Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Topological generalization of continuous valued raster data

Corcoran, Padraig ORCID: https://orcid.org/0000-0001-9731-3385 2019. Topological generalization of continuous valued raster data. Presented at: ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Chicago, Illinois, USA, 5-8 November 2019. Proceedings of ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. ACM, -.

[thumbnail of ACM_SIGSPATIAL_short_Corcoran.pdf]
Preview
PDF - Published Version
Download (875kB) | Preview

Abstract

We propose a novel method for generalizing continuous valued raster data with respect to topological constraints whereby smaller scale connected components and holes in the data sublevel sets are removed. The proposed method formulates the problem of generalization as an optimization problem with respect to persistent homology. We prove the objective function to be locally continuous with analytical gradients which can be used to perform optimization using gradient descent. Furthermore, we prove the convergence of gradient descent to a global optimal solution. The proposed method is general in nature and can be applied to raster data of any dimension. The utility of the method is demonstrated with respect to generalizing two- and three-dimensional raster data corresponding to digital elevation models (DEM) and subsurface mineral interpolation respectively.

Item Type: Conference or Workshop Item (Paper)
Status: In Press
Schools: Computer Science & Informatics
Publisher: ACM
Date of First Compliant Deposit: 30 October 2019
Date of Acceptance: 22 August 2019
Last Modified: 26 Oct 2022 07:54
URI: https://orca.cardiff.ac.uk/id/eprint/126133

Citation Data

Cited 1 time in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics