Worldwide, due to rapid urbanization, the provision of urban green spaces (UGSs) has become a primary goal of urban planning. As such, research on the benefits, effects, and challenges of UGSs has gained widespread attention among scholars. This paper comprehensively analyzes three decades of UGS research and its evolution; it conducts a bibliometric analysis of approximately 4000 articles and reviews from the Web of Science platform to discover the patterns and trends characterizing UGS research over time. We found that the pioneers of initial UGS research were the United States and Canada, whereas recently the European Union and China have become the global engines of research in the field. UGS research initially focused on studying urban forests, gradually shifting toward green spaces located in inner urban areas. Early on, researchers investigated UGSs (i.e., urban forests) from an ecological perspective. However, the most current research phase focuses on the social aspects of UGSs, characterized by such keywords as environmental justice and accessibility. Furthermore, the introduction of geographic information systems (GIS) has given new impetus to the evolution of UGS research and has remained the most used technological advancement besides remote sensing techniques. As the social aspects of UGS research have gained importance, new research methods have been employed, such as machine learning, big data and social media data analysis, and artificial intelligence, most recently.

As the open access movement has gained widespread popularity in the scientific community, academic publishers have gradually adapted to the new environment. The pioneer open access journals have turned themselves into megajournals, and the subscription-based publishers have established open access branches and have turned subscription-based journals into hybrid ones. Maybe the most dramatic outcome of the open access boom is the market entry of such fast-growing open access publishers as Frontiers and Multidisciplinary Digital Publishing Institute (MDPI). By 2021, in terms of the number of papers published, MDPI has become one of the largest academic publishers worldwide. However, the publisher’s market shares across countries and regions show an uneven pattern. Whereas in such scientific powers as the United States and China, MDPI has remained a relatively small-scale player, it has gained a high market share in Europe, particularly in the Central and Eastern European (CEE) countries. In 2021, 28 percent of the SCI/SSCI papers authored/co-authored by researchers from CEE countries were published in MDPI journals, a share that was as high as the combined share of papers published by Elsevier and Springer Nature, the two largest academic publishers in the world. This paper seeks to find an explanation for the extensively growing share of MDPI in the publication outputs of CEE countries by choosing Hungary as a case study. To do this, by employing data analysis, some unique features of MDPI will be revealed. Then, we will present the results of a questionnaire survey conducted among Hungary-based researchers regarding MDPI and the factors that motivated them to publish in MDPI journals. Our results show that researchers generally consider MDPI journals’ sufficiently prestigious, emphasizing the importance of the inclusion of MDPI journals in Scopus and Web of Science databases and their high ranks and impacts. However, most researchers posit that the quick turnaround time that MDPI journals offer is the top driver of publishing in such journals.

The loss of farmland to urban use in peri-urban areas is a global phenomenon. Urban sprawl generates a decline in the availability of productive agricultural land around cities, causing versatile conflicts between nature and society and threatening the sustainability of urban agglomerations. This study aimed to uncover the spatial pattern of long-term (80 years) land cover changes in the functional urban area of Budapest, with special attention to the conversion of agricultural land. The paper is based on a unique methodology utilizing various data sources such as military-surveyed topographic maps from the 1950s, the CLC 90 from 1990, and the Urban Atlas from 2012. In addition, the multilayer perceptron (MLP) method was used to model land cover changes through 2040. The research findings showed that land conversion and the shrinkage of productive agricultural land around Budapest significantly intensified after the collapse of communism. The conversion of arable land to artificial surfaces increased, and by now, the traditional metropolitan food supply area around Budapest has nearly disappeared. The extent of forests and grasslands increased in the postsocialist period due to national afforestation programs and the demand of new suburbanites for recreational space. Urban sprawl and the conversion of agricultural land should be an essential issue during the upcoming E.U. Common Agricultural Policy (CAP) reforms.

Sweeping changes in park visitation have accompanied the Covid-19 pandemic. In countries where governments imposed strict lockdowns during the first wave, park visitation declined in cities. The benefits of visiting urban green spaces on people’s mental and physical health and well-being are generally acknowledged; many people in confinement during lockdowns reported increasing mental health issues. Therefore, based on lessons learned from the Covid-19 pandemic’s first wave, urban parks and other urban green spaces remained open in most countries in subsequent pandemic phases. Furthermore, many studies have reported an overall increase in park visitation after strict lockdowns imposed in the pandemic’s first wave have been removed. This study aims to investigate park visitation trends in Hungary based on a dataset of 28 million location data points from approximately 666,000 distinct mobile devices collected in 1884 urban parks and other urban green spaces in 191 settlements between June 1, 2019, and May 31, 2021. Findings demonstrate that park visitation increased in the inter-wave period of 2020, compared to the pre-pandemic period of 2019, and decreased in Waves 2–3 of 2021, compared to Wave 1 of 2020.