Bennett, G.2024-08-172024-08-172024Bennett, G. (2023). Analysis of methods used to validate remote sensing and GIS-based groundwater potential maps in the last two decades: A review. Geosystems and Geoenvironment, 100245.https://doi.org/10.1016/j.geogeo.2023.100245https://repository.udom.ac.tz/handle/20.500.12661/4703Full text article also available at: https://doi.org/10.1016/j.geogeo.2023.100245The integration of remote sensing data, machine learning and geographic information system in managing and analysing spatial data helps in generating maps showing groundwater potential. These maps are important tools for aiding stakeholders and decision-makers in groundwater resources to make informed decisions during groundwater development and management; to ensure the reliability of these maps, validation with the field data is conducted. This study analysed 125 scientific articles spanning the period from 2002 to 2023. The results show that around 85% of articles contain validated maps, indicating a significant number of researchers adhere to validate the remote sensing and GIS-based maps with field data, which is crucial in scientific research. However, 15% of articles contain non-validated maps. This is an alarming figure; therefore, journals should be strict in ensuring that validation is adhered to. In the reviewed articles, a total of 10 methods were used to validate groundwater potential maps using various parameters such as well yield, well/spring discharge rate, aquifer transmissivity, well specific capacity, and presence of wells/springs. This study will also add to the knowledge of selecting appropriate methods for validating remote sensing and GIS-based groundwater potential maps. The use of field data reflecting aquifer productivity is more appropriate for validation of groundwater potential mapsenValidation of GIS-based mapsGroundwater potential mapRemote sensing and GISAnalysis of methods used to validate remote sensing and GIS-based groundwater potential maps in the last two decades: A reviewjournal-article10.1016/j.geogeo.2023.100245