Geotechnical maps are essential tools for urban planning and for the design of foundations and infrastructure, because they show soil properties, groundwater conditions and ground hazards at a site. Traditional methods rely on exploratory boreholes and field surveys. These are accurate but costly and slow, and they cover only limited points, especially in rapidly expanding cities. Combining remote sensing with geographic information systems (GIS) has therefore become a practical option for covering large areas at lower cost. Remote sensing relies on satellite imagery from missions such as Landsat and Sentinel-2, synthetic aperture radar (SAR), light detection and ranging (LiDAR), and unmanned aerial vehicle (UAV) photogrammetry. From these, digital elevation models (DEMs) and maps of slope and surface drainage are derived, and spectral indices such as NDVI and NDBI are calculated to distinguish vegetation from built-up areas. Interferometric SAR (InSAR) also makes it possible to measure land subsidence with millimetre-level precision. GIS then combines these layers with borehole data and laboratory test results to build a unified spatial database. Spatial interpolation methods such as IDW and Kriging are used to estimate soil properties between borehole locations, and multi-criteria analysis is applied to divide the city into zones according to soil bearing capacity and groundwater level. This system produces maps of several geotechnical hazards, including expansive soils, liquefaction, landslides, urban flooding and land subsidence. These maps help planners and engineers choose project sites and foundation types early, and prioritise the maintenance of existing networks and structures. These techniques nevertheless have limits. Images provide information only about the surface and the near-surface, and they do not replace the boreholes and laboratory tests needed for detailed design. The accuracy of the results also depends on image resolution and surface cover, so calibration and field verification (ground truthing) are required. In conclusion, combining remote sensing and GIS with field data gives a comprehensive and up-to-date picture of ground conditions in cities, and supports safe and economical planning and design decisions. Presented by Assistant Lecturer Saif Salam Saoud Department of Civil Engineering Source: Lillesand, T.M., Kiefer, R.W. & Chipman, J.W. Remote Sensing and Image Interpretation, 7th ed., Wiley, 2015.