Geospatial Big Data and the Built Environment: Applications in Urban Planning and Infrastructure Management

Abstract

The exponential growth of geospatial big data stemming from a plethora of sources, including smartphones, sensors, and satellite imagery, has ushered in a new era of opportunities and challenges for the fields of urban planning and infrastructure management. This paper offers a comprehensive review of the applications of geospatial big data in these domains, shedding light on the myriad ways it has redefined urban analytics. Notably, it delves into the transformational potential of geospatial big data in optimizing land use, enhancing transportation systems, and streamlining resource allocation within urban landscapes. Furthermore, it scrutinizes the employment of data mining techniques to harness valuable insights from the wealth of citizen-generated geospatial data, illuminating the path toward more informed urban development. Despite the evident promise, this paper does not shy away from addressing the formidable challenges that accompany the adoption of geospatial big data in built environment disciplines. Issues concerning data quality, privacy, efficient storage, and the development of requisite analytical capabilities are all thoroughly examined, providing a holistic view of the landscape. In summation, geospatial big data emerges as a cornerstone for evidence-based decision-making in the realm of smart urban development. However, its successful implementation necessitates a strategic approach to data governance and a concerted effort to foster the analytical skills of professionals in the built environment, equipping them with the expertise required to navigate this dynamic and data-rich terrain.