Key points are not available for this paper at this time.
Abstract In this paper we propose a simple technique for assessing the positional accuracy of digitized linear features. The approach relies on a comparison with a representation of higher accuracy, and estimates the percentage of the total length of the low accuracy representation that is within a specified distance of the high accuracy representation. The approach deals successfully with three deficiencies of other methods: it is statistically based; is relatively insensitive to extreme outliers; and does not require matching of points between representations. It can be implemented using standard functions and a standard scripting language in any raster or vector GIS. We present the results of a test using data from the Digital Chart of the World.
Building similarity graph...
Analyzing shared references across papers
Loading...
Goodchild et al. (Tue,) studied this question.
synapsesocial.com/papers/6a178d2e4f2b3115b012b4a3 — DOI: https://doi.org/10.1080/136588197242419
Michael F. Goodchild
University of California System
Gary J. Hunter
University of California, Santa Barbara
International Journal of Geographical Information Systems
University of California, Santa Barbara
Building similarity graph...
Analyzing shared references across papers
Loading...