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Forest road extraction from orthophoto images by convolutional neural networks / Erhan Çalişkan in Geocarto international, vol 38 n° inconnu ([01/01/2023])  

Public [article]  inGeocarto international > vol 38 n° inconnu [01/01/2023] . - pp Titre : Forest road extraction from orthophoto images by convolutional neural networks Type de document : Article/Communication Auteurs : Erhan Çalişkan, Auteur ; Yusuf Sevim, Auteur Année de publication : 2023 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] chemin forestier [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] extraction automatique [Termes IGN] orthoimage [Termes IGN] segmentation sémantique Résumé : (auteur) Continuous monitoring of the forest road infrastructure and keeping track of the changes occurred are important for forestry practices, map updating, forest fire and forest transport decision support systems. In this context, the most of up to date data can be obtained by automatic forest road extraction from satellite images via machine learning (ML). Acquiring sufficient data is one of the most important factors which affect the success of ML and deep learning (DL). DL architectures yield more consistent results for complex data sets compared with ML algorithms. In the present study, three different deep learning (Resnet-18, MobileNet-V2 and Xception) architectures with semantic segmentation architecture were compared for extracting the forest road network from high-resolution orthophoto images and the results were analyzed. The architectures were evaluated through a multiclass statistical analysis based precision, recall, F1 score, intersection over union and overall accuracy (OA). The results present significant values obtained by the Resnet-18 architecture, with 99.72% of OA and 98.87% of precision and by the MobileNet-V2 architecture, with 97.76% of OA and 98.28% of precision. Also the results show that Resnet-18, MobileNet-V2 semantic segmentation architectures can be used efficiently for forest road extraction. Numéro de notice : A2022-159 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1080/10106049.2022.2060319 Date de publication en ligne : 06/04/2022 En ligne : https://doi.org/10.1080/10106049.2022.2060319 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100380 [article]

GA-Net: A geometry prior assisted neural network for road extraction / Xin Chen in International journal of applied Earth observation and geoinformation, vol 114 (November 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 114 (November 2022) . - n° 103004 Titre : GA-Net: A geometry prior assisted neural network for road extraction Type de document : Article/Communication Auteurs : Xin Chen, Auteur ; Qun Sun, Auteur ; Wenyue Guo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103004 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] attention (apprentissage automatique) [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection de contours [Termes IGN] données multiéchelles [Termes IGN] extraction automatique [Termes IGN] extraction de traits caractéristiques [Termes IGN] extraction du réseau routier [Termes IGN] jeu de données [Termes IGN] Massachusetts (Etats-Unis) Résumé : (auteur) With geospatial intelligence research developing rapidly, automatic road extraction is becoming a fundamental and challenging task. Due to the special geometric structure and spectral information of road networks, existing methods suffer from incomplete and fractured results. In this work, a novel road extraction convolutional neural network, incorporating the road boundary details and road junction information via a dual-branch multi-task structure, is proposed to learn synergistic feature representations and strengthen road connectivity. Firstly, a BiFPN-based feature aggregation module is utilised to bridge the semantic gap between low-level and high-level feature maps, allowing multi-scale spatial details to be fully fused. Secondly, the boundary auxiliary branch, using a U-shaped network with a spatial-channel attention module, captures residential information for the backbone to enhance the subtleties of road edges. Thirdly, the node inferring branch models the road junction position jointly with the road surface, aiming to strengthen the topology structure and reduce the fragmented road segments. We perform experiments on three diverse road datasets, namely the DeepGlobe dataset, Massachusetts dataset, and SpaceNet dataset. The results demonstrate that our model shows an overall performance improvement over some SOTA algorithms and the IoU indicator achieves 3.86%, 0.79%, and 1.71% improvements over Unet on the three datasets, respectively. Numéro de notice : A2022-785 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.103004 En ligne : https://doi.org/10.1016/j.jag.2022.103004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101888 [article]

