Supporting Resilient Urban Planning through Walkability Assessment

Creating a Healthy Environment for Children: GIS Tools for Improving the Quality of the Social Welfare Management System

Childhood is considered to be the most vital period for mental, physical, and social development. Even short-term deprivation of nutrition, health care, education, and affection in childhood can have long-term and irreversible negative consequences. Various social assistance programs are being launched around the world to eliminate or alleviate social problems, including those experienced by children in their immediate environment. Different solutions have been proposed around the world, but welfare systems in all countries share the following common features: social assistance is necessary and underfinanced, and social workers struggle to cope with caseloads. As a result, welfare work is stressful and not highly effective. In this study, modern Geographic Information System (GIS) tools for supporting the employees of social assistance centers (SACs) have been proposed. The data relating to welfare beneficiaries were analyzed by nonparametric kernel density estimation and divided into five datasets. The kernel density tool in ArcGIS Pro software (Esri Polska sp. z o.o., Warsaw, Poland) was used to visualize areas with a relatively high prevalence of social problems, as well as areas where the neighborhood can deliver synergistic effects. A multicriteria analysis (MCA) procedure for mapping social problems was proposed, and an algorithm was developed in the GIS environment. The generated maps deliver helpful information for supporting SAC employees, as well as monitoring, planning, and initiating preventive measures. Above all, the presented method was designed to improve living conditions by facilitating the management of welfare workers' duties. Therefore, the proposed approach had to be effective and easy to use without an advanced knowledge of GIS tools.

Evaluation of Resilience in Historic Urban Areas by Combining Multi-Criteria Decision-Making System and GIS, with Sustainability and Regeneration Approach: The Case Study of Tehran (IRAN)

Historic urban areas are the beating heart of the city, but neglecting them can lead to low resilience. Therefore, paying attention to their regeneration can create a sustainable city. The purpose of this study was to determine the resilience of neighborhoods in Tehran and evaluate effective criteria for the resilience increase. In this study, to evaluate the resilience of Tehran, initially, 18 criteria were considered. Then, using the Delphi technique, 14 criteria among them were selected for final analysis. Using the AHP multi-criteria decision-making method, the importance of each criterion was determined. Using GIS capabilities, the parameters map was prepared, and by combining the prepared maps with AHP weights, a resilience map was created. Finally, 20 neighborhoods with the lowest resilience were identified as priorities for stabilization and regeneration measures, and the criteria status used in them was examined. Results showed that deteriorated urban areas (19.53%) and construction materials (18.51%) were the most important criteria. Non-resilience areas were generally in the southern half of the city. 78% of 20 selected neighborhoods had deteriorated urban areas, while only 14% of the city deteriorated. Finally, by examining the criteria in neighborhoods with the lowest resilience, suggestions were made to regeneration, sustainability, and increase the resilience of these neighborhoods.

Bridging the Gap: The Measure of Urban Resilience

The concept of resilience has arisen as a “new way of thinking” [...]

Multi-Criteria Stochastic Selection of Electric Vehicles for the Sustainable Development of Local Government and State Administration Units in Poland

Increasing the popularity of electric vehicles is one way of reducing greenhouse gas emissions and making the economy more sustainable. In Poland, the use of electric vehicles is to be increased by the adoption of the Act on Electromobility and Alternative Fuels. This Act obliges local government units and state administration to expand the electric vehicle fleet. The expansion of the fleet should be carried out on a planned basis, based on rational decisions supported by economic analyses. Therefore, the aim of this article is to provide a recommendation of an electric vehicle that meets the needs of local and state administration to the greatest extent possible. The aim has been achieved using the multi-criteria decision analysis method called PROSA-C (PROMETHEE for Sustainability Assessment—Criteria) combined with the Monte Carlo method. The PROSA-C method allows promoting more sustainable vehicles with high technical, economic, environmental and social parameters. The Monte Carlo method, on the other hand, is a stochastic simulation tool that allows for taking into account the uncertainty of parameters describing vehicles. As a result of the research, the most and least attractive vehicles were identified from the perspective of the needs of local government units and state administration. Moreover, the conducted research allowed confirming the effectiveness and usefulness of the research methodology proposed in the article and the procedural approach combining the PROSA-C and Monte Carlo methods.