Analysis of methods used to validate remote sensing and GIS-based groundwater potential maps in the last two decades: A review

George Bennett
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Abstract

The 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 maps.

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过去二十年来用于验证遥感和基于gis的地下水潜力图的方法分析:综述
遥感数据、机器学习和地理信息系统在管理和分析空间数据方面的整合有助于生成显示地下水潜力的地图。这些地图是帮助地下水资源利益相关者和决策者在地下水开发和管理过程中做出明智决策的重要工具;为了确保这些地图的可靠性,与现场数据进行了验证。这项研究分析了2002年至2023年期间的125篇科学论文。结果表明,约85%的文章包含经过验证的地图,这表明相当多的研究人员坚持用实地数据验证基于遥感和gis的地图,这在科学研究中至关重要。但是,15%的文章包含未经验证的地图。这是一个令人担忧的数字;因此,期刊应严格确保验证得到遵守。在回顾的文章中,总共使用了10种方法来验证地下水潜力图,这些方法使用了各种参数,如井产量、井/泉流量、含水层透射率、井比容和井/泉的存在。这项研究还将增加选择适当方法验证遥感和基于地理信息系统的地下水潜力图的知识。使用反映含水层生产力的实地数据更适合于验证地下水潜力图。
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