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Classification of poplar trees with object-based ensemble learning algorithms using Sentinel-2A imagery / H. Tombul in Journal of geodetic science, vol 10 n° 1 (January 2020)
[article]
Titre : Classification of poplar trees with object-based ensemble learning algorithms using Sentinel-2A imagery Type de document : Article/Communication Auteurs : H. Tombul, Auteur ; Ismail Colkesen, Auteur ; Taskin Kavzoglu, Auteur Année de publication : 2020 Article en page(s) : pp 14 - 22 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme d'apprentissage
[Termes IGN] analyse canonique
[Termes IGN] analyse comparative
[Termes IGN] bande spectrale
[Termes IGN] boosting adapté
[Termes IGN] carte de la végétation
[Termes IGN] carte thématique
[Termes IGN] classification orientée objet
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Sentinel-MSI
[Termes IGN] jeu de données
[Termes IGN] Populus (genre)
[Termes IGN] précision de la classification
[Termes IGN] Rotation Forest classification
[Termes IGN] segmentation multi-échelle
[Termes IGN] TurquieRésumé : (auteur) The poplar species in the forest ecosystems are one of the most valuable and beneficial species for the society and environment. Conventional methods require high cost, time and labor need, and the results obtained vary and are insu˚cient in terms of achieved accuracy level. Determination of poplar cultivated fields and mapping of their spatial sites play a vital role for decision-makers and planners to enhance the economic and ecological value of poplar trees. The study aims to map Poplar (P. deltoides) cultivated areas in Akyazi district of Sakarya, Turkey province using various combinations of the Sentinel-2A image bands. For this purpose, object-based classification based on multi-resolution segmentation algorithm was utilized to produce image objects and ensemble learning algorithms, namely, Adaboost (AdaB), Random Forest (RF), Rotation Forest (RotFor) and Canonical correlation forest (CCF) were applied to produce thematic maps. In order to analyze the effects of the spectral bands of the Sentinel-2A image on the object-based classification performance, three datasets consisting of different spectral band combinations (i.e. four 10 m bands, six 20 m bands and ten 10m pan-sharpened bands) were used. The results showed that the RotFor and CCF classifiers produced superior classification performances compared to the AdaB and RF classifiers for the band combinations regarded in this study. Moreover, it was found that determination of poplar tree class level accuracy reached to ~94% in terms of F-score. It was also observed that the inclusion of the six spectral bands at 20 m resolution resulted in a noteworthy increase in classification accuracy (up to 6%) compared to single 10m band combination. Numéro de notice : A2020-420 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jogs-2020-0003 Date de publication en ligne : 04/05/2020 En ligne : https://doi.org/10.1515/jogs-2020-0003 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95477
in Journal of geodetic science > vol 10 n° 1 (January 2020) . - pp 14 - 22[article]Focal plant species and soil factors in Mediterranean coastal dunes: An undisclosed liaison? / Claudia Angiolini in Estuarine, Coastal and Shelf Science, vol 211 (31 October 2018)
[article]
Titre : Focal plant species and soil factors in Mediterranean coastal dunes: An undisclosed liaison? Type de document : Article/Communication Auteurs : Claudia Angiolini, Auteur ; Gianmaria Bonari, Auteur ; Marco Landi, Auteur Année de publication : 2018 Article en page(s) : pp 248 - 258 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse canonique
[Termes IGN] dune
[Termes IGN] facteur édaphique
[Termes IGN] indicateur biologique
[Termes IGN] littoral méditerranéen
[Termes IGN] microhabitat
[Termes IGN] pédologie locale
[Termes IGN] placette d'échantillonnage
[Termes IGN] Toscane (Italie)
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Understanding the response of plant species to soil factors on coastal sand dunes is critical for effective conservation of coastal habitats in the Mediterranean basin. Our main objectives were to investigate: i) the main soil factors driving species composition in a Mediterranean coastal dune environment; ii) the ecological requirements of focal plant species with respect to single soil factors; iii) whether the focal species of a given macrohabitat (including EU habitats) have similar edaphic needs. We identified 108 plots with three macrohabitats as strata (embryo dunes; mobile dunes; fixed dunes) by random stratified sampling design along the Tyrrhenian coast of central Italy in areas with a high degree of biodiversity and naturalness. Vegetation and soil data were collected in the plots.
