Spatial Data Science introduces fundamental aspects of spatial data that every data scientist
should know before they start working with spatial data. These aspects include how …

In this paper, I give a personal view on the development of the field of spatial econometrics
during the past 30 years. I argue that it has moved from the margins to the mainstream of …

This study investigates the determinants of Internet access and its effect on educational
inequality in OECD countries during the period of the Covid-19 pandemic. The spatial panel …

Challenged by climate change and severe damage of the ecological environment caused by
carbon emissions, the process of green transformation in the world has to be urgently …

This paper applies spatial econometrics in relation to hedonic house price modeling. Some
basic spatial model alternatives are used for a battery of relevant tests. Geographically …

Spatial Econometrics provides a modern, powerful and flexible skillset to early career
researchers interested in entering this rapidly expanding discipline. It articulates the …

Many methods can be used to construct geographical cellular automata (CA) models of
urban land use, but most do not adequately capture spatial heterogeneity in urban …

This article provides an empirical assessment of the growth experiences of European
regions, during the period 1991–2004, by taking into account the spatial effects due to both …

This study proposes a general nesting spatiotemporal (GNST) model in an effort to improve
the accuracy of tourism demand forecasts. The proposed GNST model extends the general …

Neighbouring economies are likely to influence one another. The concentration of farming
activities referred to as an 'agro-cluster'generates opportunities for income and employment …