AI-Enabled Spatial Intelligence: Revolutionizing Data Management and Decision Making in Geographic Information Systems

Introduction

Geographical information is collected in a wide variety of formats and through various sources. Geographic Information Systems (GIS) is a software programme used in the management, analysis, and visualization of geographical data (Esri, 2023). GIS began to take shape between the 1960s and 1970s as computer technology and advancements in spatial data processing capabilities became more prevalent. The “Father of GIS,” Roger Tomlinson, made significant contributions to this discipline. Tomlinson took the lead in the development of the Canada Geographic Information System during the early 1960s, which served as a cornerstone for the evolution of modern GIS. Originally, this system was created to manage and analyze resource data efficiently, specifically for rural land-use planning (Coppock & Rhind, 1991; Goodchild, 2018).

To give us a better knowledge of the world around us, GIS integrates geographic data (information about places on the surface of the earth) with other types of data (F. Wang & Luo, 2005) to acquire a better understanding of patterns and correlations that are not readily discernible in conventional numerical data. Information can be used to extend our knowledge, enhance our wisdom and reduce our uncertainty (Stillwell et al., 1999). GIS technology is a useful information system used for accurately mapping areas and locations, making it easier for people to access information about the distribution of public services and navigate their way to specific sites (Kurniadi et al., 2019). GIS system provides spatial data captured with the help of various tools and techniques for the analysis of particular situations. It has been widely used as a method for effective, efficient, and robust decision-making in the business world (Ihalauw & Tandafatu, 2021). Spatial data mining techniques are used collectively with GIS and satellite imagery in various fields (Ouchra et al., 2022). The geographic information system is designed to generate maps, manage spatial datasets, perform sophisticated “what if” spatial analyses, visualize multiple spatial datasets simultaneously, and solve location-based queries (Afgun Usmani et al., 2020). Geographic analysis in GIS facilitates the study of various processes by developing and applying suitable models (Reddy, 2018). Figure 1 illustrates a GIS model involves of five thematic layers.

Figure 1.

GIS model

Source: ESRI (2002)

GIS is used in different areas for research. GIS finds applications in multiple fields such as urban planning, environmental management, disaster response, and transportation, to name a few. It is used in the analysis of traffic monitoring, tourist monitoring, health management, and biodiversity conservation (Perumal et al., 2015). It is a highly technologically effective tool for analyzing large amounts of geographic information and making difficult decisions in the modern world (Ostroukh et al., 2020). GIS can play significant roles in both marketing planning and the decision-making process (Turk et al., 2014). The GIS-based business decision system serves for business management and decision-making (Ren et al., 2010). GIS can be used as a decision support system to help the managers of public health (Mesgari & Masoomi, 2018). GIS assists decision-makers in comprehending, analyzing, and interpreting intricate spatial data to make informed decisions in these domains. Nonetheless, GIS poses some obstacles in data management and decision-making that might constrain its efficacy in several domains. GIS poses a challenge when it comes to managing spatial data due to the difficulty in acquiring and maintaining accurate and real-time data. In addition, conventional GIS workflows are insufficient for handling vast amounts of spatial data. To overcome these challenges, new technologies such as artificial intelligence (AI) have been implemented to facilitate more effective, efficient, and precise data management and decision-making processes in GIS.