The coronavirus disease which results from severe acute respiratory syndrome (SARS-COV-2), is considered a global challenge affecting millions of people and leading to a global increase in mortality, including in Jordan. Therefore, this study aims to analyze the temporal and spatial patterns of the prevalence and outbreak of coronavirus in Jordan during six periods, from 1, October 2020 until 31, March 2021 by applying geographical information systems. The Moran coefficient was applied in addition to the G* test and location quotient (LQ). The results showed the overall pattern for the distribution of cases affected by the virus was random since most governorates' experience increased the focus and prevalence of the pandemic. Furthermore, four hot spots were revealed, namely Amman, Irbid, Zarqa, and Balqa'. This study introduced new insights into the statistical analysis of the distribution and prevalence of coronavirus in Jordan using geographical information systems. This will help planners and decision-makers to predict the dynamics of the temporal and spatial transfer of the virus in the future. It will also explain the current situation to set the appropriate policies or measures to face the pandemic, as well as reduce its prevalence. Therefore, monitoring, evaluating, and planning the usage of geospatial analysis are essential for controlling the spread of COVID-19 in the country.
This research paper investigates the spatial distribution of urban centres in Tafila Governorate, by determining their spatial extension, their actual centre of gravity, the expected and the median centre. To analyse this pattern spatial statistical methods were used and the technical capabilities represented by the technology of geographic information systems. The results of the study showed the average locations for the distribution of urban centres, the location of the spatial mean, the weighted spatial mean according to the population, and the location of the spatial mediator and the weighted spatial mediator. A convergence between these sites was found clearly evident. In addition, the weighted standard distance for the spread of urban centres was calculated, and the direction of the spatial distribution of the urban centres was determined to show the extent of dispersion of those centres around the weighted spatial mean. The study also showed that the distribution pattern of urban centres in the governorate takes the spatial scattered pattern by applying the closest neighbour analysis; the analysis showed the population weight in the form of points and in the form of rings reflecting the population density of the communities in each of the areas selected for study. In addition, by using Thiessen polygons, the drawing of urban centres’ areas (regions) was revealed. The study recommended the necessity of classifying urban centres, developing special planning standards compatible with the local reality, and creating a comprehensive database in collaboration with the authorities responsible with the planning process of urban centres.
In this study, we identify methods of measuring accessibility to public services in the city of Aqaba. Accessibility is an indicator of the efficiency of their spatial distribution in relation to residential neighborhoods in the city. Administrative, commercial, educational, health and entertainment services were selected for a case study because they are the most important services. We used spatial analysis tools in Arc Map within the geographic information systems (GIS) environment to measure direct distances between neighborhood centres and public services and to determine the number of services within specific ranges (1,000 m, 500 m, 200 m), using the three most common methods of measuring accessibility: the distance to the nearest service, the number of services within a certain distance or time, and the average distance for all services. The results of this research indicate that educational services have the highest degree of accessibility, followed by slight differences among recreational, administrative, and commercial services. Health services lag further behind.
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