Canonical Correspondence Analysis (CCA) confirmed that soil had a main role in driving focal dune species composition as found in other Mediterranean areas and indicated that three factors (field capacity, pH and CaCO3) sufficiently explain patterns of plant species. An inverse relation between field capacity, which proves to be the most decisive feature for differences in species ecological requirements between macrohabitats, and pH was observed. Generalized Additive Models (GAMs) showed that: i) the focal species of fixed dunes have a higher probability of occurrence and response curves that overlap at high field capacity and TOC values and at low pH, showing an opposite trend with respect to the species of embryonic and mixed dunes; ii) species of mixed dunes have a probability of occurrence linked to different values of CaCO3, with Ammophila arenaria showing its optimum at high CaCO3 values. Thus our results sustain the hypothesis that dune focal species, diagnostic and characteristic of coastal dune marcohabitats, have different ecological responses with respect to soil factors. Moreover, species within the same habitat can have different ecological responses due to species competition. Data about edaphic requirements of sand dune species and modelling of their ecological responses suggests that focal dune species can be bio-indicators of soil conditions and provide useful indications for conservation, monitoring and restoration of Mediterranean coastal habitats.Numéro de notice : A2017-249 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1016/j.ecss.2017.06.001 Date de publication en ligne : 08/06/2017 En ligne : https://doi.org/10.1016/j.ecss.2017.06.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85209
in Estuarine, Coastal and Shelf Science > vol 211 (31 October 2018) . - pp 248 - 258[article]Hyperspectral image classification with canonical correlation forests / Junshi Xia in IEEE Transactions on geoscience and remote sensing, vol 55 n° 1 (January 2017)
[article]
Titre : Hyperspectral image classification with canonical correlation forests Type de document : Article/Communication Auteurs : Junshi Xia, Auteur ; Naoto Yokoya, Auteur ; Akira Iwasaki, Auteur Année de publication : 2017 Article en page(s) : pp 421 - 431 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse canonique
[Termes IGN] analyse en composantes indépendantes
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classificateur
[Termes IGN] classification
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image hyperspectrale
[Termes IGN] Rotation Forest classificationRésumé : (Auteur) Multiple classifier systems or ensemble learning is an effective tool for providing accurate classification results of hyperspectral remote sensing images. Two well-known ensemble learning classifiers for hyperspectral data are random forest (RF) and rotation forest (RoF). In this paper, we proposed to use a novel decision tree (DT) ensemble method, namely, canonical correlation forest (CCF). More specifically, several individual canonical correlation trees (CCTs) that are binary DTs, which use canonical correlation components for the hyperplane splitting, are used to construct the CCF. Additionally, we adopt the projection bootstrap technique in CCF, in which the full spectral bands are retained for split selection in the projected space. The techniques aforementioned allow the CCF to improve the accuracy of member classifiers and diversity within the ensemble. Furthermore, the CCF is extended to the spectral-spatial frameworks that incorporate Markov random fields, extended multiattribute profiles (EMAPs), and the ensemble of independent component analysis and rolling guidance filter (E-ICA-RGF). Experimental results on six hyperspectral data sets are used to indicate the comparative effectiveness of the proposed method, in terms of accuracy and computational complexity, compared with RF and RoF, and it turns out that CCF is a promising approach for hyperspectral image classification not only with spectral information but also in the spectral-spatial frameworks. Numéro de notice : A2017-021 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2607755 En ligne : https://doi.org/10.1109/TGRS.2016.2607755 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83953
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 1 (January 2017) . - pp 421 - 431[article]L'analyse des données / J.M. Bouroche (2002)
Titre : L'analyse des données Type de document : Monographie Auteurs : J.M. Bouroche, Auteur ; Gilbert Saporta, Auteur Editeur : Paris : Presses Universitaires de France - PUF Année de publication : 2002 Collection : Que-sais-je num. 1854 Importance : 127 p. Format : 11 x 18 cm ISBN/ISSN/EAN : 978-2-13-052495-3 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Mathématique
[Termes IGN] analyse canonique
[Termes IGN] analyse de données
[Termes IGN] analyse des correspondances
[Termes IGN] analyse discriminante
[Termes IGN] analyse en composantes principales
[Termes IGN] classificationNuméro de notice : 52791 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Monographie Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=59409 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 52791-01 23.00 Livre Centre de documentation Mathématiques Disponible Initiation à l'analyse des données / Jean de Lagarde (2000)
Titre : Initiation à l'analyse des données Type de document : Guide/Manuel Auteurs : Jean de Lagarde, Auteur Mention d'édition : 3 Editeur : Paris : Dunod Année de publication : 2000 Collection : Eco Sup Importance : 162 p. Format : 15 x 24 cm ISBN/ISSN/EAN : 978-2-10-004148-0 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] analyse canonique
[Termes IGN] analyse de données
[Termes IGN] analyse de variance
[Termes IGN] analyse des correspondances
[Termes IGN] analyse discriminante
[Termes IGN] analyse en composantes principales
[Termes IGN] analyse factorielle
[Termes IGN] calcul matriciel
[Termes IGN] classification automatique
[Termes IGN] corrélation
[Termes IGN] régression multipleRésumé : (Editeur) L'auteur explique clairement la base mathématique des différentes méthodes d'analyse des données, dévoile les mécanismes essentiels de ces méthodes et montre, au moyen de nombreux exemples puisés dans le vie courante, l'étonnante variété des cas d'application. Numéro de notice : 13126 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Manuel de cours Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=46247 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 13126-01 23.60 Livre Centre de documentation Mathématiques Disponible