Potentialités de l’imagerie satellitaire Spot 5 pour la cartographie de la végétation terrestre

The aim of this study is to test the Spot 5 satellite imagery for the cartography of terrestrial vegetation in the prospect of a monitoring of coastal zones. Two methods are used. The first method is based on a photointerpretation of a 2.5 meters multipectral image with the european EUNIS habitat cl...

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Main Authors: Françoise Gourmelon, Frédéric Bioret, Laure Sauve
Format: Article
Language:deu
Published: Unité Mixte de Recherche 8504 Géographie-cités 2005-11-01
Series:Cybergeo
Subjects:
Online Access:https://journals.openedition.org/cybergeo/3027
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author Françoise Gourmelon
Frédéric Bioret
Laure Sauve
author_facet Françoise Gourmelon
Frédéric Bioret
Laure Sauve
author_sort Françoise Gourmelon
collection DOAJ
description The aim of this study is to test the Spot 5 satellite imagery for the cartography of terrestrial vegetation in the prospect of a monitoring of coastal zones. Two methods are used. The first method is based on a photointerpretation of a 2.5 meters multipectral image with the european EUNIS habitat classification. A comparison with aerial orthoimages is realised. The results show that Spot 5 satellite imagery is quite suitable for vegetation mapping at a local scale. The majority of the habitats are identified with very few exceptions (patchy habitat of particular texture and of small size). The second method is based on the updating of existing data through the classification of the 10 meters multispectral image into a GIS. This process implies the development of a dynamic vegetation model. A map is produced in a short delay. It may be useful for the large-scale monitoring of dynamic vegetation processes.
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spelling doaj.art-d2acc23387454d7fb455906357a0d34a2024-04-04T09:33:40ZdeuUnité Mixte de Recherche 8504 Géographie-citésCybergeo1278-33662005-11-0110.4000/cybergeo.3027Potentialités de l’imagerie satellitaire Spot 5 pour la cartographie de la végétation terrestreFrançoise GourmelonFrédéric BioretLaure SauveThe aim of this study is to test the Spot 5 satellite imagery for the cartography of terrestrial vegetation in the prospect of a monitoring of coastal zones. Two methods are used. The first method is based on a photointerpretation of a 2.5 meters multipectral image with the european EUNIS habitat classification. A comparison with aerial orthoimages is realised. The results show that Spot 5 satellite imagery is quite suitable for vegetation mapping at a local scale. The majority of the habitats are identified with very few exceptions (patchy habitat of particular texture and of small size). The second method is based on the updating of existing data through the classification of the 10 meters multispectral image into a GIS. This process implies the development of a dynamic vegetation model. A map is produced in a short delay. It may be useful for the large-scale monitoring of dynamic vegetation processes.https://journals.openedition.org/cybergeo/3027photointerpretationmappingclassificationvegetationSpot satellite imageUshant Island
spellingShingle Françoise Gourmelon
Frédéric Bioret
Laure Sauve
Potentialités de l’imagerie satellitaire Spot 5 pour la cartographie de la végétation terrestre
Cybergeo
photointerpretation
mapping
classification
vegetation
Spot satellite image
Ushant Island
title Potentialités de l’imagerie satellitaire Spot 5 pour la cartographie de la végétation terrestre
title_full Potentialités de l’imagerie satellitaire Spot 5 pour la cartographie de la végétation terrestre
title_fullStr Potentialités de l’imagerie satellitaire Spot 5 pour la cartographie de la végétation terrestre
title_full_unstemmed Potentialités de l’imagerie satellitaire Spot 5 pour la cartographie de la végétation terrestre
title_short Potentialités de l’imagerie satellitaire Spot 5 pour la cartographie de la végétation terrestre
title_sort potentialites de l imagerie satellitaire spot 5 pour la cartographie de la vegetation terrestre
topic photointerpretation
mapping
classification
vegetation
Spot satellite image
Ushant Island
url https://journals.openedition.org/cybergeo/3027
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