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.
"synopsis" may belong to another edition of this title.
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.
"About this title" may belong to another edition of this title.
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 64 pp. Englisch. Seller Inventory # 9783659246999
Seller: moluna, Greven, Germany
Condition: 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 Geospatial Information Agency (BIG) Republic of Indonesia since 2003. Her professional activities are related to GIS and Remote Sensing application for environmental monitoring. Seller Inventory # 5142800
Quantity: Over 20 available
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock. Seller Inventory # 3659246999
Quantity: 1 available
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Seller Inventory # 9783659246999
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9783659246999
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Extracting Nature Areas Using Object Oriented Analysis | Remote Sensing for Environmental Monitoring | Lalitya Narieswari | Taschenbuch | 64 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659246999 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 106209065