Updating Topographic Map using Remote Sensing Techniques - Narieswari, Lalitya
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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…mehr

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Produktbeschreibung
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.
Autorenporträt
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.