European journal of remote sensing . vol 50 n° 1Paru le : 01/02/2017 |
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Ajouter le résultat dans votre panierIntegrating elevation data and multispectral high-resolution images for an improved hybrid Land Use/Land Cover mapping / Mirco Sturari in European journal of remote sensing, vol 50 n° 1 (2017)
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Titre : Integrating elevation data and multispectral high-resolution images for an improved hybrid Land Use/Land Cover mapping Type de document : Article/Communication Auteurs : Mirco Sturari, Auteur ; Emanuele Frontoni, Auteur ; Roberto Pierdicca, Auteur ; Adriano Mancini, Auteur ; Eva Savina Malinverni, Auteur ; Anna Nora Tassetti, Auteur ; Primo Zingaretti, Auteur Année de publication : 2017 Article en page(s) : pp 1 - 17 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] base de données d'occupation du sol
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification hybride
[Termes IGN] données altimétriques
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image multibande
[Termes IGN] intégration de données
[Termes IGN] occupation du solRésumé : (Auteur) The combination of elevation data together with multispectral high-resolution images is a new methodology for obtaining land use/land cover classification. It represents a step forward for both the accuracy and automation of LULC applications and allows users to setup thematic assignments through rules based on feature attributes and human expert interpretation of land usage. The synergy between different types of information means that LiDAR can give new hints at both the segmentation and hybrid classification steps, leading to a joint use of multispectral, spatial and elevation data. The output is a thematic map characterized by a custom-designed legend that is able to discriminate between land cover classes with similar spectral characteristics (level 3 of the CLC legend). Experimental results from a hilly farmland area with some urban structures (Musone river basin, Ancona, Italy) are used to highlight how the proposed methodology enhances land cover classification in heterogeneous environments. Numéro de notice : A2017-043 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2017.1274572 En ligne : http://doi.org/10.1080/22797254.2017.1274572 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84213
in European journal of remote sensing > vol 50 n° 1 (2017) . - pp 1 - 17[article]Object-based water body extraction model using Sentinel-2 satellite imagery / Gordana Kaplan in European journal of remote sensing, vol 50 n° 1 (2017)
[article]
Titre : Object-based water body extraction model using Sentinel-2 satellite imagery Type de document : Article/Communication Auteurs : Gordana Kaplan, Auteur ; Ugur Avdan, Auteur Année de publication : 2017 Article en page(s) : pp 143 - 150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] extraction automatique
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] lac
[Termes IGN] Macédoine
[Termes IGN] Normalized Difference Water Index
[Termes IGN] segmentation d'imageRésumé : (auteur) Water body extraction is an important part of water resource management and has been the topic of a number of research works related to remote sensing for over two decades. Extracting water bodies from satellite images with a pixel-based method or indexes cannot eliminate other objects that have a low albedo, such as shadows and built-up areas. Since their spectral differences cannot be separated, in this paper a method that combines a pixel-based index and object-based method has been used on a Sentinel-2 satellite image with a resolution of 10 m. The method uses image segmentation on a multispectral image containing 13 bands. It also uses indexes used for extracting water bodies, such as the Normalized Difference Water Index (NDWI). Two study areas with different characteristics have been chosen, one mountainous and one urban region, both of them located in Macedonia. Using object-based techniques and pixel-based indexes, such as NDWI, the results from the NDWI have been improved by a kappa value of more than 0.5. Numéro de notice : A2017-719 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2017.1297540 En ligne : https://doi.org/10.1080/22797254.2017.1297540 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88375
in European journal of remote sensing > vol 50 n° 1 (2017) . - pp 143 - 150[article]