Image segmentation as basis for object oriented analysis promises high classification accuracy as it also takes structural, textural, contextual and spectral information into account. In this study, vegetation features were extracted on the basis of classification results acquired using the object oriented image analysis and pixel based approaches using fusion of ALOS imagery (PRISM & VNIR) with a spatial resolution of 2.5 m. The main objective of the study is to evaluate the performance of the object oriented image analysis on extracting vegetation features compared to the traditional pixel based classification as an alternative approach for updating the Indonesian topographic map. Beside the accuracy assessment, cost and time assessment was also performed in this study.
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Image segmentation as basis for object oriented analysis promises high classification accuracy as it also takes structural, textural, contextual and spectral information into account. In this study, vegetation features were extracted on the basis of classification results acquired using the object oriented image analysis and pixel based approaches using fusion of ALOS imagery (PRISM & VNIR) with a spatial resolution of 2.5 m. The main objective of the study is to evaluate the performance of the object oriented image analysis on extracting vegetation features compared to the traditional pixel based classification as an alternative approach for updating the Indonesian topographic map. Beside the accuracy assessment, cost and time assessment was also performed in this study.
Lalitya Narieswari is a researcher in GeospatialInformation Agency (BIG) Republic of Indonesia since 2003. Her professional activities are related to GIS and Remote Sensing application for environmental monitoring.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Image segmentation as basis for object oriented analysis promises high classification accuracy as it also takes structural, textural, contextual and spectral information into account. In this study, vegetation features were extracted on the basis of classification results acquired using the object oriented image analysis and pixel based approaches using fusion of ALOS imagery (PRISM & VNIR) with a spatial resolution of 2.5 m. The main objective of the study is to evaluate the performance of the object oriented image analysis on extracting vegetation features compared to the traditional pixel based classification as an alternative approach for updating the Indonesian topographic map. Beside the accuracy assessment, cost and time assessment was also performed in this study. 52 pp. Englisch. N° de réf. du vendeur 9783659300639
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Narieswari LalityaLalitya Narieswari is a researcher in GeospatialInformation Agency (BIG) Republic of Indonesia since 2003. Her professional activities are related to GIS and Remote Sensing application for environmental monitoring. N° de réf. du vendeur 5146849
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Image segmentation as basis for object oriented analysis promises high classification accuracy as it also takes structural, textural, contextual and spectral information into account. In this study, vegetation features were extracted on the basis of classification results acquired using the object oriented image analysis and pixel based approaches using fusion of ALOS imagery (PRISM & VNIR) with a spatial resolution of 2.5 m. The main objective of the study is to evaluate the performance of the object oriented image analysis on extracting vegetation features compared to the traditional pixel based classification as an alternative approach for updating the Indonesian topographic map. Beside the accuracy assessment, cost and time assessment was also performed in this study.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. N° de réf. du vendeur 9783659300639
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Image segmentation as basis for object oriented analysis promises high classification accuracy as it also takes structural, textural, contextual and spectral information into account. In this study, vegetation features were extracted on the basis of classification results acquired using the object oriented image analysis and pixel based approaches using fusion of ALOS imagery (PRISM & VNIR) with a spatial resolution of 2.5 m. The main objective of the study is to evaluate the performance of the object oriented image analysis on extracting vegetation features compared to the traditional pixel based classification as an alternative approach for updating the Indonesian topographic map. Beside the accuracy assessment, cost and time assessment was also performed in this study. N° de réf. du vendeur 9783659300639
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Updating Topographic Map using Remote Sensing Techniques | Comparison of Pixel Based Interpretation and Object Oriented Analysis | Lalitya Narieswari | Taschenbuch | 52 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659300639 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 106163466
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Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
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