Centre de documentation
scientifique

Urban construction waste with VHR remote sensing using multi-feature analysis and a hierarchical segmentation method / Qiang Chen in Remote sensing, vol 13 n° 1 (January-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 1 (January-1 2021) . - n° 158 Titre : Urban construction waste with VHR remote sensing using multi-feature analysis and a hierarchical segmentation method Type de document : Article/Communication Auteurs : Qiang Chen, Auteur ; Qianhao Cheng, Auteur ; Jinfei Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 158 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse d'image orientée objet [Termes IGN] analyse multicritère [Termes IGN] analyse spectrale [Termes IGN] construction [Termes IGN] déchet [Termes IGN] extraction de traits caractéristiques [Termes IGN] gestion urbaine [Termes IGN] image à très haute résolution [Termes IGN] morphologie [Termes IGN] Pékin (Chine) [Termes IGN] segmentation hiérarchique [Termes IGN] urbanisation Résumé : (auteur) With rapid urbanization, the disposal and management of urban construction waste have become the main concerns of urban management. The distribution of urban construction waste is characterized by its wide range, irregularity, and ease of confusion with the surrounding ground objects, such as bare soil, buildings, and vegetation. Therefore, it is difficult to extract and identify information related to urban construction waste by using the traditional single spectral feature analysis method due to the problem of spectral confusion between construction waste and the surrounding ground objects, especially in the context of very-high-resolution (VHR) remote sensing images. Considering the multi-feature analysis method for VHR remote sensing images, we propose an optimal method that combines morphological indexing and hierarchical segmentation to extract the information on urban construction waste in VHR images. By comparing the differences between construction waste and the surrounding ground objects in terms of the spectrum, geometry, texture, and other features, we selected an optimal feature subset to improve the separability of the construction waste and other objects; then, we established a classification model of knowledge rules to achieve the rapid and accurate extraction of construction waste information. We also chose two experimental areas of Beijing to validate our algorithm. By using construction waste separability quality evaluation indexes, the identification accuracy of construction waste in the two study areas was determined to be 96.6% and 96.2%, the separability indexes of the construction waste and buildings reached 1.000, and the separability indexes of the construction waste and vegetation reached 1.000 and 0.818. The experimental results show that our method can accurately identify the exposed construction waste and construction waste covered with a dust screen, and it can effectively solve the problem of spectral confusion between the construction waste and the bare soil, buildings, and vegetation. Numéro de notice : A2021-073 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13010158 Date de publication en ligne : 05/01/2021 En ligne : https://doi.org/10.3390/rs13010158 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96809 [article]

Adjusting the regular network of squares resolution to the digital terrain model surface shape / Dariusz Gościewski in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 12 (December 2020) . - n° 761 Titre : Adjusting the regular network of squares resolution to the digital terrain model surface shape Type de document : Article/Communication Auteurs : Dariusz Gościewski, Auteur ; Małgorzata Gerus-Gościewska, Auteur Année de publication : 2020 Article en page(s) : n° 761 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] erreur moyenne quadratique [Termes IGN] interpolation [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique de terrain [Termes IGN] morphologie [Termes IGN] semis de points [Termes IGN] Triangulated Irregular Network Résumé : (auteur) A regular network of squares is formed by points uniformly distributed (mostly in the square corners) over the surface that is represented by the network. Each point (node) of the network has specified coordinates (X and Y) with a fixed constant distance between them. The third coordinate in a node (H) is determined by the application of interpolation based on the points distributed (usually dispersed as a point cloud e.g., from LiDAR) over the surface of the area surrounding the node. The regular network of squares formed in this manner allows the representation of a digital terrain model (DTM) to be performed in spatial information systems (SIP, GIS). The main problem that arises during the construction of such a network is the proper determination of its resolution (the base distance between the coordinates X and Y) depending on the topography. This article presents a method of the regular network of squares resolution determination depending on the morphological shape of the terrain surface. Following the application of the procedures being described, a differently shaped terrain is assigned various network densities. This enables the minimisation of inaccuracies of the surface model being formed. Consequently, a regular network of squares is formed with different base square sizes, which is adjusted with its resolution to the morphology of the surface it describes. Such operations allow the terrain model accuracy to be maintained over the entire area while reducing the number of points stored in the DTM database to the minimum. Numéro de notice : A2020-807 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9120761 Date de publication en ligne : 20/12/2020 En ligne : https://doi.org/10.3390/ijgi9120761 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96952 [article]

Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata / Yaqian Zhai in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 7 (July 2020) . - pp 1475 - 1499 Titre : Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata Type de document : Article/Communication Auteurs : Yaqian Zhai, Auteur ; Yao Yao, Auteur ; Qingfeng Guan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1475 - 1499 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] aide à la décision [Termes IGN] automate cellulaire [Termes IGN] changement d'occupation du sol [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] extraction de traits caractéristiques [Termes IGN] milieu urbain [Termes IGN] morphologie [Termes IGN] parcelle cadastrale [Termes IGN] petite échelle [Termes IGN] planification urbaine [Termes IGN] précision de la classification [Termes IGN] Shenzhen [Termes IGN] voisinage (relation topologique) Résumé : (auteur) Vector-based cellular automata (VCA) models have been applied in land use change simulations at fine scales. However, the neighborhood effects of the driving factors are rarely considered in the exploration of the transition suitability of cells, leading to lower simulation accuracy. This study proposes a convolutional neural network (CNN)-VCA model that adopts the CNN to extract the high-level features of the driving factors within a neighborhood of an irregularly shaped cell and discover the relationships between multiple land use changes and driving factors at the neighborhood level. The proposed model was applied to simulate urban land use changes in Shenzhen, China. Compared with several VCA models using other machine learning methods, the proposed CNN-VCA model obtained the highest simulation accuracy (figure-of-merit = 0.361). The results indicated that the CNN-VCA model can effectively uncover the neighborhood effects of multiple driving factors on the developmental potential of land parcels and obtain more details on the morphological characteristics of land parcels. Moreover, the land use patterns of 2020 and 2025 under an ecological control strategy were simulated to provide decision support for urban planning. Numéro de notice : A2020-307 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1711915 Date de publication en ligne : 14/01/2020 En ligne : https://doi.org/10.1080/13658816.2020.1711915 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95149 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2020071	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Evaluation of a spatially adaptive approach for land surface classification from digital elevation models / Maria Dekavalla in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 31 n° 9-10 (September - October 2017) . - pp 1978 - 2000 Titre : Evaluation of a spatially adaptive approach for land surface classification from digital elevation models Type de document : Article/Communication Auteurs : Maria Dekavalla, Auteur ; Demetre Argialas, Auteur Année de publication : 2017 Article en page(s) : pp 1978 - 2000 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] classification [Termes IGN] géomorphométrie [Termes IGN] information sémantique [Termes IGN] modèle numérique de surface [Termes IGN] modélisation spatiale [Termes IGN] morphologie [Termes IGN] photogrammétrie spatiale [Termes IGN] relief Résumé : (Auteur) Classification of land surface to landforms is fundamental to interpretation of various environmental processes. The heterogeneous landform descriptions and classification approaches, in combination with the scale dependence of digital elevation models (DEMs) and their products, defy the development of an interoperable and transferable automated landform classification approach. A theoretical framework has proposed that land surface should be regionalised to morphologic meaningful objects, delimited by discontinuities (i.e. slope breaks and inflections) and subsequently classified with morphometric and contextual criteria. However, an automated methodology meeting these conditions is still lacking. This study is an attempt to automate this framework through the investigation of a modified version of a spatially adaptive pattern-based approach and its potential to produce morphologic meaningful objects of various shapes and sizes, present at the given DEM resolution. These objects were classified to 15 landform element classes based on semantic descriptions, including criteria of morphometry, relative topographic position and topological relations. Results were visually analysed by draping them over DEMs and contours and quantitatively assessed with fuzzy classification tools. The modified pattern-based approach was proven to be efficient for delineation of morphologic meaningful objects in DEMs. The classification approach was transferable to various landscapes and DEM resolutions, given that it uses spatially flexible fuzzy criteria. Numéro de notice : A2017-507 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1344984 En ligne : http://dx.doi.org/10.1080/13658816.2017.1344984 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86453 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2017051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Toward optimum fusion of thermal hyperspectral and visible images in classification of urban area / Farhad Samadzadegan in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 4 (April 2017)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 4 (April 2017) . - pp 269 - 280 Titre : Toward optimum fusion of thermal hyperspectral and visible images in classification of urban area Type de document : Article/Communication Auteurs : Farhad Samadzadegan, Auteur ; Hadiseh Hasani, Auteur ; Peter Reinartz, Auteur Année de publication : 2017 Article en page(s) : pp 269 - 280 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] bande visible [Termes IGN] bati [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] fusion d'images [Termes IGN] géostatistique [Termes IGN] image hyperspectrale [Termes IGN] image thermique [Termes IGN] indice de végétation [Termes IGN] morphologie [Termes IGN] optimisation (mathématiques) [Termes IGN] réseau routier [Termes IGN] zone urbaine Résumé : (Auteur) Recently, classification of urban area based on multi-sensor fusion has been widely investigated. In this paper, the potential of using visible (VIS) and thermal infrared (TIR) hyperspectral images fusion for classification of urban area is evaluated. For this purpose, comprehensive spatial-spectral feature space is generated which includes vegetation index, differential morphological profile (DMP), attribute profile (AP), texture, geostatistical features, structural feature set (SFS) and local statistical descriptors from both datasets in addition to original datasets. Although Support Vector Machine (SVM) is an appropriate tool in the classification of high dimensional feature space, its performance is significantly affected by its parameters and feature space. Cuckoo search (CS) optimization algorithm with mixed binary-continuous coding is proposed for feature selection and SVM parameter determination simultaneously. Moreover, the significance of each selected feature category in the classification of a specific object is verified. Accuracy assessment on two subsets shows that stacking of VIS and TIR bands can improve the classification performance to 87 percent and 82 percent for two subsets, compare to VIS image (72 percent and 80 percent) and TIR image (50 percent and 56 percent). However, the optimum results obtained based on the proposed method which gains 94 percent and 92 percent. Furthermore, results show that using TIR beside VIS image improves classification accuracy of roads and buildings in urban area. Numéro de notice : A2017-111 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.83.4.269 En ligne : https://doi.org/10.14358/PERS.83.4.269 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84589 [article]

