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.

The GEOtiled framework facilitates the scalable and efficient computation of high-resolution terrain parameters using Digital Elevation Models (DEMs) across the Continental United States (CONUS). These parameters are essential in Earth Science applications. This paper presents significant advances to optimizing GEOtiled's performance. In GEOtiled 2.0, we introduce three key optimizations to speed up GEOtiled's overall runtime: concurrent cropping, efficient mosaic operation, and unified parallel processing. These optimizations improve data distribution and handling, reducing computation times while maintaining accuracy. We evaluate performance using DEM data at 30-meter resolution over a region covering the state of Tennessee. Our results demonstrate that the optimized framework provides substantial performance improvements for generating terrain parameters. GEOtiled 2.0 software, openly available on GitHub, advances reproducible, data-driven scientific discovery in Earth Science.