Date (Revision)

2022-05-17T19:09:06

Edition

1.0

Edition date

2015-01-01

Citation identifier

e324c038-08f3-4a11-aca2-7abbeda014e7

Cited responsible party

Organisation name	Individual name	Electronic mail address	Role
UMR TETIS - CNRS	Christiane Weber	Christiane.Weber@cnrs.fr	Principal investigator

Purpose

Provide with urban trees 3 level nomenclature

Status

Completed

Point of contact

Organisation name	Individual name	Electronic mail address	Role
UMR TETIS - CNRS	Christiane Weber	Christiane.Weber@cnrs.fr	Principal investigator

Maintenance and update frequency

Not planned

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

Use limitation

This work is licensed under a Creative Commons Attribution 4.0 License (CC BY 4.0, https://creativecommons.org/licenses/by/4.0 ).

Access constraints

License

Use constraints

License

Classification

Unclassified

User note

unclassified

Classification system

no classification in particular

Handling description

description

Spatial representation type

Vector

Language

English

Character set

UTF8

Topic category

• Geoscientific information
• Environment

Begin date

2015-07-01T00:00:00Z

End date

2015-07-31T00:00:00Z

Supplemental Information

some additional information

Reference system identifier

EPSG / 4326

Distribution format

Name	Version
ESRI Shapefile	1.0

OnLine resource

Protocol	Linkage	Name
file for download	https://zenodo.org/record/3611240/files/Fields_samples.7z?download=1	geopackage file
OGC:WMS	http://idg-tetis-gs.teledetection.fr:8080/geoserver/idg-tetis/wms	species_27classes

Hierarchy level

Dataset

Statement

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/47020 2) in terms of averaged overall accuracy (AOA) and averaged kappa index of agreement (AKIA).

Metadata

File identifier

e324c038-08f3-4a11-aca2-7abbeda014e7 XML

Metadata language

English

Character set

UTF8

Parent identifier

HYEP Project

83867504-286c-4436-b3fc-436ffdc1d912

Hierarchy level

Dataset

Date stamp

2022-05-17T19:25:04

Metadata standard name

ISO 19115:2003/19139

Metadata standard version

1.0

Metadata author

Organisation name	Individual name	Electronic mail address	Role
LETG - Univ Rennes 2	Thomas Houet	thomas.houet@univ-rennes2.fr	Point of contact
UMR TETIS - CNRS	Christiane Weber	Christiane.Weber@cnrs.fr	Principal investigator
UMR TETIS - CNRS	Claudia Lavalley	Claudia. Lavalley@cnrs.fr	Publisher