Automated detection of Martian gullies from HiRISE imagery / Wei Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 12 (December 2015)  

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Monitoring coastal morphological changes using remote sensing and GIS in the Red river delta area, Vietnam / Si Son Tong in Photo interprétation, European journal of applied remote sensing, vol 50 n° 2 (juin 2014)

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Topographie, représentation et analyse morphologique 3D de drains, de conduits et de parois du karst / Stéphane Jaillet in Collection EDYTEM. cahiers de géographie, n° 12 (01/06/2011)  

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Reconstitution de la morphologie d'une rivière à méandres par l'utilisation de la photogrammétrie numérique : exemple du Sebou, Maroc / M. Igouzal in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 171 (Juillet 2003)

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Cours de randonnée et de cartographie / C. Raybaud (2000)

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Comparison of morphological characters and molecular markers for the analysis of hybridization in sessile and pedunculate oak / R. Bacilieri in Annales des Sciences forestières, vol 53 n° 1 ([01/02/1996])    

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Site et développement urbain / J.M. Avramides (1974)

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Bases et techniques d'une cartographie des sols, 1. Textes / M. Jamagne (1967)

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Bases et techniques d'une cartographie des sols, 2. Cartes / M. Jamagne (1967)

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Le cycle morphologique des dunes / L. Aufrere in Annales de géographie, n° 226 (juillet - août 1931)  

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