Detection of terrain feature points from digital elevation models using contour context

Abstract

Terrain feature points, such as peaks, pits, and saddles, represent the macro-structure of the landform. Conventional techniques for extracting these points from digital elevation models (DEMs) often grapple with issues of inaccuracy, omission and redundancy, largely due to the problematic necessity of setting threshold values. This paper proposes an innovative approach for the automatic detection of terrain feature points based on the topological relationships of contours and the inherent constraints of terrain shape characteristics. The study provides a robust mathematical model of terrain feature points and an effective algorithm for their extraction. Comparing with manually reference data, the accuracy metrics including completeness, correctness, and quality of our extracted results demonstrate a high level, significantly surpassing those obtained through existing algorithms. This proposed approach not only avoids the spurious feature points produced by the local window method, but also prevents the omission of valid points and the creation of redundant ones. Moreover, by utilizing the contour interval as its only variable, our approach eliminates the need for various threshold settings, streamlining the extraction process.