Descripteur
Termes IGN > aménagement > urbanisme > zone urbaine
zone urbaineVoir aussi |
Documents disponibles dans cette catégorie (306)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Critical analysis of model-based incoherent polarimetric decomposition methods and investigation of deorientation effect / Pooja Mishra in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)
[article]
Titre : Critical analysis of model-based incoherent polarimetric decomposition methods and investigation of deorientation effect Type de document : Article/Communication Auteurs : Pooja Mishra, Auteur ; Akanksha Garg, Auteur ; Dharmendra Singh, Auteur Année de publication : 2017 Article en page(s) : pp 4868 - 4877 Note générale : Bibliothèque Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] décomposition d'image
[Termes IGN] diffusion du rayonnement
[Termes IGN] données polarimétriques
[Termes IGN] image ALOS
[Termes IGN] image ALOS-PALSAR
[Termes IGN] occupation du sol
[Termes IGN] polarimétrie radar
[Termes IGN] valeur propre
[Termes IGN] zone urbaineRésumé : (Auteur) This paper critically analyzes several incoherent model-based decomposition methods for assessing the effect of deorientation in characterization of various land covers. It has been found that even after performing decomposition, ambiguity still occurs in scattering response from various land covers, such as urban and vegetation. Researchers introduced the concept of deorientation to remove this ambiguity. Therefore, in this paper, a critical analysis has been carried out using seven different three- and four-component decomposition methods with and without deorientation and two Eigen decomposition-based methods to investigate the scattering response on various land covers, such as urban, vegetation, bare soil, and water. The comprehensive evaluation of decomposition and deorientation effect has been performed by both visual and quantitative analyses. Two types of quantitative analysis have been performed; first, by observing percentage of scattering power and second, by analyzing the variation in the number of pixels in different land covers for each scattering contribution. The analysis shows that deorientation increases not only the power but also the number of pixels for surface and double bounce scattering. The number of pixels representing volume scattering remain almost the same for all the methods with or without deorientation, whereas volume scattering power reduces after deorientation. Eigen decomposition-based methods are observed to solve the problem of overestimation of volume scattering power. Numéro de notice : A2017-657 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2652060 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2652060 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87067
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 9 (September 2017) . - pp 4868 - 4877[article]Effects of using different sources of remote sensing and geographic information system data on urban stormwater 2D–1D modeling / Yi Hong in Applied sciences, vol 7 n° 9 (September 2017)
[article]
Titre : Effects of using different sources of remote sensing and geographic information system data on urban stormwater 2D–1D modeling Type de document : Article/Communication Auteurs : Yi Hong, Auteur ; Céline Bonhomme, Auteur ; Bahman Soheilian , Auteur ; Ghassan Chebbo, Auteur Année de publication : 2017 Projets : TrafiPollu / Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] données lidar
[Termes IGN] données localisées 2D
[Termes IGN] données localisées 3D
[Termes IGN] eau pluviale
[Termes IGN] logiciel de simulation
[Termes IGN] modèle de simulation
[Termes IGN] modèle numérique de terrain
[Termes IGN] réseau d'assainissement
[Termes IGN] ruissellement
[Termes IGN] surface imperméable
[Termes IGN] utilisation du sol
[Termes IGN] ville
[Termes IGN] zone urbaineRésumé : (auteur) Remote sensing (RS) and geographic information system (GIS) data is increasingly used in urban stormwater modeling. The undirected use of such data may waste economic and human resources. In order to provide guidance for practitioners to efficiently use different data collection resources, as well as give a reference for future works, this paper aims to assess the effects of using free access GIS data and ad hoc RS data on urban 2D–1D stormwater modeling. The 2D-surface Two-dimensional Runoff, Erosion, and Export model (TREX) model was published in Science of the Total Environment in 2008. The 1D-sewer CANOE (Logiciel intégré de conception et de diagnostic des réseaux d’assainissement) model was published in Journal of Hydrology in 2004. The two models are integrated in the TRENOE (TREX-CANOE) platform. The modeling approach is applied to a small urban catchment near Paris (Le Perreux sur Marne, 0.12 km2). Simulation results reveal that the detailed land-use information derived from multiple data sources is a crucial factor for accurate simulations. Nevertheless, using the very high resolution LiDAR (light detection and ranging) data is not equally significant for the water flow simulations at sewage outlets. Finally, we suggest that using the free access GIS data accompanying the urban sewer network design might be an acceptable low-cost solution for accurate urban 2D–1D stormwater modeling during moderate rainfall events. Further studies of urban stormwater modeling could focus on the development of “suitable” models with “enough” input data, depending on the management/research objectives. Numéro de notice : A2017-842 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/app7090904 Date de publication en ligne : 05/09/2017 En ligne : https://doi.org/10.3390/app7090904 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89409
in Applied sciences > vol 7 n° 9 (September 2017)[article]Potential application of remote sensing in monitoring ecosystem services of forests, mangroves and urban areas / Ram Avtar in Geocarto international, vol 32 n° 8 (August 2017)
[article]
Titre : Potential application of remote sensing in monitoring ecosystem services of forests, mangroves and urban areas Type de document : Article/Communication Auteurs : Ram Avtar, Auteur ; Pankaj Kumar, Auteur ; Akiko Oono, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 874 - 885 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aide à la décision
[Termes IGN] forêt
[Termes IGN] image aérienne
[Termes IGN] image optique
[Termes IGN] image radar
[Termes IGN] image satellite
[Termes IGN] mangrove
[Termes IGN] service écosystémique
[Termes IGN] surveillance écologique
[Termes IGN] zone urbaineRésumé : (Auteur) The application of remote sensing (RS) techniques to monitor ecosystem services has increased in recent years. Nevertheless, the potential application of RS to monitor some of ecosystem services is still challenging. The paper reviews the applications of RS to monitor ecosystem services of forests, mangroves and urban areas. Satellite data provide substantial information about dynamics of environmental changes over time from local to global scale. These information are useful data sources for the people who are involved in the on-going evaluation and decision-making process to manage ecosystem. Many recent research papers on the topic were reviewed to find new applications and limitations of RS for monitoring ecosystem services. Advanced RS techniques have high potential to monitor ecosystem services with the advancement of sensors ranging from aerial photography to high and medium resolution optical RS and from hyperspectral RS to microwave RS. Numéro de notice : A2017-456 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1206974 Date de publication en ligne : 15/08/2016 En ligne : http://dx.doi.org/10.1080/10106049.2016.1206974 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86381
