A so-called non-intervention management scheme has been adopted in a large part of the nature areas. This means that natural processes like storm, grazing, climate, succession and diseases are allowed to occur and become a dominant factor that changes the structure and ecosystem in the area. There is a need to monitor how the applied management influences the environment and the habitat of the nature area. This study focuses on developing an approach to extract the different types of land cover which characterize the nature areas in the study area based on object oriented analysis using aerial photographs. Three subset areas were chosen and considered as representative areas. The study aimed to create a rule set transferable to other datasets to enable automatic monitoring. Using Definiens Developer, segmentation and classification were undertaken at 2 levels to create a hierarchical image object. The validation was assessed by comparing the result of the computer-based segmentation with a reference segmentation generated by visual interpretation.
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A so-called non-intervention management scheme has been adopted in a large part of the nature areas. This means that natural processes like storm, grazing, climate, succession and diseases are allowed to occur and become a dominant factor that changes the structure and ecosystem in the area. There is a need to monitor how the applied management influences the environment and the habitat of the nature area. This study focuses on developing an approach to extract the different types of land cover which characterize the nature areas in the study area based on object oriented analysis using aerial photographs. Three subset areas were chosen and considered as representative areas. The study aimed to create a rule set transferable to other datasets to enable automatic monitoring. Using Definiens Developer, segmentation and classification were undertaken at 2 levels to create a hierarchical image object. The validation was assessed by comparing the result of the computer-based segmentation with a reference segmentation generated by visual interpretation.
Lalitya Narieswari is a researcher in Geospatial Information 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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Taschenbuch. Zustand: Neu. Neuware -A so-called non-intervention management scheme has been adopted in a large part of the nature areas. This means that natural processes like storm, grazing, climate, succession and diseases are allowed to occur and become a dominant factor that changes the structure and ecosystem in the area. There is a need to monitor how the applied management influences the environment and the habitat of the nature area. This study focuses on developing an approach to extract the different types of land cover which characterize the nature areas in the study area based on object oriented analysis using aerial photographs. Three subset areas were chosen and considered as representative areas. The study aimed to create a rule set transferable to other datasets to enable automatic monitoring. Using Definiens Developer, segmentation and classification were undertaken at 2 levels to create a hierarchical image object. The validation was assessed by comparing the result of the computer-based segmentation with a reference segmentation generated by visual interpretation.Books on Demand GmbH, Überseering 33, 22297 Hamburg 64 pp. Englisch. Artikel-Nr. 9783659246999
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Paperback. Zustand: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock. Artikel-Nr. 3659246999
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