Toulouse 2015 Supervised SVN classification results for 600 urban trees according to a 3 level nomenclature

Hyperspectral data were obtained during an acquisition campaign led on Toulouse (France) urban area on July 2015 using Hyspex instrument which provides 408 spectral bands spread over 0.4 – 2.5 μ. Flight altitude lead to 2 m spatial resolution images. Supervised SVN classification results for 600 urban trees according to a 3 level nomenclature: leaf type (5 classes), family (12 and 19 classes) and species (14 and 27 classes). The number of classes differ for the two latter as they depend on the minimum number of individuals considered (4 and 10 individuals per class respectively). Trees positions have been acquired using differential GPS and are given with centimetric to decimetric precision. A randomly selected subset of these trees has been used to train machine SVM and Random Forest classification algorithms. Those algorithms were applied to hyperspectral images using a number of classes for family (12 and 19 classes) and species (14 and 27 classes) levels defined according to the minimum number of individuals considered during training/validation process (4 and 10 individuals per class, respectively). Global classification precision for several training subsets is given by Brabant et al, 2019 (https://www.mdpi.com/470202) in terms of averaged overall accuracy (AOA) and averaged kappa index of agreement (AKIA).

Simple

Date ( Révision )
2022-05-17T19:09:06
Edition
1.0
Date d'édition
2015-01-01
Identificateur
e324c038-08f3-4a11-aca2-7abbeda014e7
Point de recherche
UMR TETIS - CNRS - Christiane Weber

But
Provide with urban trees 3 level nomenclature
Etat
Finalisé
Point de recherche
UMR TETIS - CNRS - Christiane Weber

Fréquence de mise à jour
Non planifiée
General ( Thème )
  • remote sensing
  • VHRS imagery
  • HYPERSPECTRAL imagery
  • urban studies
GEMET - INSPIRE themes, version 1.0 ( Thème )
GEMET - Concepts ( Thème )
GCMD Keywords viewer ( Thème )
TETIS Thesaurus, version 1.0 21112019 ( Thème )
Limitation d'utilisation
This work is licensed under a Creative Commons Attribution 4.0 License (CC BY 4.0, https://creativecommons.org/licenses/by/4.0 ).
Contraintes d'accès
Licence
Contraintes d'utilisation
Licence
Restrictions de manipulation
Non classifié
Explications sur les restrictions
unclassified
Système de classification
no classification in particular
Description de manipulation
description
Type de représentation spatiale
Vecteur
Langue
en
Jeu de caractères
Utf8
Catégorie ISO
  • Geoscientific information
  • Environment
N
S
E
W


Date de début
2015-07-01T00:00:00Z
Date de fin
2015-07-31T00:00:00Z
Informations supplémentaires
some additional information
Nom du système de référence
EPSG / 4326
Format (encodage)
  • ESRI Shapefile ( 1.0 )

Ressource en ligne
geopackage file ( file for download )
Ressource en ligne
species_27classes ( OGC:WMS )

WMS Service

Niveau
Jeu de données

Résultat de conformité

Autres appellations ou acronymes
This is is some data quality check report
Date ( Publication )
2022-05-17T19:09:06
Explication
some explanation about the conformance
Degré de conformité
Oui

Résultat de conformité

Date ( Publication )
2010-12-08T12:00:00
Explication
See the referenced specification
Degré de conformité
Oui

Résultat de conformité

Date ( Publication )
2008-12-04T12:00:00
Explication
See the referenced specification
Degré de conformité
Oui
Généralités sur la provenance
Hyperspectral data were obtained during an acquisition campaign led on Toulouse (France) urban area on July 2015 using Hyspex instrument which provides 408 spectral bands spread over 0.4 – 2.5 μ. Flight altitude lead to 2 m spatial resolution images. Supervised SVN classification results for 600 urban trees according to a 3 level nomenclature: leaf type (5 classes), family (12 and 19 classes) and species (14 and 27 classes). The number of classes differ for the two latter as they depend on the minimum number of individuals considered (4 and 10 individuals per class respectively). Trees positions have been acquired using differential GPS and are given with centimetric to decimetric precision. A randomly selected subset of these trees has been used to train machine SVM and Random Forest classification algorithms. Those algorithms were applied to hyperspectral images using a number of classes for family (12 and 19 classes) and species (14 and 27 classes) levels defined according to the minimum number of individuals considered during training/validation process (4 and 10 individuals per class, respectively). Global classification precision for several training subsets is given by Brabant et al, 2019 (https://www.mdpi.com/470202) in terms of averaged overall accuracy (AOA) and averaged kappa index of agreement (AKIA).

gmd:MD_Metadata

Identifiant de la fiche
e324c038-08f3-4a11-aca2-7abbeda014e7 XML
Langue
en
Jeu de caractères
Utf8
Identifiant de la fiche de métadonnées parent
HYEP Project 83867504-286c-4436-b3fc-436ffdc1d912
Type de ressource
Jeu de données
Date des métadonnées
2022-05-17T19:25:04
Nom du standard de métadonnées
ISO 19115:2003/19139
Version du standard de métadonnées
1.0
Point de contact
LETG - Univ Rennes 2 - Thomas Houet

Point de recherche
UMR TETIS - CNRS - Christiane Weber

Editeur (publication)
UMR TETIS - CNRS - Claudia Lavalley

Aperçus

SVN Toulouse urban Trees classification

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