Checking the spatial accuracy of class boundaries with a varying range of accuracy requirements

David Bley 1 and Ruedi Haller 2 
1 Swiss National Park (SNP)
Schlossstr. 25, 38871 Ilsenburg, Germany
Tel.: + 49 171 4789890
david_bley@hotmail.com
2 Swiss National Park (SNP)
Casa dal park, 7530 Zernez, , Switzerland
Tel.: +41 81 856 12 82; Fax: +41 81 845 17 40
rhaller@nationalpark.ch

Abstract
This paper presents a method to assess the horizontal accuracy of class boundary location for large scale categorical data for large mountainous and protected areas. The test was performed on a land cover dataset which was created for the Swiss National Park (SNP) with an overall area of 370 km2. The average area of a polygon has been 0.66 ha with a minimal distance between two lines of 5 meters. Therefore a set up of stratified random samples was required because of the lack of sufficient  data with higher accuracy as a reference and restricted access to the area due to conservation policies. Additionally we regarded the assumption that spatial properties in maps are a function of thematic categories and accuracy requirements differ in boundaries  between different classes.  The comparison is based on orthoimages with a well defined spatial quality description. We defined all possible pairs of neighboring habitat classes and classified the required accuracy by a confusion matrix. The accuracy values are based on the guidelines for interpretation. We intersected a regular set of directed transect lines across the data set and obtained a point  dataset of all intersections between transect lines and class boundaries. The intersection point data was buffered according to the varying accuracy between the adjacent habitat types. With an independent manually operated control procedure the accuracy of the line was accepted or rejected by defining the delineation within or outside the buffer. In an area with missing data of higher accuracy or restricted access, the method has shown a simple approach to assess the overall accuracy of categorical data as well as a well distinguished image of the delineation work of different adjacent classes. Moreover, with the design of control points, an overall view over a large area is guaranteed.

Keywords: spatial uncertainty, categorical data, accuracy assessment

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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