in Geocarto international > vol 32 n° 8 (August 2017) . - pp 874 - 885[article]A relative evaluation of random forests for land cover mapping in an urban area / Di Shi in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 8 (August 2017)
[article]
Titre : A relative evaluation of random forests for land cover mapping in an urban area Type de document : Article/Communication Auteurs : Di Shi, Auteur ; Xiaojun Yang, Auteur Année de publication : 2017 Article en page(s) : pp 541 - 552 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] objet géographique complexe
[Termes IGN] occupation du sol
[Termes IGN] Perceptron multicouche
[Termes IGN] zone urbaineRésumé : (auteur) Random forests as a novel ensemble learning algorithm have significant potential for land cover mapping in complex areas but have not been sufficiently tested by the remote sensing community relative to some more popular pattern classifiers. In this research, we implemented random forests as a pattern classifier for land cover mapping from a satellite image covering a complex urban area, and evaluated the performance relative to several popular classifiers including Gaussian maximum likelihood (GML), multi-layer-perceptron networks (MLP), and support vector machines (SVM). Each classifier was carefully configured with the parameter settings recommended by recent literature, and identical training data were used in each classification. The accuracy of each classified map was further evaluated using identical reference data. Random forests were slightly more accurate than SVM and MLP but significantly better than GML in the overall map accuracy. Random forests and support vector machines generated almost identical overall map accuracy, but the former produced a smaller standard deviation of categorical accuracies, suggesting its better overall capability in classifying both homogeneous and heterogeneous land cover classes. Random forests have shown its robustness due to the most accurate classification on the whole, relatively balanced performance across all land cover categories, and relatively easier to implement. These findings should help promote the use of random forests for land cover classification in complex areas. Numéro de notice : A2017-435 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.14358/PERS.83.8.541 En ligne : https://doi.org/10.14358/PERS.83.8.541 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86339
in Photogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 8 (August 2017) . - pp 541 - 552[article]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)
[article]
Titre : Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks Type de document : Article/Communication Auteurs : Rasha Alshehhi, Auteur ; Prashanth Reddy Marpu, Auteur ; Wei Lee Woon, Auteur ; Mauro Dalla Mura, Auteur Année de publication : 2017 Article en page(s) : pp 139 - 149 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] architecture de réseau
[Termes IGN] classification par réseau neuronal
[Termes IGN] détection du bâti
[Termes IGN] extraction automatique
[Termes IGN] extraction du réseau routier
[Termes IGN] filtrage numérique d'image
[Termes IGN] image à haute résolution
[Termes IGN] réseau neuronal convolutif
[Termes IGN] tachèle
[Termes IGN] test de performance
[Termes IGN] zone urbaineRésumé : (Auteur) Extraction of man-made objects (e.g., roads and buildings) from remotely sensed imagery plays an important role in many urban applications (e.g., urban land use and land cover assessment, updating geographical databases, change detection, etc). This task is normally difficult due to complex data in the form of heterogeneous appearance with large intra-class and lower inter-class variations. In this work, we propose a single patch-based Convolutional Neural Network (CNN) architecture for extraction of roads and buildings from high-resolution remote sensing data. Low-level features of roads and buildings (e.g., asymmetry and compactness) of adjacent regions are integrated with Convolutional Neural Network (CNN) features during the post-processing stage to improve the performance. Experiments are conducted on two challenging datasets of high-resolution images to demonstrate the performance of the proposed network architecture and the results are compared with other patch-based network architectures. The results demonstrate the validity and superior performance of the proposed network architecture for extracting roads and buildings in urban areas. Numéro de notice : A2017-512 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.05.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.05.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86458
in ISPRS Journal of photogrammetry and remote sensing > vol 130 (August 2017) . - pp 139 - 149[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017083 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017082 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Robust point cloud classification based on multi-level semantic relationships for urban scenes / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 129 (July 2017)PermalinkEffects of urban tree canopy loss on land surface temperature magnitude and timing / Arthur Elmes in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)PermalinkExtracting urban functional regions from points of interest and human activities on location-based social networks / Song Gao in Transactions in GIS, vol 21 n° 3 (June 2017)PermalinkModeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules / Yongjiu Feng in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)PermalinkRetrieving spatial variations of land surface temperatures from satellite data–Cairo region, Egypt / Mohamed E. Hereher in Geocarto international, vol 32 n° 5 (May 2017)PermalinkUrban land use/land cover discrimination using image-based reflectance calibration methods for hyperspectral data / Shailesh S. Deshpande in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 5 (May 2017)PermalinkToward 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)PermalinkEvaluation of quad-constellation GNSS precise point positioning in Egypt / Emad El Manaily in Artificial satellites, vol 52 n° 1 (March 2017)PermalinkAdaptive time-variant adjustment for the positioning errors of a mobile mapping platform in GNSS-hostile areas / Jiawei Han in Survey review, vol 49 n° 352 (March 2017)PermalinkAttribute profiles on derived features for urban land cover classification / Bharath Bhushan Damodaran in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 3 (March 2017)Permalink