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A semi-automatic method for extraction of urban features by integrating aerial images and LIDAR data and comparing its performance in areas with different feature structures (case study: comparison of the method performance in Isfahan and Toronto) / Masoud Azad in Applied geomatics, vol 14 n° 4 (December 2022)  

Public [article]  inApplied geomatics > vol 14 n° 4 (December 2022) . - pp 589 - 607 Titre : A semi-automatic method for extraction of urban features by integrating aerial images and LIDAR data and comparing its performance in areas with different feature structures (case study: comparison of the method performance in Isfahan and Toronto) Type de document : Article/Communication Auteurs : Masoud Azad, Auteur ; Farshid Farnood Ahmadi, Auteur Année de publication : 2022 Article en page(s) : pp 589 - 607 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] détection d'objet [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction de la végétation [Termes IGN] extraction de traits caractéristiques [Termes IGN] extraction semi-automatique [Termes IGN] image aérienne [Termes IGN] Iran [Termes IGN] modèle numérique de terrain [Termes IGN] segmentation d'image [Termes IGN] seuillage [Termes IGN] Toronto [Termes IGN] zone urbaine Résumé : (auteur) In this article, a new feature detection approach based on integration of LiDAR data and visible images in the form of a semi-automatic method has been proposed. In this approach, a two-step method for feature detection was developed using object-based analysis in order to increase the level of automation and level of accuracy in the detection process. The first step is providing a method for integration of two data sources for detection process by maintaining independency between image data and LiDAR altimetric data. In this step, the feature detection process is started based on image data and for detecting areas that detection properly is not done, LiDAR altimetric data is used. In the second step, a new method for detection of vegetation is implemented. Of the characteristics of this method is that there is no need to use the infrared band in the image data and also there is no need for LiDAR intensity data. The implemented method in the recent step is based on the new indices developed for detection of vegetation using three visible bands (red, green, and blue). The results of applying the method on two sample data sets show that the proposed approach and developed indices have the lowest dependency on the type and region of imaging and about each input image data includes visible bands (red, green, and blue) along with LiDAR data (that both data have a high spatial resolution), feature detection process is done with acceptable accuracy. Only thresholds depend on image data and change about different images. The changes are very small. Therefore, using the mean of these thresholds, despite may not be optimal for all image data, but generally is useful and for different images is efficient. In the case of many accessible images from Iran, the thresholds determined optimally by the trial-and-error method, the changes were very small. About the image data of Toronto and Iran which great changes were expected in the thresholds, the optimal thresholds showed very small changes. The results of this research demonstrated that the proposed method can successfully detect urban features (include vegetation, road, and building) with different shapes. Evaluation process showed that the overall accuracy, kappa coefficient, producer’s accuracy, and user’s accuracy of the proposed method about vegetation are 97%, 92%, 96%, and 94%, respectively. Also, the producer’s accuracy, user’s accuracy, and kappa coefficient about the building class are 94%, 95%, and 91%, respectively. About the road class these parameters are 95%, 89%, and 91%. Numéro de notice : A2022-892 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-022-00455-x Date de publication en ligne : 10/08/2022 En ligne : https://doi.org/10.1007/s12518-022-00455-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102239 [article]

