GEOtiled-SG: A Scalable Framework for High-Resolution Terrain Parameter Computation

GEOtiled enables efficient computation of high-resolution terrain parameters from digital elevation models (DEMs) by decomposing large regions into smaller, parallelizable tiles. Originally developed as GEOtiled-G with support for three parameters (Slope, Aspect, Hillshade) via GDAL, we present GEOtiled-SG, an enhanced version that integrates the SAGA GIS library to compute over 15 parameters, expanding its utility in Earth science. To offset SAGA’s computational overhead, GEOtiled-SG introduces three optimizations: concurrent DEM cropping, buffer-aware mosaicking, and unified concurrency across workflow stages. Evaluations show that GEOtiled-SG maintains GEOtiled-G’s performance on the original parameters and offers consistent speedups across the expanded set. The framework is open source on GitHub, with data hosted on Dataverse, supporting reproducible, scalable terrain analysis.

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Published
2025-09-15
DOI
https://doi.org/10.1109/escience65000.2025.00019
Primary Topic
Remote Sensing and LiDAR Applications
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article
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article

GEOtiled-SG: A Scalable Framework for High-Resolution Terrain Parameter Computation

Rodrigo Vargas, Paula Olaya, Jack Marquez, Michela Taufer et al.
Remote Sensing and LiDAR Applications
article

GEOtiled-SG: A Scalable Framework for High-Resolution Terrain Parameter Computation

Rodrigo Vargas, Paula Olaya, Jack Marquez, Michela Taufer, Ian Lumsden, Gabriel Laboy, Kin Wai N G
article en

Abstract

GEOtiled enables efficient computation of high-resolution terrain parameters from digital elevation models (DEMs) by decomposing large regions into smaller, parallelizable tiles. Originally developed as GEOtiled-G with support for three parameters (Slope, Aspect, Hillshade) via GDAL, we present GEOtiled-SG, an enhanced version that integrates the SAGA GIS library to compute over 15 parameters, expanding its utility in Earth science. To offset SAGA’s computational overhead, GEOtiled-SG introduces three optimizations: concurrent DEM cropping, buffer-aware mosaicking, and unified concurrency across workflow stages. Evaluations show that GEOtiled-SG maintains GEOtiled-G’s performance on the original parameters and offers consistent speedups across the expanded set. The framework is open source on GitHub, with data hosted on Dataverse, supporting reproducible, scalable terrain analysis.

Knoxville College (US), IBM Research - Thomas J. Watson Research Center (US), Arizona State University (US), University of Tennessee at Knoxville (US)
Openalex Percentile: Top 75%
Remote Sensing and LiDAR Applications
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GEOtiled-SG: A Scalable Framework for High-Resolution Terrain Parameter Computation — Rodrigo Vargas, Paula Olaya, et al. · (2025) | TGRS Research Map | TGRS