Research on machine intelligent perception of urban geographic location based on high resolution remote sensing images / Jun Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 4 (April 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 4 (April 2022) . - pp 223 - 231 Titre : Research on machine intelligent perception of urban geographic location based on high resolution remote sensing images Type de document : Article/Communication Auteurs : Jun Chen, Auteur ; Cunjian Yang, Auteur ; Zengyang Yu, Auteur Année de publication : 2022 Article en page(s) : pp 223 - 231 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] base de données [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] cognition [Termes IGN] détection d'objet [Termes IGN] extraction automatique [Termes IGN] géolocalisation [Termes IGN] image à haute résolution [Termes IGN] intelligence artificielle [Termes IGN] reconnaissance automatique [Termes IGN] zone urbaine Résumé : (auteur) Machine intelligent perception (MIP) provides a novel way for human beings to recognize geographical locations automatically. MIP of geographical locations enables computers to describe locations automatically and quantitatively by extracting Earth's surface features and building relationships. The earth surface fingerprint is established here by mining the relationship between spatial objects with stable characteristics extracted from urban high-resolution remote sensing images, which realizes intelligent perception of geographical location innovatively. Mask Region-based Convolutional Neural Network is used to automatically extract the spatial objects such as playgrounds, crossroads, and bridges from the images. Then, the extracted spatial objects are encoded according to the landuse type, distance, and angle of 24 nearest objects to construct urban surface fingerprint database. The urban surface fingerprint database is used to match the geographical location of spatial objects in local images so that the matching algorithm can be used for machine recognition of the geographical location of specific objects in the target image. Taking the main cities in China as the experimental area, the success rate of location perception is 92%. We have made a useful exploration in the field of MIP of geographical location, hoping to promote the development of human cognition of geographical location. Numéro de notice : A2022-285 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00017R3 Date de publication en ligne : 04/04/2022 En ligne : https://doi.org/10.14358/PERS.21-00017R3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100319 [article]

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Automatic extraction of building geometries based on centroid clustering and contour analysis on oblique images taken by unmanned aerial vehicles / Leilei Zhang in International journal of geographical information science IJGIS, vol 36 n° 3 (March 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 3 (March 2022) . - pp 453 - 475 Titre : Automatic extraction of building geometries based on centroid clustering and contour analysis on oblique images taken by unmanned aerial vehicles Type de document : Article/Communication Auteurs : Leilei Zhang, Auteur ; Guoxin Wang, Auteur ; Weijian Sun, Auteur Année de publication : 2022 Article en page(s) : pp 453 - 475 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de groupement [Termes IGN] classification barycentrique [Termes IGN] classification non dirigée [Termes IGN] détection de contours [Termes IGN] détection du bâti [Termes IGN] extraction automatique [Termes IGN] image captée par drone [Termes IGN] image oblique [Termes IGN] modèle numérique de surface [Termes IGN] orthophotocarte [Termes IGN] précision géométrique (imagerie) Résumé : (auteur) This paper introduces a method based on centroid clustering and contour analysis to extract area and height measurements on buildings from the 3D model generated by oblique images. The method comprises three steps: (1) extract the contour plane from the fused data of the digital surface model (DSM) and digital orthophoto map (DOM); (2) identify building contour clusters based on the number of centroids contained in each category determined by mean-shift centroid clustering; (3) remove the mis-identified contours in a given building contour cluster by a contour analysis and obtain the geometric information of the building using map algebra. The proposed approach was tested against four datasets. Compared with other results, the detection has effective completeness, correctness, quality, and higher geometric accuracy. The maximum average relative error of building height and area extraction is less than 8%. The method is fast for a large-scale collection of building attributes and improves the applicability of oblique photography in GIS. Numéro de notice : A2022-205 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1937632 Date de publication en ligne : 14/06/2021 En ligne : https://doi.org/10.1080/13658816.2021.1937632 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100020 [article]

