Geomorphology plays a fundamental role in understanding the interactions between humans and nature, both in urban and rural environments. To conduct environmental studies, it is essential to perform geomorphological mapping, which requires the compartmentalization of the main geomorphological units. In this context, the present research employed digital image processing, geoprocessing, and image analysis to map the slope units proposed by (Dalrymple et al. in An hypothetical nine-unit landsurface model. Z. Geomorphol, Berlin, Stuttgart, 1968), compartmentalizing the region of Feira de Santana, Bahia, Brazil. The materials and methods used consisted of open-source software, namely Spring 4.6. The processing of Shuttle Radar Topography Mission (SRTM) images required converting the digital elevation model into an 8-bit grayscale image (256 levels of gray), where lower values correspond to valley bottoms and lakes, and higher values represent the tops of slopes. Subsequently, filtering, segmentation, and unsupervised classification (Isoseg algorithm) were applied. The processing results were promising, revealing eight distinct geomorphological units, including interfluves, infiltration slopes, convex slopes with creep, intermediate transport slopes, colluvial slopes, alluvial slopes, stream margins, and streambeds. These units represent different morphogenetic processes, such as mechanical eluviation, terrace formation, action of surface and subsurface waters, erosion and land-slides, fluvial corrosion, and material transport. This study contributes to the geomorphological knowledge of the Feira de Santana region, providing important information for urban and rural planning, sustainable land use, and environmental management. Furthermore, applying of remote sensing techniques and geoprocessing has proven an efficient and accessible approach for conducting geomorphological mapping in extensive areas. The detailed analysis of geomorphological units and their processes can help better understand environmental dynamics and support strategic decisions for the sustainable development of the region. However, it is important to emphasize that future research can enhance the accuracy and representativeness of the mapping by including other variables and analysis techniques.