Document Type

Article - Open Access

Publication Title

SIGSPATIAL Special

Publisher

Association for Computing Machinery

Publication Date

3-2009

Abstract/ Summary

We present an error metric based on the potential energy of water flow to evaluate the quality of lossy terrain simplification algorithms. Typically, terrain compression algorithms seek to minimize RMS (root mean square) and maximum error. These metrics fail to capture whether a reconstructed terrain preserves the drainage network. A quantitative measurement of how accurately a drainage network captures the hydrology is important for determining the effectiveness of a terrain simplification technique. Having a measurement for testing and comparing different models has the potential to be widely used in numerous applications (flood prevention, erosion measurement, pollutant propagation, etc). In this paper, we transfer the drainage network computed on reconstructed geometry onto the original uncompressed terrain and use our error metric to measure the level of error created by the simplification. We also present a novel terrain simplification algorithm based on the compression of hydrology features. This method and other terrain compression schemes are then compared using our new metric.

Publisher Statement

Green Open Access Otherwise known as "Self-Archiving" or "Posting Rights", all ACM published authors retain the right to post the pre-submitted (also known as "pre-prints"), submitted, accepted, and peer-reviewed versions of their work in any and all of the following sites: Author's Homepage Author's Institutional Repository Any Repository legally mandated by the agency or funder funding the research on which the work is based Any Non-Commercial Repository or Aggregation that does not duplicate ACM tables of contents. Non-Commercial Repositories are defined as Repositories owned by non-profit organizations that do not charge a fee to access deposited articles and that do not sell advertising or otherwise profit from serving scholarly articles

Share

COinS