Mapping Ghana by GMT and R scripting: advanced cartographic approaches to visualize correlations between the topography, climate and environmental setting

The applications of the machine learning and programming approaches in cartography has been increasing in recent years. This paper presents a case study of the scripting techniques used for cartographic mapping using Generic Mapping Tools (GMT) and R language (raster and tmaps packages). The aim of the study is environmental mapping of Ghana. The materials include high-resolution raster grids: topography by the General Bathymetric Chart of the Oceans (GEBCO), climate and environmental datasets (TerraClimate) and Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) for geomorphometric analysis (slope, aspect, hillshade and elevations). The methodology includes code snippets commented and explained with details of scripts. It is argued that using consolebased scripting tools for mapping is effective for cartographic workflow due to the logical structure and repeatability of scripts. The results include eight new thematic maps of Ghana performed using scripting approach inGMTscripting toolset and R language for quantitative and qualitative environmental assessment. Maps show correlations between the landforms of Ghana and certain environmental variables (drought index and soil moisture) showing the effects of the topographic relief on the distribution of the continuous geographic fields. These varied in several geographically distinct regions of Ghana: Ashanti (Kumasi), Volta, Savannah, coastal and northern regions. Demonstrated maps show that scripting method works effectively on a wide range of geosciences including environmental, topographic and climate studies. In such a way, this paper contributes both to the regional studies of Ghana and development of cartographic techniques.