Surface Analysis Using Cloud Computing: An Applied Study on the Google Earth Engine Platform

Abstract

Objectives: This study aims to retrieve a digital elevation model (DEM) and perform surface analyses using Google Earth Engine (GEE) as a free and open-source cloud-based platform. It seeks to highlight the efficiency and capability of GEE in processing and analyzing large-scale spatial data without relying on advanced local computing resources or licensed software. The study also aims to enrich the Arabic scientific literature with research focused on GEE applications.
Methods: A descriptive-analytical approach was applied to Saudi Arabia through surface analyses including hillshade, slope, slope classification (Young, 1997), area and percentage of each class, aspect, and contour lines at 200 m and 500 m intervals, using the open-source SRTM30 DEM via GEE.
Results: Seven maps were produced to represent the surface analyses of the study area, namely: elevation, hillshade, slope, slope classification according to Young (1997), aspect, and contour lines at 200 m and 500 m intervals. These layers underwent basic processing, including tile merging into a unified raster, color gradient adjustment, and final map layout using ArcGIS Pro. A table was also prepared showing the area of each slope class.
Conclusions: The findings confirm that GEE offers a practical alternative to traditional software for performing surface analyses across large geographic extents due to its cloud-based capabilities and access to open data. The post-processing steps were simple and can also be performed efficiently using open-source GIS software such as QGIS, supporting the use of flexible and cost-free tools in spatial research, especially in academic environments with limited resources.