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Forest boundary delineation is one of the key issues of forest management for Swiss National Forest Inventory (NFI). The proposed approach in this paper focuses on the delineation of forest boundaries with special emphasis on spatially contiguous and reproducible results by using both aerial images and LIDAR data. The used Green Vegetation Index (GVI) is(More)
Forest boundary is one of the important parameters in Swiss National Forest Inventory (NFI). It is mainly delineated by aerial photo interpretation according to the defined " Forest/Non-forest decision " rules at each sample plot. However, it is not suitable for local assessment of forest stands with such kind of coarse grid sampling design. This paper(More)
Unsupervised segmentation methods are important to extract boundary features from large forest vegetation databases. Finding optimized segmentation algorithms for images with natural vegetation is crucial because of the computational load and the required reproducibility of results. In this paper, we present an approach how to automatically select optimized(More)
Tree cover is one of the important forest parameters in SWISS National Forest Inventory (NFI). Therefore, automatic tree cover detection is of practical interest. However, it difficult to remover shadow areas because of some effects related to ADS40 data processing of Digital Surface Model (DSM) by NGATE. This paper proposes an automatic and flexible(More)
National Forest Inventories (NFI) are essential for countrywide estimations of a wide range of forest functions. Our research aim is to derive measurable forest features out of airborne image data by using automatic computer-vision based methods. This paper focuses on tree layer detection of high resolution ADS40 data for automation. Preliminary(More)