analytics

Abstract Geospatial analytics has become an essential tool for decision-making across various sectors, including urban planning, agriculture, environmental monitoring, and disaster management. However, the complexity of geospatial data and the analytical methods used can lead to errors and misinterpretations, resulting in wrong decisions. This paper outlines a comprehensive framework to avoid making incorrect decisions in geospatial analytics by addressing key aspects such as problem definition, data quality, validation, multiple perspectives, expert consultation, and continuous monitoring. By following these best practices, practitioners can enhance the accuracy and reliability of their geospatial analyses and make more informed decisions. Introduction Geospatial analytics involves […]