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Automatic extraction of damaged houses by earthquake based on improved YOLOv5: A case study in Yangbi / Yafei Jing in Remote sensing, vol 14 n° 2 (January-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 2 (January-2 2022) . - n° 382 Titre : Automatic extraction of damaged houses by earthquake based on improved YOLOv5: A case study in Yangbi Type de document : Article/Communication Auteurs : Yafei Jing, Auteur ; Yuhuan Ren, Auteur ; Yalan Liu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 382 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] détection d'objet [Termes IGN] détection de cible [Termes IGN] détection du bâti [Termes IGN] dommage matériel [Termes IGN] extraction automatique [Termes IGN] image captée par drone [Termes IGN] orthoimage [Termes IGN] séisme [Termes IGN] Yunnan (Chine) Résumé : (auteur) Efficiently and automatically acquiring information on earthquake damage through remote sensing has posed great challenges because the classical methods of detecting houses damaged by destructive earthquakes are often both time consuming and low in accuracy. A series of deep-learning-based techniques have been developed and recent studies have demonstrated their high intelligence for automatic target extraction for natural and remote sensing images. For the detection of small artificial targets, current studies show that You Only Look Once (YOLO) has a good performance in aerial and Unmanned Aerial Vehicle (UAV) images. However, less work has been conducted on the extraction of damaged houses. In this study, we propose a YOLOv5s-ViT-BiFPN-based neural network for the detection of rural houses. Specifically, to enhance the feature information of damaged houses from the global information of the feature map, we introduce the Vision Transformer into the feature extraction network. Furthermore, regarding the scale differences for damaged houses in UAV images due to the changes in flying height, we apply the Bi-Directional Feature Pyramid Network (BiFPN) for multi-scale feature fusion to aggregate features with different resolutions and test the model. We took the 2021 Yangbi earthquake with a surface wave magnitude (Ms) of 6.4 in Yunan, China, as an example; the results show that the proposed model presents a better performance, with the average precision (AP) being increased by 9.31% and 1.23% compared to YOLOv3 and YOLOv5s, respectively, and a detection speed of 80 FPS, which is 2.96 times faster than YOLOv3. In addition, the transferability test for five other areas showed that the average accuracy was 91.23% and the total processing time was 4 min, while 100 min were needed for professional visual interpreters. The experimental results demonstrate that the YOLOv5s-ViT-BiFPN model can automatically detect damaged rural houses due to destructive earthquakes in UAV images with a good performance in terms of accuracy and timeliness, as well as being robust and transferable. Numéro de notice : A2022-104 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14020382 Date de publication en ligne : 14/01/2022 En ligne : https://doi.org/10.3390/rs14020382 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99577 [article]

Automated construction of a French Entity Linking dataset to geolocate social network posts in the context of natural disasters / Gaëtan Caillaut (2022)  

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Point clouds for use in Building Information Models (BIM) / Robert Klinc in Geodetski vestnik, vol 65 n° 4 (December 2021 - February 2022)  

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A deep multi-modal learning method and a new RGB-depth data set for building roof extraction / Mehdi Khoshboresh Masouleh in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)  

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Extraction of impervious surface using Sentinel-1A time-series coherence images with the aid of a Sentinel-2A image / Wenfu Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 3 (March 2021)  

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Geometric approximation of structured scenes from images / Muxingzi Li (2021)  

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A hybrid deep learning–based model for automatic car extraction from high-resolution airborne imagery / Mehdi Khoshboresh Masouleh in Applied geomatics, vol 12 n° 2 (June 2020)  

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Object-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])  

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Polarimetric SAR calibration and residual error estimation when corner reflectors are unavailable / Lei Shi in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)  

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Integration of remote sensing and GIS to extract plantation rows from a drone-based image point cloud digital surface model / Nadeem Fareed in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)  

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Sea-land segmentation using deep learning techniques for Landsat-8 OLI imagery / Ting Yang in Marine geodesy, Vol 43 n° 2 (March 2020)  

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Automated extraction of lane markings from mobile LiDAR point clouds based on fuzzy inference / Heidar Rastiveis in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

