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We discuss the nature of processes relating to human behaviour and how to model such processes when they vary over space. In so doing, we describe the role of local modelling and how the bandwidth parameter, a component of multiscale geographically weighted regression, can inform on the spatial scale over which processes are relatively constant. To do this, we translate properties of spatial data, such as heterogeneity and spatial dependency into the realm of spatial processes. We argue that the modelling of spatially varying processes has important ramifications for how we see the world.

We employ a Multiscale Geographically Weighted Regression (MGWR) model to examine the spatial variation of researchers in China in 2015 and its determinants. It is found that the distribution of researchers is driven by the economy in urban centers, public services, natural areas of recreation, urban consumption, and work‐related facilities. Results from the MGWR model conclusively identify significant spatial non‐stationarity in the determinants measuring scientific researchers' distribution. Other factors such as per capita GDP, the number of hospital beds per 10,000 inhabitants, and public financial expenditures influence the distribution of researchers more in the Western cities, and their effect decreases steadily from West to East. Air pollutants affect researchers negatively in the eastern part of the country, while the percentage of available green land is a strong driver in the central and western parts. The factor measuring the effect of the number of universities is seen to affect researchers more strongly in the northwestern and northeastern cities. Other findings further suggest that the economy and public services in cities have a consistent effect on the distribution of researchers across the country whereas, natural areas of recreation, work‐related facilities, and urban consumption have a significantly varying effect across cities.

Scale is a central concept in the geographical sciences and is an intrinsic property of many spatial systems. It also serves as an essential thread in the fabric of many other physical and social sciences, which has contributed to the use of different terminology for similar manifestations of what we refer to as ‘scale’, leading to a surprising amount of diversity around this fundamental concept and its various ‘multiscale’ extensions. To address this, we review common abstractions about spatial scale and how they are employed in quantitative research. We also explore areas where the conceptualizations of multiple spatial scales can be differentiated. This is achieved by first bridging terminology and concepts, and then conducting a scoping review of the topic. A typology for spatial scale is discussed that can be used to categorize its multifarious meanings and measures. This typology is then used to distinguish what we term ‘process scale,’ from other types of spatial scale and to highlight current trends in uncovering aspects of process scale. We end with suggestions on how to further build knowledge regarding spatial processes through the lens of spatial scale.