Semi-automatic extraction of rural roads under the constraint of combined geometric and texture features / Hai Tan in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 11 (November 2021) . - pp 754 Titre : Semi-automatic extraction of rural roads under the constraint of combined geometric and texture features Type de document : Article/Communication Auteurs : Hai Tan, Auteur ; Zimo Shen, Auteur ; Jiguang Dai, Auteur Année de publication : 2021 Article en page(s) : pp 754 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] chemin rural [Termes IGN] Chine [Termes IGN] coefficient de corrélation [Termes IGN] contrainte géométrique [Termes IGN] corrélation croisée normalisée [Termes IGN] courbure [Termes IGN] extraction de traits caractéristiques [Termes IGN] extraction semi-automatique [Termes IGN] image à haute résolution [Termes IGN] modèle de simulation [Termes IGN] niveau de gris (image) [Termes IGN] route [Termes IGN] texture d'image Résumé : (auteur) The extraction of road information from high-resolution remotely-sensed images has important application value in many fields. Rural roads have the characteristics of relatively narrow widths and diversified pavement materials; these characteristics can easily lead to problems involving the similarity of the road texture with the texture of surrounding objects and make it difficult to improve the automation of traditional high-precision road extraction methods. Based on this background, a semi-automatic rural road extraction method constrained by a combination of geometric and texture features is proposed in this paper. First, an adaptive road width extraction model is proposed to improve the accuracy of the initial road centre point. Then, aiming at the continuous change of curvature of rural roads, a tracking direction prediction model is proposed. Finally, a matching model under geometric texture constraints is proposed, which solves the problem of similarity between road and neighbourhood texture to a certain extent. The experimental results show that by selecting different types of experimental scenes or remotely sensed image data, compared with other methods, the proposed method can not only guarantee the road extraction accuracy but also improve the degree of automation to a certain extent. Numéro de notice : A2021-850 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10110754 Date de publication en ligne : 09/11/2021 En ligne : https://doi.org/10.3390/ijgi10110754 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99009 [article]

Semi-automatic building extraction from WorldView-2 imagery using taguchi optimization / Hasan Tonbul in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 9 (September 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 9 (September 2020) . - pp 547-555 Titre : Semi-automatic building extraction from WorldView-2 imagery using taguchi optimization Type de document : Article/Communication Auteurs : Hasan Tonbul, Auteur ; Taskin Kavzoglu, Auteur Année de publication : 2020 Article en page(s) : pp 547-555 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de variance [Termes IGN] carte d'occupation du sol [Termes IGN] détection du bâti [Termes IGN] extraction semi-automatique [Termes IGN] image Worldview [Termes IGN] optimisation (mathématiques) [Termes IGN] rapport signal sur bruit [Termes IGN] régression linéaire [Termes IGN] segmentation multi-échelle [Termes IGN] séparateur à vaste marge Résumé : (Auteur) Due to the complex spectral and spatial structures of remotely sensed images, the delineation of land use/land cover classes using conventional approaches is a challenging task. This article tackles the problem of seeking optimal parameters of multi-resolution segmentation for a classification task using WorldView-2 imagery. Taguchi optimization was applied to search optimal parameters using the plateau objective function (POF) and quality rate (Qr) as fitness criteria. Analysis of variance was also used to estimate the contributions of the parameters for POF and Qr, separately. The scale parameter was the most effective one, with contribution levels of 87.45% and 56.87% for POF and Qr, respectively. Linear regression and support-vector regression methods were used to predict the results of the experiment. Test results revealed that Taguchi optimization was more effective than linear regression and support-vector regression for predicting POF and Qr values. Numéro de notice : A2020-490 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.9.547 Date de publication en ligne : 01/09/2020 En ligne : https://doi.org/10.14358/PERS.86.9.547 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95931 [article]

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Counting of grapevine berries in images via semantic segmentation using convolutional neural networks / Laura Zabawa in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 73 - 83 Titre : Counting of grapevine berries in images via semantic segmentation using convolutional neural networks Type de document : Article/Communication Auteurs : Laura Zabawa, Auteur ; Anna Kicherer, Auteur ; Lasse Klingbeil, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 73 - 83 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] comptage [Termes IGN] échantillon [Termes IGN] extraction de traits caractéristiques [Termes IGN] extraction semi-automatique [Termes IGN] régression [Termes IGN] rendement agricole [Termes IGN] segmentation sémantique [Termes IGN] traitement d'image [Termes IGN] viticulture Résumé : (auteur) The extraction of phenotypic traits is often very time and labour intensive. Especially the investigation in viticulture is restricted to an on-site analysis due to the perennial nature of grapevine. Traditionally skilled experts examine small samples and extrapolate the results to a whole plot. Thereby different grapevine varieties and training systems, e.g. vertical shoot positioning (VSP) and semi minimal pruned hedges (SMPH) pose different challenges. In this paper we present an objective framework based on automatic image analysis which works on two different training systems. The images are collected semi automatic by a camera system which is installed in a modified grape harvester. The system produces overlapping images from the sides of the plants. Our framework uses a convolutional neural network to detect single berries in images by performing a semantic segmentation. Each berry is then counted with a connected component algorithm. We compare our results with the Mask-RCNN, a state-of-the-art network for instance segmentation and with a regression approach for counting. The experiments presented in this paper show that we are able to detect green berries in images despite of different training systems. We achieve an accuracy for the berry detection of 94.0% in the VSP and 85.6% in the SMPH. Numéro de notice : A2020-252 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.002 Date de publication en ligne : 22/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.002 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94996 [article]

