This chapter outlines the frameworks and techniques used to map, analyse, and interpret the Martian surface through remote sensing and geospatial science. It describes the development of Mars’ coordinate system, including the definition of latitude and longitude anchored to features, and explains how various map projections balance distortions when representing a spherical planet on flat surfaces. The importance of accurate reference models, particularly the Martian ellipsoid and elevation datums derived from MOLA data, is emphasised for georeferencing and spatial consistency. Data processing pipelines from raw outputs to higher-level products and processing techniques for accurate spatial alignment are discussed. It highlights the generation and application of high-resolution elevation models from LiDAR and stereo imagery, and the integration of diverse datasets within Geographic Information Systems (GIS) for tasks such as landing site selection, terrain analysis, and change detection. Finally, it explores the growing role of artificial intelligence and machine learning in automating feature detection, improving data analysis efficiency, and enabling autonomous decision-making for Mars missions, underscoring their importance in advancing planetary exploration.