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Multi-scale point cloud analysis / Thibault Lejemble (2020)  

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An indoor navigation model and its network extraction / Filippo Mortari in Applied geomatics, Vol 11 n° 4 (December 2019)  

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Extracting urban landmarks from geographical datasets using a random forests classifier / Yue Lin in International journal of geographical information science IJGIS, vol 33 n° 12 (December 2019)  

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Mapping urban fingerprints of odonyms automatically extracted from French novels / Ludovic Moncla in International journal of geographical information science IJGIS, vol 33 n° 12 (December 2019)  

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Accurate detection of built-up areas from high-resolution remote sensing imagery using a fully convolutional network / Yihua Tan in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 10 (October 2019)  

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Automatic extraction of accurate 3D tie points for trajectory adjustment of mobile laser scanners using aerial imagery / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

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Building detection and regularisation using DSM and imagery information / Yousif A. Mousa in Photogrammetric record, vol 34 n° 165 (March 2019)  

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Land cover classification in combined elevation and optical images supported by OSM data, mixed-level features, and non-local optimization algorithms / Dimitri Bulatov in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 3 (March 2019)  

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Webscraping, bigdata et analyse spatiale de données immobilières : réponse à un projet ESPON au sein de l'UMS RIATE / Marc Lieury (2019) 

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Fictive motion extraction and classification / Ekaterina Egorova in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)  

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Novel fusion approach on automatic object extraction from spatial data: case study Worldview-2 and TOPO5000 / Umut Gunes Sefercik in Geocarto international, vol 33 n° 10 (October 2018)  

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Pedestrian network information extraction based on VGI / Xuejing Xie in Geomatica [en ligne], vol 72 n° 3 (September 2018)  

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A deep learning approach to DTM extraction from imagery using rule-based training labels / Caroline M. Gevaert in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

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Désambiguïsation des entités spatiales par apprentissage actif / Amal Chihaoui in Revue internationale de géomatique, vol 28 n° 2 (avril - juin 2018)  

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Generating vague neighbourhoods through data mining of passive web data / Paul Brindley in International journal of geographical information science IJGIS, vol 32 n° 3-4 (March - April 2018)  

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Multisource remote sensing data classification based on convolutional neural network / Xiaodong Xu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)  

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Automated delineation of wildfire areas using Sentinel-2 satellite imagery / Mira Weirather in GI Forum, vol 2018 n° 1 ([01/01/2018])  

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Fusion tardive d’images SPOT-6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl (2018)    

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Géolocalisation précise basée image : une approche de type “seconde itération du processus photogrammétrique” / Truong Giang Nguyen (2018) 

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Comparison of Landsat-8, ASTER and Sentinel 1 satellite remote sensing data in automatic lineaments extraction: A case study of Sidi Flah-Bouskour inlier, Moroccan Anti Atlas / Zakaria Adiri in Advances in space research, vol 60 n° 11 (1 December 2017)  

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Towards a multi-scale approach for an Earth observation-based assessment of natural resource exploitation in conflict regions / Elisabeth Schoepfer in Geocarto international, vol 32 n° 10 (October 2017)  

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A graph-based approach to detect spatiotemporal dynamics in satellite image time series / Fabio Guttler in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)  

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Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks / Rasha Alshehhi in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)  

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Analytical and numerical investigations on the accuracy and robustness of geometric features extracted from 3D point cloud data / André Dittrich in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)  

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Industrialisation des processus d'extraction d'objets à partir de données photogrammétriques par drones / Jérémie Brossard in XYZ, n° 150 (mars - mai 2017) 

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Object-based water body extraction model using Sentinel-2 satellite imagery / Gordana Kaplan in European journal of remote sensing, vol 50 n° 1 (2017)  

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Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features / Wang Min in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)  

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Télédétection pour l'observation des surfaces continentales, Volume 1. Observation des surfaces continentales par télédétection optique / Nicolas Baghdadi (2017)

