Risk Analysis, Vol. 39, No. 1, 2019 DOI: 10.1111/risa.13260 Advances in Spatial Risk Analysis Nikolaos Argyris , 1,* Valentina Ferretti , 2,3 Simon French, 4 Seth Guikema, 5 and Gilberto Montibeller 1 1. INTRODUCTION We live in a 3D world with increasing availability of real-time spatial data, from satellite information, mobile tracking, and autonomous transportation sys- tems, among many other sources. Such availability of data, together with increasingly sophisticated risk and decision analytic frameworks, is enabling more effective support in answering questions such as:  How to plan the growth of cities in a sustainable way?  Where to bury nuclear waste?  Where to increase flood defenses?  What is the likely spatial spread of a disease?  How will airborne or waterborne contamina- tion disperse?  What is the likely impact region of a satellite in a decaying orbit?  How to distribute police on open patrol in a large city?  How to assess the chance of finding a missing aircraft over a wide area? In answering these questions, there is growing recognition that the spatial distribution of many of the factors affecting the risks, costs, and outcomes are heterogeneous (e.g., Keller, Kirkwood, & Simon, 1 School of Business and Economics, Loughborough University, Loughborough, UK. 2 Department of Architecture, Built Environment and Construc- tion Engineering (ABC), Politecnico di Milano, Milano, Italy. 3 Department of Management, London School of Economics and Political Science, London, UK. 4 Department of Statistics, University of Warwick, Coventry, UK. 5 Department of Industrial and Operations Engineering, Univer- sity of Michigan, Ann Arbor, MI, USA. ∗ Address correspondence to Nikolaos Argyris, School of Business and Economics, Loughborough University, Loughborough LE11 3TU, UK; N.Argyris@lboro.ac.uk. 2015; Zagmutt, Schoenbaum, & Hill, 2016; Zhou, Li, Wu, Wu, & Shi, 2014). The rich literature on multicri- teria spatial decision support systems (Malczewski, 2006) has also seen an increasing number of applications involving risk assessment (e.g., Aceves- Quesada, D´ ıaz-Salgado, & L´ opez-Blanco, 2007; Vadrevu, Eaturu, & Badarinath, 2010). In parallel with the analysis of spatial risk, the presentation of spatial and geographical uncertainty has also at- tracted growing attention (MacEachren et al., 2005). The time is thus ripe for having a special issue on Spatial Risk Analysis, which we have edited. The aims of the special issue were to: (i) gather recent theoretical and applied develop- ments in the field; (ii) identify common trends and new directions of research; (iii) provide some coherence to this active field of research. We are delighted that the response to our call for articles has been so positive, with 45 submissions, the highest number of submissions for a special issue in Risk Analysis history. This success confirms the widespread and fast-growing interest on the topic. From the initial set, 17 articles have been accepted after the reviewing process. This collection of articles includes both theoretical and applied studies, which deal with different types of risks (e.g., environmental, industrial, health) and cover differ- ent stages of risk analysis processes. Applications cover risks related to business, biosecurity, biological invasion, civil aviation, climate change vulnerability, contamination, groundwater-induced subsidence, emergency risk analysis, flooding and extreme rain events, power networks, radiation dose assessment, railways, subsidence, and tornados. 1 0272-4332/19/0100-0001$22.00/1 C  2019 Society for Risk Analysis