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Novel fuzzy clustering algorithm with variable multi-pixel fitting spatial information for image segmentation / Hang Zhang in Pattern recognition, vol 121 (January 2022)  

Public [article]  inPattern recognition > vol 121 (January 2022) . - n° 108201 Titre : Novel fuzzy clustering algorithm with variable multi-pixel fitting spatial information for image segmentation Type de document : Article/Communication Auteurs : Hang Zhang, Auteur ; Haili Li, Auteur ; Ning Chen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 108201 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de groupement [Termes IGN] approche pixel [Termes IGN] classification floue [Termes IGN] filtre [Termes IGN] segmentation d'image [Termes IGN] voisinage (topologie) Résumé : (auteur) Spatial information is often used to enhance the robustness of traditional fuzzy c-means (FCM) clustering algorithms. Although some recently emerged improvements are remarkable, the computational complexity of these algorithms is high, which may lead to lack of practicability. To address this problem, an efficient variant named the fuzzy clustering algorithm with variable multi-pixel fitting spatial information (FCM-VMF) is presented. First, a fuzzy clustering algorithm with multi-pixel fitting spatial information (FCM-MF) is developed. Specifically, by dividing the input image into several filter windows, the spatial information of all pixels in each filter window can be obtained simultaneously by fitting the pixels in its corresponding neighbourhood window, which enormously reduces the computational complexity. However, the FCM-MF may result in the loss of edge information. Therefore, the FCM-VMF integrates a variable window strategy with FCM-MF. In this strategy, to preserve more edge information, the sizes of the filter window and generalized neighbourhood window are adaptively reduced. The experimental results show that FCM-VMF is as effective as some recent algorithms. Notably, the FCM-VMF has extremely high efficiency, which means it has a better prospect of application. Numéro de notice : A2022-100 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.patcog.2021.108201 Date de publication en ligne : 26/07/2021 En ligne : https://doi.org/10.1016/j.patcog.2021.108201 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99564 [article]

Deep learning for toponym resolution: Geocoding based on pairs of toponyms / Jacques Fize in ISPRS International journal of geo-information, vol 10 n° 12 (December 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 12 (December 2021) . - n° 818 Titre : Deep learning for toponym resolution: Geocoding based on pairs of toponyms Type de document : Article/Communication Auteurs : Jacques Fize, Auteur ; Ludovic Moncla , Auteur ; Bruno Martins, Auteur Année de publication : 2021 Article en page(s) : n° 818 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie [Termes IGN] analyse de groupement [Termes IGN] apprentissage profond [Termes IGN] échantillonnage [Termes IGN] géocodage [Termes IGN] matrice de co-occurrence [Termes IGN] site wiki [Termes IGN] toponyme [Termes IGN] zone d'intérêt Résumé : (auteur) Geocoding aims to assign unambiguous locations (i.e., geographic coordinates) to place names (i.e., toponyms) referenced within documents (e.g., within spreadsheet tables or textual paragraphs). This task comes with multiple challenges, such as dealing with referent ambiguity (multiple places with a same name) or reference database completeness. In this work, we propose a geocoding approach based on modeling pairs of toponyms, which returns latitude-longitude coordinates. One of the input toponyms will be geocoded, and the second one is used as context to reduce ambiguities. The proposed approach is based on a deep neural network that uses Long Short-Term Memory (LSTM) units to produce representations from sequences of character n-grams. To train our model, we use toponym co-occurrences collected from different contexts, namely textual (i.e., co-occurrences of toponyms in Wikipedia articles) and geographical (i.e., inclusion and proximity of places based on Geonames data). Experiments based on multiple geographical areas of interest—France, United States, Great-Britain, Nigeria, Argentina and Japan—were conducted. Results show that models trained with co-occurrence data obtained a higher geocoding accuracy, and that proximity relations in combination with co-occurrences can help to obtain a slightly higher accuracy in geographical areas with fewer places in the data sources. Numéro de notice : A2021-927 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi10120818 Date de publication en ligne : 02/12/2021 En ligne : https://doi.org/10.3390/ijgi10120818 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99293 [article]

The use of Otsu algorithm and multi-temporal airborne LiDAR data to detect building changes in urban space / Renato César Dos santos in Applied geomatics, vol 13 n° 4 (December 2021)  