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Extracting building patterns with multilevel graph partition and building grouping / Shihong Du in ISPRS Journal of photogrammetry and remote sensing, vol 122 (December 2016)  

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Hyperspectral feature extraction using total variation component analysis / Behnood Rasti in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

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Automatic extraction of road networks from GPS traces / Jia Qiu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 8 (August 2016)  

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Supervised classification of very high resolution optical images using wavelet-based textural features / Olivier Regniers in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)  

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Kernel-based domain-invariant feature selection in hyperspectral images for transfer learning / Claudio Persello in IEEE Transactions on geoscience and remote sensing, vol 54 n° 5 (May 2016)  

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Active-metric learning for classification of remotely sensed hyperspectral images / Edoardo Pasolli in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)  

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Fusion of hyperspectral images and digital surface models for urban object extraction / Janja Avbelj (2016) 

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Mise en place de procédures automatiques en vue d’accélérer la production des plans topographiques au sein de l’entreprise Techni Drone / Kévin Javerliat (2016)

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Road vectorisation from high-resolution imagery based on dynamic clustering using particle swarm optimisation / Fateme Ameri in Photogrammetric record, vol 30 n° 152 (December 2015 - February 2016)  

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Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching / Amin Sedaghat in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

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Measuring the effectiveness of various features for thematic information extraction from very high resolution remote sensing imagery / X. Chen in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)  

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Semisupervised transfer component analysis for domain adaptation in remote sensing image classification / Giona Matasci in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)  

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Vectorisation automatique des forêts dans les minutes de la carte d’état-major du 19e siècle / Pierre-Alexis Herrault in Revue internationale de géomatique, vol 25 n° 1 (mars - mai 2015)  

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vol 25 n° 1 - mars - mai 2015 - Traitement de l'information et prospective (Bulletin de Revue internationale de géomatique) / Françoise Gourmelon  

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In-flight photogrammetric camera calibration and validation via complementary lidar / A.S. Gneeniss in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)  

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Radiometric and geometric evaluation of GeoEye-1, WorldView-2 and Pléiades-1A stereo images for 3D information extraction / Daniela Poli in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)  

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Automatic reconstruction of itineraries from descriptive texts / Ludovic Moncla (2015)  

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Extraction de fragments forestiers et caractérisation de leurs évolutions spatio-temporelles pour évaluer l'effet de l'histoire sur la biodiversité : une approche multi-sources / Pierre-Alexis Herrault (2015)  

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Hierarchical extraction of urban objects from mobile laser scanning data / Bisheng Yang in ISPRS Journal of photogrammetry and remote sensing, vol 99 (January 2015)  

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Automatic building extraction using a fuzzy active contour model / Mostafa Kabolizade in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)  

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Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery / Mustafa Neamah Jebur in Geocarto international, vol 29 n° 7 - 8 (November - December 2014)  

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Apport de l'imagerie satellitaire à haute et très haute résolution pour la recherche d'indices de drainage superficiel : Application aux aires d'alimentation de captage (AAC) d'eau potable / Sébastien Rucquoi in Revue Française de Photogrammétrie et de Télédétection, n° 208 (Octobre 2014)  

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Detecting cars in UAV images with a catalog-based approach / Thomas Moranduzzo in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)  

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Ground and building extraction from LiDAR data based on differential morphological profiles and locally fitted surfaces / Domen Mongus in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)  

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Comparaison de méthodes d'extraction automatique à partir d'images multispectrales / Valerio Baiocchi in Géomatique expert, n° 96 (01/01/2014)

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Using mobile laser scanning data for automated extraction of road markings / Haiyan Guan in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)  

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An automated algorithm for extracting road edges from terrestrial mobile LiDAR data / Pankaj Kumar in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)  

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Single tree biomass modelling using airborne laser scanning / Ville Kankare in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)  

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Pedestrian network extraction from fused aerial imagery (orthoimages) and laser imagery (lidar) / Piyawan Kasemsuppakorn in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 4 (April 2013)  

