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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

  • remote sensing

  • VHRS imagery

  • HYPERSPECTRAL imagery

  • urban studies

GEMET - INSPIRE themes, version 1.0
  • Land cover
GEMET - Concepts
  • artificial land
  • urban ecology
GCMD Keywords viewer
  • LAND USE/LAND COVER CLASSIFICATION
  • INFRARED IMAGERY
  • VISIBLE IMAGERY
  • URBAN AREAS
TETIS Thesaurus, version 1.0 21112019
  • HYEP
  • Urbain
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
English
Jeu de caractères
Utf8
Catégorie ISO
  • Sciences de la terre, géosciences
  • Environnement
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).

Identifiant de la fiche
e324c038-08f3-4a11-aca2-7abbeda014e7 XML
Langue
English
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

Étendue spatiale

N
S
E
W


Mots clés

GCMD Keywords viewer
INFRARED IMAGERY LAND USE/LAND COVER CLASSIFICATION URBAN AREAS VISIBLE IMAGERY
GEMET - Concepts
artificial land urban ecology
GEMET - INSPIRE themes, version 1.0
Land cover
General
HYPERSPECTRAL imagery VHRS imagery remote sensing urban studies
TETIS Thesaurus, version 1.0 21112019
HYEP Urbain

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