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 ( Revision )
2022-05-17T19:09:06
Edition
1.0
Edition date
2015-01-01
Identifier
e324c038-08f3-4a11-aca2-7abbeda014e7
Principal investigator
UMR TETIS - CNRS - Christiane Weber

Purpose
Provide with urban trees 3 level nomenclature
Status
Completed
Principal investigator
UMR TETIS - CNRS - Christiane Weber

Maintenance and update frequency
Not planned
General ( Theme )
  • remote sensing
  • VHRS imagery
  • HYPERSPECTRAL imagery
  • urban studies
GEMET - INSPIRE themes, version 1.0 ( Theme )
GEMET - Concepts ( Theme )
GCMD Keywords viewer ( Theme )
TETIS Thesaurus, version 1.0 21112019 ( Theme )
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
Metadata language
en
Character set
UTF8
Topic category
  • Geoscientific information
  • Environment
N
S
E
W
thumbnail


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
  • ESRI Shapefile ( 1.0 )

OnLine resource
geopackage file ( file for download )
OnLine resource
species_27classes ( OGC:WMS )

WMS Service

Hierarchy level
Dataset

Conformance result

Alternate title
This is is some data quality check report
Date ( Publication )
2022-05-17T19:09:06
Explanation
some explanation about the conformance
Pass
Yes

Conformance result

Date ( Publication )
2010-12-08T12:00:00
Explanation
See the referenced specification
Pass
Yes

Conformance result

Date ( Publication )
2008-12-04T12:00:00
Explanation
See the referenced specification
Pass
Yes
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/470202) in terms of averaged overall accuracy (AOA) and averaged kappa index of agreement (AKIA).

gmd:MD_Metadata

File identifier
e324c038-08f3-4a11-aca2-7abbeda014e7 XML
Metadata language
en
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
Point of contact
LETG - Univ Rennes 2 - Thomas Houet

Principal investigator
UMR TETIS - CNRS - Christiane Weber

Publisher
UMR TETIS - CNRS - Claudia Lavalley

Overviews

overview
SVN Toulouse urban Trees classification

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