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Classification grande échelle de surfaces d’eau par lidar aéroporté / Nicolas David (2013) 

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Comparaison et évaluation de méthodes d'extraction automatique d'objets sur des images optique et radar / Charlotte Benedetto (2013) 

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Etude de l’extraction automatique de coupe à partir de nuages de points / Selma Bidino (2013) 

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Manual of photogrammetry, sixth edition / J. Chris Mcglone (2013)

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Automatic co-registration of satellite time series / M. Gianinetto in Photogrammetric record, vol 27 n° 140 (December 2012 - February 2013)  

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A vector sift detector for interest point detection in hyperspectral imagery / L. Dorado-Munoz in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)  

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An automated system for image-to-vector georeferencing / Y. Li in Cartography and Geographic Information Science, vol 39 n° 4 (October 2012)  

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Assessment of a photogrammetric approach for urban DSM extraction from tri-stereoscopic satellite imagery / F. Tack in Photogrammetric record, vol 27 n° 139 (September - November 2012)  

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The influence of subpixel measurement on digital camera calibration / Mauricio Galo in Revue Française de Photogrammétrie et de Télédétection, n° 198 - 199 (Septembre 2012)  

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Automatic extraction of road markings from mobile Lidar point clouds / B. Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 4 (April 2012)  

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Automatic tie-point extraction / Z. Shragai in GIM international, vol 26 n° 4 (April 2012)

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Extraction of building roof contours from LiDAR data using a Markov-random-field-based approach / E. Dos Santos Galvanin in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)  

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Advances in spatial data handling and GIS / Wenzhong Shi (2012)  

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Automated damage indication for rapid geospatial reporting / D. Tiede in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 9 (September 2011)  

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Extraction des courbes de niveau cartographiques à partir d'un modèle numérique de terrain (MNT) / Kusay Jaara in Cartes & Géomatique, n° 209 (septembre 2011)    

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A multispectral and multiscale morphological index for automatic building extraction from multispectral GeoEye-1 imagery / X. Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 7 (July 2011)  

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Approche non supervisée par processus ponctuels marqués pour l'extraction d'objets à partir d'images aériennes et satellitaires / S. Ben Hadj in Revue Française de Photogrammétrie et de Télédétection, n° 194 (Mai 2011)

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A new solution to the relative orientation problem using only 3 points and the vertical direction / Mahzad Kalantari in Journal of Mathematical Imaging and Vision, vol 39 n° 3 (March 2011)  

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Impervious surface area extraction from IKONOS imagery using an object-based fuzzy method / X. Hu in Geocarto international, vol 26 n° 1 (February 2011)  

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Détection de changement 2D à partir d’imagerie satellitaire : Application à la mise à jour des bases de données géographiques / Nicolas Champion (2011)  

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Extraction automatique des discontinuités planes à partir d'une scannérisation laser 3D en milieu rocheux / Souhail Hajri in Revue Française de Photogrammétrie et de Télédétection, n° 192 (Septembre 2010)

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Using aerial imagery and GIS in automated building footprint extraction and shape recognition for earthquake risk assessment of urban inventories / L. Sahar in IEEE Transactions on geoscience and remote sensing, vol 48 n° 9 (September 2010)  

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Digital urban morphometrics : Automatic extraction and assessment of morphological properties of buildings / Claudio Carneiro in Transactions in GIS, vol 14 n° 4 (August 2010)  

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3D road marking reconstruction from street-level calibrated stereo pairs / Bahman Soheilian in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 4 (July - August 2010)  

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Exploiting geographic references of documents in a geographical information retrieval system using an ontology-based index / N. Brisaboa in Geoinformatica, vol 14 n° 3 (July 2010)  

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Ten years of technology advancement in remote sensing and the research in the CRC-AGIP in GCE / Y. Zhang in Geomatica, vol 64 n° 2 (June 2010)

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Delineation and geometric modeling of road networks / C. Poullis in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 2 (March - April 2010)  

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