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Auteur Demetre Argialas |
Documents disponibles écrits par cet auteur (3)
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Mapping of forest tree distribution and estimation of forest biodiversity using Sentinel-2 imagery in the University Research Forest Taxiarchis in Chalkidiki, Greece / Maria Kampouri in Geocarto international, vol 34 n° 12 ([15/09/2019])
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Titre : Mapping of forest tree distribution and estimation of forest biodiversity using Sentinel-2 imagery in the University Research Forest Taxiarchis in Chalkidiki, Greece Type de document : Article/Communication Auteurs : Maria Kampouri, Auteur ; Polychronis Kolokoussis, Auteur ; Demetre Argialas, Auteur ; Vassilia Karathanassi, Auteur Année de publication : 2019 Article en page(s) : pp 1273 - 1285 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse d'image orientée objet
[Termes IGN] biomasse forestière
[Termes IGN] conservation des ressources forestières
[Termes IGN] écosystème forestier
[Termes IGN] espèce végétale
[Termes IGN] Grèce
[Termes IGN] image multibande
[Termes IGN] image multitemporelle
[Termes IGN] image Sentinel-MSI
[Termes IGN] indicateur de biodiversité
[Termes IGN] indice de diversité
[Termes IGN] modèle numérique de surface
[Termes IGN] réalité de terrain
[Termes IGN] segmentation d'imageRésumé : (Auteur) The aim of this study is to investigate the potential of Sentinel-2 imagery for the identification and determination of forest patches of particular interest, with respect to ecosystem integrity and biodiversity and to produce a relevant biodiversity map, based on Simpson’s diversity index in Taxiarchis university research forest, Chalkidiki, North Greece. The research is based on OBIA being developed on to bi-temporal summer and winter Sentinel-2 imagery. Fuzzy rules, which are based on topographic factors, such as terrain elevation and slope for the distribution of each tree species, derived from expert knowledge and field observations, were used to improve the accuracy of tree species classification. Finally, Simpson’s diversity index for forest tree species, was calculated and mapped, constituting a relative indicator for biodiversity for forest ecosystem organisms (fungi, insects, birds, reptiles, mammals) and carrying implications for the identification of patches prone to disturbance or that should be prioritized for conservation. Numéro de notice : A2019-465 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1489424 Date de publication en ligne : 12/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1489424 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93616
in Geocarto international > vol 34 n° 12 [15/09/2019] . - pp 1273 - 1285[article]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)
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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] reliefRésumé : (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
in International journal of geographical information science IJGIS > vol 31 n° 9-10 (September - October 2017) . - pp 1978 - 2000[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017051 RAB Revue Centre de documentation En réserve L003 Disponible A region-based level set segmentation for automatic detection of man-made objects from aerial and satellite Images / K. Karatzalos in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 6 (June 2009)
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Titre : A region-based level set segmentation for automatic detection of man-made objects from aerial and satellite Images Type de document : Article/Communication Auteurs : K. Karatzalos, Auteur ; Demetre Argialas, Auteur Année de publication : 2009 Article en page(s) : pp 667 - 677 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] détail topographique artificiel
[Termes IGN] détection du bâti
[Termes IGN] extraction automatique
[Termes IGN] image aérienne
[Termes IGN] image satellite
[Termes IGN] segmentation d'image
[Termes IGN] traitement géométrique de donnéesRésumé : (Auteur) A region-based level set segmentation was developed for the automatic detection of man-made objects from aerial and satellite images. The essence of the approach is to optimize the position and the geometric form of an evolving curve, by measuring information within the regions that compose a particular image partition based on their statistical description. The present region-based variational model is fully automated without the need to manually specify the position of the initial contour. Furthermore, it converges after a small number of iterations, allowing real-time applications. The developed algorithm was tested for the detection of roads, buildings and other man-made objects in a number of aerial and satellite images. The effectiveness of the algorithm is demonstrated by the experimental results and the performed qualitative and quantitative. Numéro de notice : A2009-259 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.6.667 En ligne : https://doi.org/10.14358/PERS.75.6.667 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29889
in Photogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 6 (June 2009) . - pp 667 - 677[article]