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Unmixing-based Sentinel-2 downscaling for urban land cover mapping / Fei Xu in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)
[article]
Titre : Unmixing-based Sentinel-2 downscaling for urban land cover mapping Type de document : Article/Communication Auteurs : Fei Xu, Auteur ; Ben Somers, Auteur Année de publication : 2021 Article en page(s) : pp 133 - 154 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] bande spectrale
[Termes IGN] Berlin
[Termes IGN] Bruxelles
[Termes IGN] cartographie urbaine
[Termes IGN] Cologne
[Termes IGN] corrélation
[Termes IGN] fusion d'images
[Termes IGN] image Sentinel-MSI
[Termes IGN] matrice de co-occurrence
[Termes IGN] occupation du solRésumé : (auteur) With the launch of Sentinel-2 new opportunities for large scale urban mapping arise. However, the spectral information embedded in the Sentinel-2 20 m spatial resolution bands cannot yet be fully explored in heterogeneous urban landscapes. The 20 m image pixels are often composed of different land covers, resulting in a difficult to interpret mixed pixel spectrum. Here, we propose an unmixing-based image fusion algorithm (UnFuSen2) that self-adapts to the spectral variability of varying land covers and improves the image fusion accuracy by constraining the unmixing equations on the basis of spectral mixing models and the correlation between spectral bands of coarse and fine spatial resolution, respectively. When compared to alternative state-of-the-art downscaling methods UnFuSen2 consistently showed the highest accuracy when applied across test sites in three different European cities (RMSEUnFuSen2 = 203 vs RMSEalternatives = [252, 337]). In a next step, we applied Multiple Endmember Spectral Mixture Analysis (MESMA) on the downscaled Sentinel-2 image cube (i.e. ten 10 m bands) to generate subpixel urban land cover fractions. We compared our MESMA results against the traditional MESMA output as applied on the original Sentinel-2 image cube (i.e. four 10 m bands and six 20 m bands) and tested its robustness against reference data obtained over all three study sites. Results revealed an average decrease in RMSE of respectively 18% and 8% for impervious surface and vegetation fractions when our approach was compared to the traditional MESMA outcomes. Numéro de notice : A2021-015 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.11.009 Date de publication en ligne : 26/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.11.009 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96419
in ISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 133 - 154[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021011 SL Revue Centre de documentation Revues en salle Disponible 081-2021013 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021012 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Virtual Support Vector Machines with self-learning strategy for classification of multispectral remote sensing imagery / Christian Geiss in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
[article]
Titre : Virtual Support Vector Machines with self-learning strategy for classification of multispectral remote sensing imagery Type de document : Article/Communication Auteurs : Christian Geiss, Auteur ; Patrick Aravena Pelizari, Auteur ; Lukas Blickensdörfer, Auteur ; Hannes Taubenböck, Auteur Année de publication : 2019 Article en page(s) : pp 42 - 58 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] apprentissage automatique
[Termes IGN] classification
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] Cologne
[Termes IGN] échantillon
[Termes IGN] échantillonnage
[Termes IGN] image à très haute résolution
[Termes IGN] image multibande
[Termes IGN] invariant
[Termes IGN] Kenya
[Termes IGN] séparateur à vaste margeRésumé : (Auteur) We follow the idea of learning invariant decision functions for remote sensing image classification with Support Vector Machines (SVM). To do so, we generate artificially transformed samples (i.e., virtual samples) from available prior knowledge. Labeled samples closest to the separating hyperplane with maximum margin (i.e., the Support Vectors) are identified by learning an initial SVM model. The Support Vectors are used for generating virtual samples by perturbing the features to which the model should be invariant. Subsequently, the model is relearned using the Support Vectors and the virtual samples to eventually alter the hyperplane with maximum margin and enhance generalization capabilities of decision functions. In contrast to existing approaches, we establish a self-learning procedure to ultimately prune non-informative virtual samples from a possibly arbitrary invariance generation process to allow for robust and sparse model solutions. The self-learning strategy jointly considers a similarity and margin sampling constraint. In addition, we innovatively explore the invariance generation process in the context of an object-based image analysis framework. Image elements (i.e., pixels) are aggregated to image objects (as represented by segments/superpixels) with a segmentation algorithm. From an initial singular segmentation level, invariances are encoded by varying hyperparameters of the segmentation algorithm in terms of scale and shape. Experimental results are obtained from two very high spatial resolution multispectral data sets acquired over the city of Cologne, Germany, and the Hagadera Refugee Camp, Kenya. Comparative model accuracy evaluations underline the favorable performance properties of the proposed methods especially in settings with very few labeled samples. Numéro de notice : A2019-203 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.03.001 Date de publication en ligne : 12/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.03.001 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92666
in ISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 42 - 58[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019051 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019053 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019052 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt 3D builbing reconstruction from lidar based on a cell decomposition approach / Martin Kada (01/12/2009)
contenu dans CMRT09 Object extraction for 3D city models, road databases and traffic monitoring-concepts, algorithms and evaluation / Uwe Stilla (2009)
Titre : 3D builbing reconstruction from lidar based on a cell decomposition approach Type de document : Article/Communication Auteurs : Martin Kada, Auteur ; L. Mckinley, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 01/12/2009 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 38-3-W4 Conférence : CMRT 2009, City Models, Roads and Traffic, Object extraction for 3D city models, road databases, traffic monitoring 03/09/2009 04/09/2009 Paris France OA ISPRS Archives Importance : pp 47 - 52 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] Berlin
[Termes IGN] Cologne
[Termes IGN] données lidar
[Termes IGN] plan cadastral
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] texturage
[Termes IGN] toit
[Termes IGN] villeRésumé : (Auteur) The reconstruction of 3D city models has matured in recent years from a research topic and niche market to commercial products and services. When constructing models on a large scale, it is inevitable to have reconstruction tools available that offer a high level of automation and reliably produce valid models within the required accuracy. In this paper, we present a 3D building reconstruction approach, which produces LOD2 models from existing ground plans and airborne LIDAR data. As well-formed roof structures are of high priority to us, we developed an approach that constructs models by assembling building blocks from a library of parameterized standard shapes. The basis of our work is a 2D partitioning algorithm that splits a building's footprint into nonintersecting, mostly quadrangular sections. A particular challenge thereby is to generate a partitioning of the footprint that approximates the general shape of the outline with as few pieces as possible. Once at hand, each piece is given a roof shape that best fits the LIDAR points in its area and integrates well with the neighbouring pieces. An implementation of the approach is used now for quite some time in a production environment and many commercial projects have been successfully completed. The second part of this-paper reflects the experiences that we have made with this approach working on the 3D reconstruction of the entire cities of East Berlin and Cologne. Numéro de notice : C2009-007 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Communication DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVIII/3-W4/pub/CMRT09_47.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65047 Cologne cathedral history through surveying: monitoring a German landmark through history / H. Müller in Geoinformatics, vol 7 n° 7 (01/10/2004)
[article]
Titre : Cologne cathedral history through surveying: monitoring a German landmark through history Type de document : Article/Communication Auteurs : H. Müller, Auteur Année de publication : 2004 Article en page(s) : pp 42 - 45 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie moderne
[Termes IGN] archéométrie
[Termes IGN] cathédrale
[Termes IGN] Cologne
[Termes IGN] lever tachéométrique
[Termes IGN] modélisation 3D
[Termes IGN] monument historique
[Termes IGN] télémètre laser terrestre
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) Cologne Cathedral as it shows itself nowadays is one of the most famous German architectural monuments and has been Cologne's dominating landmark for centuries. The two towers are 157,4 m tall, the cathedral is 144,6 m long and 86,2 m wide. The cathedral is the seat of the Archbishop of Cologne and is a spiritual centre of the religious life of the Roman Catholic Church in Germany. Due to its enormous size and being built up in pure original Gothic style, it is a Gothic masterpiece and, thus, is even one of Europe's most famous monuments. Numéro de notice : A2004-578 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27094
in Geoinformatics > vol 7 n° 7 (01/10/2004) . - pp 42 - 45[article]Der Tübinger Atlas des Vorderen Orients (TAVO) / W. Denk in Annuaire international de cartographie, n° 20 (1980)
[article]
Titre : Der Tübinger Atlas des Vorderen Orients (TAVO) Titre original : L'atlas du Proche-Orient de Tübingen (TAVO) Type de document : Article/Communication Auteurs : W. Denk, Auteur ; W. Rollig, Auteur Année de publication : 1980 Article en page(s) : pp 54 - 77 Langues : Allemand (ger) Descripteur : [Vedettes matières IGN] Cartographie étrangère
[Termes IGN] Afghanistan
[Termes IGN] atlas
[Termes IGN] Bade-Wurtemberg (Allemagne)
[Termes IGN] Cologne
[Termes IGN] géographie générale
[Termes IGN] histoire
[Termes IGN] Mayence
[Termes IGN] Persique, golfe
[Termes IGN] Proche-Orient
[Termes IGN] TurquieNuméro de notice : A1980-058 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=23504
in Annuaire international de cartographie > n° 20 (1980) . - pp 54 - 77[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 53767-01 39.04 Livre Centre de documentation En réserve L003 Disponible