Search

The novel coronavirus (COVID-19) pandemic is a public health emergency of international concern that caused disaster consequences all over the world. To mitigate and manage the pandemic, geographical information systems (GIS)-based spatial analysis has been used in a key role. To this aim, many GIS-based maps are produced by many national and international institutions. However, the produced maps are prepared by conventional methods and the features in these maps representing by their areal size. This paper proposes the diffusion-based cartograms for visualization of the COVID-19 outbreak. In the study, daily country-level data of the first 150 days of the COVID-19 outbreak were obtained from WHO, and the spread and spatial patterns of the epidemic were presented according to the number of confirmed cases and deaths. As a result of the study, it was observed that the cartogram is a powerful visualization tool and superior to the classical methods. [ABSTRACT FROM AUTHOR]

This paper examines the spatial patterns of non-work activities for 34 drivers in the Southeast Michigan region. Capitalizing upon a unique global positioning systems (GPS) dataset and GIS visualization techniques, this study quantifies the spatial distributions of non-work activities for drivers with different commuting distances, and for non-work activities that are chained in different types of travel (commute travel vs. non-commute travel). We find a strong dependence of non-work activity locations on commuting distances, and an influence of commuting routes on non-work activities chained in all types of travel. The results underline the importance of commuting routes in shaping the spatial configuration of non-work activities. [ABSTRACT FROM AUTHOR]

Multicriteria analysis is a set of mathematical tools and methods allowing the comparison of different alternatives according to many criteria, often conflicting, to guide the decision maker towards a judicious choice. Multicriteria methods are used in spatial context to evaluate and compare spatial decision alternatives, often modeled through constraint-based suitability analysis and represented by point, line, and polygon features or their combination, and evaluated on several space-related criteria, to select a restricted subset for implementation. Outranking methods, a family of multicriteria methods, may be useful in spatial decision problems, especially when ordinal evaluation criteria are implied. However, it is recognized that these methods, except those devoted to multicriteria classification problems, are subject to computational limitations with respect to the number of alternatives. This paper proposes a framework to facilitate the incorporation and use of outranking methods in geographical information systems (GIS). The framework is composed of two phases. The first phase allows producing a planar subdivision of the study area obtained by combining a set of criteria maps; each represents a particular vision of the decision problem. The result is a set of non-overlapping spatial units. The second phase allows constructing decision alternatives by combining the spatial units. Point, line and polygon feature-based decision alternatives are then constructed as an individual, a grouping of linearly adjacent or a grouping of contiguous spatial units. This permits us to reduce considerably the number of alternatives, enabling the use of outranking methods. The framework is illustrated through the development of a prototype and through a step-by-step application to a corridor identification problem. This paper includes also a discussion of some conceptual and technical issues related to the framework. [ABSTRACT FROM AUTHOR]