Public [article]  inApplied geomatics > vol 13 n° 4 (December 2021) . - pp 499 - 513 Titre : The use of Otsu algorithm and multi-temporal airborne LiDAR data to detect building changes in urban space Type de document : Article/Communication Auteurs : Renato César Dos santos, Auteur ; Mauricio Galo, Auteur ; André C. Carrilho, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 499 - 513 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] algorithme de Otsu [Termes IGN] analyse de groupement [Termes IGN] Brésil [Termes IGN] détection de changement [Termes IGN] détection du bâti [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] données multitemporelles [Termes IGN] espace urbain [Termes IGN] modèle numérique de surface [Termes IGN] planéité [Termes IGN] semis de points [Termes IGN] seuillage Résumé : (auteur) Building change detection techniques are essential for several urban applications. In this context, multi-temporal airborne LiDAR data has been considered an effective alternative since it has some advantages over conventional photogrammetry. Despite several works in the literature, the automatic class definition with great accuracy and performance remains a challenge in change detection. The developed strategies usually explore training samples or empirical thresholds to discriminate the classes. To overcome this limitation, we proposed an automatic building change detection method based on Otsu algorithm and median planarity attribute computed from eigenvalues. The main contribution corresponds to the automatic and unsupervised identification of building changes. The experiments were conducted using airborne LiDAR data from two epochs: 2012 and 2014. From qualitative and quantitative analysis, the robustness of the proposed method in detecting building changes in urban areas was evaluated, presenting completeness and correctness around 99% and 76%, respectively. Numéro de notice : A2021-856 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.1007/s12518-021-00371-6 Date de publication en ligne : 24/04/2021 En ligne : https://doi.org/10.1007/s12518-021-00371-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99062 [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)  

Public [article]  inEuropean journal of remote sensing > vol 54 sup 2 (2021) . - pp 248 - 264 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 ondelettes Résumé : (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 [article]

Spatial structure system of land use along urban rail transit based on GIS spatial clustering / Yu Gao in European journal of remote sensing, vol 54 sup 2 (2021)  

Public [article]  inEuropean journal of remote sensing > vol 54 sup 2 (2021) . - pp 438 - 445 Titre : Spatial structure system of land use along urban rail transit based on GIS spatial clustering Type de document : Article/Communication Auteurs : Yu Gao, Auteur ; Ying Zhang, Auteur ; Haidjar Alsulaiman, Auteur Année de publication : 2021 Article en page(s) : pp 438 - 445 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] aménagement du territoire [Termes IGN] analyse de groupement [Termes IGN] Chine [Termes IGN] exploration de données géographiques [Termes IGN] modélisation spatiale [Termes IGN] optimisation (mathématiques) [Termes IGN] planification urbaine [Termes IGN] réseau ferroviaire [Termes IGN] système d'information géographique [Termes IGN] utilisation du sol [Termes IGN] zone urbaine Résumé : (auteur) During the past 30 years of reform and opening up, the level of urbanization in our country has made considerable progress, and more cities have had development conditions of the rail transit. In order to solve various problems caused by urbanization and optimize the allocation of urban resources, in this paper, the significance of spatial planning in big cities was analyzed from the perspective of land space utilization along with the rail transit. Based on GIS spatial clustering mining technology and combined with the basic characteristics of geographic information system, a GIS spatial mining search model that can solve the spatial land use was proposed. Then, by combining the clustering algorithm of some association rules, the land planning and utilization along the urban rail transit were calculated. The actual case was taken to establish the grid elements along with the rail transit, and the GIS spatial clustering algorithm was used to verify the model. The results show that GIS spatial clustering algorithm can effectively verify and calculate urban rail transit land planning programs. Numéro de notice : A2021-820 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/22797254.2020.1801356 Date de publication en ligne : 14/11/2020 En ligne : https://doi.org/10.1080/22797254.2020.1801356 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98925 [article]

Exploring fuzzy local spatial information algorithms for remote sensing image classification / Anjali Madhu in Remote sensing, vol 13 n° 20 (October-2 2021)  

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A quantitative comparison of regionalization methods / Orhun Aydun in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

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Spatially–encouraged spectral clustering: a technique for blending map typologies and regionalization / Levi John Wolf in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

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Unsupervised self-adaptive deep learning classification network based on the optic nerve microsaccade mechanism for unmanned aerial vehicle remote sensing image classification / Ming Cong in Geocarto international, vol 36 n° 18 ([04/10/2021])  

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Spatial patterns of living and dead small trees in subalpine Norway spruce forest reserves in Switzerland / Eva Bianchi in Forest ecology and management, vol 494 (15 August 2021)  

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Unsupervised band selection of hyperspectral data based on mutual information derived from weighted cluster entropy for snow classification / Divyesh Varade in Geocarto international, vol 36 n° 15 ([10/08/2021])  

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Leaf and wood separation for individual trees using the intensity and density data of terrestrial laser scanners / Kai Tan in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)  

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Towards efficient indoor/outdoor registration using planar polygons / Rahima Djahel in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)  

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Individual tree identification using a new cluster-based approach with discrete-return airborne LiDAR data / Haijian Liu in Remote sensing of environment, vol 258 (June 2021)  

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Provisioning forest and conservation science with high-resolution maps of potential distribution of major European tree species under climate change / Debojyoti Chakraborty in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

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