Abstract
Abstract. The acquisition of 3D point data with the use of both aerial laser scanning (ALS) and matching of aerial stereo images coupled with advances in image processing algorithms in the past years provide opportunities to map land cover types with better precision than before. The present study applies Object-Based Image Analysis (OBIA) to 3D point cloud data obtained from matching of stereo aerial images together with spectral data to map land cover types of the Nord-Trøndelag county of Norway. The multi-resolution segmentation algorithm of the Definiens eCognition™ software is used to segment the scenes into homogenous objects. The objects are then classified into different land cover types using rules created based on the definitions given for each land cover type by the Norwegian Forest and Landscape Institute. The quality of the land cover map was evaluated using data collected in the field as part of the Norwegian National Forest Inventory. The results show that the classification has an overall accuracy of about 80% and a kappa index of about 0.65. OBIA is found to be a suitable method for utilizing 3D remote sensing data for land cover mapping in an effort to replace manual delineation methods.
Highlights
The Norwegian Forest and Landscape Institute (NFLI) produces areal resource maps with different qualities
It is observed that careful selection of the set of features used for the segmentation and the conceptualization scale is the key step in obtaining meaningful segmentation results
The open areas are split into two classes since this is required by the NFLI they are lumped together in the existing AR5 map
Summary
The Norwegian Forest and Landscape Institute (NFLI) produces areal resource maps with different qualities (scale and thematic details) One of such maps is the AR5 which is a land cover/use map at the scale of 1:5000. This map contains four levels of thematic information, namely: (1) the land use/cover type, (2) the dominant tree species types in forested areas (i.e. forest, grasslands and wetlands), (3) the site index which is the description of the site’s productivity with respect to forest products, mainly timber, and (4) the ground condition which describes the geological and soil condition of the site These maps are produced through intensive field works with the help of analogue aerial photographs until recently when manual digitization of digital orthophotos took over. Technological developments in the areas of remote sensing and GIS in the past years and decades have created the tools and means of acquiring this information effectively creating the opportunity to take land cover mapping to a new stage
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