**Preface to "Spatial Big Data, BIM and advanced GIS for Smart Transformation: City, Infrastructure and Construction"**

Shirowzhan et al. [1] discuss the value of digital twin and cybergis in improving connectivity and measuring the impact of infrastructure construction planning in smart cities. This chapter discusses selective technologies that can potentially contribute to developing an intelligent environment and smarter cities. Although the connectivity and efficiency of smart cities is important, the analysis of the impact of construction development and large projects in the city is crucial to decision and policy makers before the project is approved. This chapter refers to the need for advanced tools such as mobile scanners, geospatial artificial intelligence, unmanned aerial vehicles, geospatial augmented reality apps, light detection, and ranging in smart cities. In line with smart city technology development, this book includes 10 chapters covering trending topics, which are briefly mentioned in this preface.

Mendoza-Silva et al. [2] present a simulator for improving smart parking practices by modelling drivers with activity plans. This experimental study offers a parking occupancy simulator to support a smart system for managing parking. This paper is critical for use in extending smart city practices, as it shows how the process of developing a simulator assists in smart parking development from design to implementation.

Gu et al. [3] propose a bike optimization algorithm to increase the efficiency of bike stations and the sharing system in Shenzhen, China. Station-free bike sharing systems were recently introduced in China in line with smart city practices. They propose an optimization algorithm to match bike offers and rides.

Wu et al. [4] used an agent-based model simulation of human mobility with the use of mobile phone datasets and spatial big data analysis. They identified individual travel in urban areas and simulated commuting behaviors of residents using an agent-based model.

Rupi et al. [5] describe the use of numerical methods to match the network demand and supply of bicycles. This is a useful study for the improvement of city infrastructure using spatial data sets.

Li et al. [6] investigated the distribution of railways in China using indicators such as network density, proximity, travel time, train frequency, population, and gross domestic product (GDP). They then evaluated China's railway network distribution using geographic information system (GIS).

Dong et al. [7] present a novel algorithm of direction-aware continuous moving K-nearest neighbor queries in road networks. They show how object azimuth information can be used to determine the moving direction toward the query object.

Wang et al. [8] propose a hybrid framework for the high-performance modelling of 3D pipe networks. Three-dimensional modelling is a trending topic in smart city literature [9]. They explain how instantiation technology significantly improves the rendering performance of the 3D pipe networks.

Han et al. [9] present an efficient staged evacuation planning algorithm for multi-exit buildings. This algorithm can be tested using advanced big data simulations and virtual reality technologies.
