[wptabs style] [wptabtitle]Abstract[/wptabtitle] [wptabcontent] The main aim of this paper is to analyse the spatial dynamic of public hospital beds in Romania (1992-2018) in order to grasp the potentially uneven development of the health care infrastructure following state policies of …
[wptabs style] [wptabtitle]Abstract[/wptabtitle] [wptabcontent] The article presents the structural changes that occurred in the territorial distribution of health and wellness related accommodation units between 2012 and 2017 in Ukraine. It attempts to analyse a specific category of accommodation units as …
Social scientists investigating how context varies by geographical location and/or how macro-level phenomenon affects individual outcomes often make use of U.S. Census Bureau Public Use Microdata Sample (PUMS) files where micro-units can only be geographically located to Public Use Microdata Area (PUMA) polygons. Most spatial analysis investigations with PUMAs ignore the fact that many of them are multipart polygons—spatially separated polygons that share the same attribute and are stored as a single feature in a vector file. We briefly discuss the theoretical premises of how geo-graphical boundaries are created for macro units and investigate the quantity, degree, and location of PUMA fragmenta-tion. We argue that the basic contiguity principle (the assumption that spatial analysis uses polygon centroids for solid and contiguous geographic units) in spatial dependence analysis is being violated with many PUMAs in the U.S. mainland—where Texas, California, Tennessee, and Illinois merit special attention. Future research should outline a method for handling multipart polygons in spatial and hierarchical analyses.