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Automatic delineation of built-up area at urban block level from topographic maps / Sebastian Muhs in Computers, Environment and Urban Systems, vol 58 (July 2016)  

Public [article]  inComputers, Environment and Urban Systems > vol 58 (July 2016) . - pp 71 - 84 Titre : Automatic delineation of built-up area at urban block level from topographic maps Type de document : Article/Communication Auteurs : Sebastian Muhs, Auteur ; Hendrik Herold, Auteur ; Gotthard Meinel, Auteur ; Dirk Burghardt, Auteur ; Odette Kretschmer, Auteur Année de publication : 2016 Article en page(s) : pp 71 - 84 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse d'image numérique [Termes IGN] base de données historiques [Termes IGN] carte topographique [Termes IGN] détection du bâti [Termes IGN] extraction semi-automatique [Termes IGN] îlot urbain [Termes IGN] vision par ordinateur [Termes IGN] zone urbaine Résumé : (auteur) To comprehensively study and better understand urban dynamic processes — such as densification, growth and sprawl, or shrinkage — spatio-temporal databases that allow to track changes of geographic objects like buildings and urban blocks are essential. While comprehensive databases exist for contemporary data, they usually lack a historic dimension. The manual constitution of historic geographic data, be it based on historic maps or aerial images, is a time consuming and laborious process, however. Therefore, we present an approach to semi-automatically extract this data from binary topographic maps with regard to built-up areas at urban block level. The suitability of topographic maps for historic urban analysis has been proven in previous research. To overcome the challenges that are inherent in scanned topographic maps in regard to digital image interpretation we designed a modular process. Among others, these challenges include fused and (multi-)fragmented map objects caused by the overlap of competing content layers in one single binary map. After a preliminary separation of individual map object layers from the map content, the process follows a two-stage top-down approach. At first, the map is organized into street blocks, which after that are re-delineated in regard to built-up area. In doing so, we achieve correctness values ranging from 0.97 to 0.93 for three study sites in Germany. With an increasing number of projects that provide historic topographic maps as georeferenced digital data, our process represents a promising approach to efficiently prepare these historic data for integration into a spatio-temporal database with minimal user intervention. Numéro de notice : A2016-404 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2016.04.001 En ligne : http://dx.doi.org/10.1016/j.compenvurbsys.2016.04.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81221 [article]

An interactive tool for semi-automatic feature extraction of hyperspectral data / Zoltan Kovacs in Open geosciences, vol 8 n° 1 (January - July 2016)  

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Semi-automated building footprint extraction from orthophotos / Rheannon Brooks in Geomatica [en ligne], vol 69 n° 2 (June 2015)  

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Semiautomated extraction of street light poles from mobile LiDAR point-clouds / Yongtao Yu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)  

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SENTERRITOIRE pour la détection d’opinions liées à l’aménagement d’un territoire / Eric Kergosien in Revue internationale de géomatique, vol 25 n° 1 (mars - mai 2015)  

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Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds / Bishen Yang in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)  

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Extraction du trait instantané de côte à partir d'images optiques satellites haute-résolution et radar / Valerio Baiocchi in Géomatique expert, n° 89 (01/11/2012)

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Photogrammetric control points from airborne laser scanner data / Q. Dalmolin in Revue Française de Photogrammétrie et de Télédétection, n° 198 - 199 (Septembre 2012)  

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Construction of digital 3D highway model using stereo IKONOS satellite imagery / Ahmed Shaker in Geocarto international, vol 26 n° 1 (February 2011)  

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Rapid mapping of high resolution SAR scenes / F. Dell'acqua in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 5 (September - October 2009)  

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Semi-automatic extraction of 3D lines using a scalable edge model and least-squares template matching / X. Hu in Geomatica, vol 62 n° 3 (September 2008)

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