in eight test sites selected from the northern part of Mersin province of Turkey. The results achieved are also compared with the state-of-the-art methods developed for tree extraction, and the success of the proposed unified strategy is clearly highlighted. Numéro de notice : A2020-491 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.9.557 Date de publication en ligne : 01/09/2020 En ligne : https://doi.org/10.14358/PERS.86.9.557 Format de la ressource électronique : LUR article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95933
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 9 (September 2020) . - pp 557-569[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2020091 SL Revue Centre de documentation Revues en salle Disponible Thermal and spatial data integration for recreating rebuilding stages of wooden and masonry buildings / Paulina Lewińska in Photogrammetric record, vol 35 n° 171 (September 2020)
[article]
Titre : Thermal and spatial data integration for recreating rebuilding stages of wooden and masonry buildings Type de document : Article/Communication Auteurs : Paulina Lewińska, Auteur ; Kamil Maciuk, Auteur Année de publication : 2020 Article en page(s) : pp 402-425 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] conservation du patrimoine
[Termes IGN] diffusion de données
[Termes IGN] image thermique
[Termes IGN] image virtuelle
[Termes IGN] inventaire du bâti
[Termes IGN] modélisation 3D
[Termes IGN] patrimoine immobilier
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] structure-from-motion
[Termes IGN] texture d'imageRésumé : (Auteur) This paper describes the means of supporting virtual reconstruction of wooden and masonry buildings with the use of thermal infrared images. Not all remaining architectural heritage can be physically preserved. War, climate change and rapidly growing cities have caused damage and degradation to valuable historical buildings. In order to preserve them virtually, various methods of 3D modelling have been employed. This paper presents information on how to create a full 3D inventory of a building’s exterior. This includes a 3D thermal model of the building, merging thermal camera data with a spatial model, which aids the reconstruction of previous stages of a building’s existence. The authors argue that in cases when it is impossible to force heat transfer from inside the structure (via man‐made heating), 24 hours of observations using only solar heating can be sufficient to find heat bridges and other thermal anomalies that can be used for virtual reconstruction. Numéro de notice : A2020-438 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12332 Date de publication en ligne : 20/09/2020 En ligne : https://doi.org/10.1111/phor.12332 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95844
in Photogrammetric record > vol 35 n° 171 (September 2020) . - pp 402-425[article]Vehicle detection of multi-source remote sensing data using active fine-tuning network / Xin Wu in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)
[article]
Titre : Vehicle detection of multi-source remote sensing data using active fine-tuning network Type de document : Article/Communication Auteurs : Xin Wu, Auteur ; Wei Li, Auteur ; Danfeng Hong, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 39 - 53 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] Allemagne
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] données multisources
[Termes IGN] image aérienne
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle stéréoscopique
[Termes IGN] segmentation
[Termes IGN] segmentation sémantique
[Termes IGN] véhiculeRésumé : (auteur) Vehicle detection in remote sensing images has attracted increasing interest in recent years. However, its detection ability is limited due to lack of well-annotated samples, especially in densely crowded scenes. Furthermore, since a list of remotely sensed data sources is available, efficient exploitation of useful information from multi-source data for better vehicle detection is challenging. To solve the above issues, a multi-source active fine-tuning vehicle detection (Ms-AFt) framework is proposed, which integrates transfer learning, segmentation, and active classification into a unified framework for auto-labeling and detection. The proposed Ms-AFt employs a fine-tuning network to firstly generate a vehicle training set from an unlabeled dataset. To cope with the diversity of vehicle categories, a multi-source based segmentation branch is then designed to construct additional candidate object sets. The separation of high quality vehicles is realized by a designed attentive classifications network. Finally, all three branches are combined to achieve vehicle detection. Extensive experimental results conducted on two open ISPRS benchmark datasets, namely the Vaihingen village and Potsdam city datasets, demonstrate the superiority and effectiveness of the proposed Ms-AFt for vehicle detection. In addition, the generalization ability of Ms-AFt in dense remote sensing scenes is further verified on stereo aerial imagery of a large camping site. Numéro de notice : A2020-546 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.06.016 Date de publication en ligne : 13/07/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.06.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95772
in ISPRS Journal of photogrammetry and remote sensing > vol 167 (September 2020) . - pp 39 - 53[article]Réservation
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