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A review on the role of green vegetation in improving urban environmental quality

The exacerbation of climate change impacts within metropolitan areas is a well-documented phenomenon, often leading to severe consequences that pose significant risks to human populations. The impact of urban vegetation and planting design on these factors can be observed. However, it is worth mentioning that while there is an extensive body of literature on the consequences of climate change, there is a relatively small number of studies specifically focused on examining the role of vegetation as a mitigating factor in urban environments. This review paper aims to critically examine existing studies pertaining to the role of urban vegetation in mitigating the detrimental effects of the urban environment. The objective is to offer practical recommendations that can be implemented by city planners. By conducting a comprehensive examination of the literature available in Scopus, Web of Science, and Google Scholar, employing specific keywords pertaining to urban vegetation and climate change, we have identified five prominent concerns pertaining to the urban environment. These concerns encompass particulate matter, gaseous pollution, noise pollution, water runoff, and the urban heat island effect. The present analysis highlights that the impact of urban vegetation on the negative consequences of climate change cannot be unequivocally classified as either positive or negative. This is due to the fact that the influence of urban greenery is intricately connected to factors such as the arrangement, makeup, and dispersion of vegetation, as well as the specific management criteria employed. Hence, this research has the potential to enhance comprehension of the multifaceted nature of urban green spaces and establish a solid groundwork for subsequent investigations.

Analytical study on the coupling coordination degree of tourism and urban development—Taking Shaanxi as an example

Tourism has been instrumental in fostering regional economic growth, enhancing the quality of life of residents, and boosting the image of urban areas in Shaanxi, thanks to the accelerated economic and social development of recent years. Nevertheless, the issue of aligning urban development and tourism in terms of space, resources, and the industrial chain remains a significant concern. This paper establishes an evaluation index system for tourism and urban development in the Shaanxi region from 2009 to 2019. It then employs the systematic coupling coordination model to conduct a comprehensive analysis of the coupling coordination degree of tourism and urban development in the region, as well as its various influencing factors. The study demonstrates that the coupling and coordination degree of tourism and urban development in the Shaanxi region exhibited a trend of continuous improvement from 2009 to 2019. The region underwent three stages of development: “uncoordinated development (2009–2011), transformation development (2012–2016), and coordinated development (2017–2019).” The coupling coordination level was elevated from “mild dissonance” to “intermediate coordination” in 2019. In contrast, the tourism economic development of Shaanxi cities remains unequal, as evidenced by the existence of two distinct categories of development: the “lagging tourism economy” and the “coordinated tourism economy.” The findings of this investigation indicate that the general trend of urban development and tourism in Shaanxi is favorable; however, the disparities in the progress of the tourism economy among cities necessitate additional regional coordination and cooperation. The theoretical support for the relevant research and a reference basis for tourism development planning and urban policy making are provided by the evaluation index system and the systematic coupling coordination model proposed in this paper. This will facilitate the sustainable and coordinated development of the tourism industry and cities in Shaanxi.

Exploring traffic accidents patterns: Spatial distribution and socio-economic determinants

Pires Abdullah, Tibor Sipos

Article ID: 2250
Vol 4, Issue 1, 2023

DOI: https://doi.org/10.54517/ec.v4i1.2250

Received: 28 April 2023; Accepted: 16 June 2023; Available online: 22 June 2023;
Issue release: 30 June 2023

VIEWS - 916 (Abstract)

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Abstract

This study employs a machine learning methodology, specifically the decision tree algorithm, in conjunction with the Quantum Geographic Information System (QGIS), to conduct a rigorous analysis of traffic accident data. The research aims to investigate various factors associated with traffic accidents, with a particular emphasis on their spatial distribution and the socio-economic determinants contributing to recurring accidents caused by drivers. The study focuses on the city of Duhok, located in the Kurdistan Region of Iraq, and utilizes a questionnaire to collect data from drivers regarding accident locations and the frequency of accidents within the past decade (from 2010 to 2020). The findings of the study reveal that the city center experiences the highest concentration of accidents, while severe collisions tend to occur in specific “black spots” scattered across the city’s road network. The decision tree model, employed to classify drivers with multiple accidents, identifies the primary causes of accidents as traffic conditions, traffic law violations, and overspeeding. Furthermore, the accident locations are found to be influenced by various factors, including different types of road hierarchy. The age and gender of drivers also contribute to accident patterns. These research findings have practical implications for enhancing road safety measures and reducing the frequency of traffic accidents. The utilization of machine learning techniques, combined with the analysis of spatial data through QGIS, provides a comprehensive understanding of the underlying factors contributing to accidents. Moreover, this research contributes novel insights to the field of road traffic accidents and safety, particularly in the context of the city of Duhok in Kurdistan Region, Iraq, and provides a valuable reference for future studies in the domain of road safety and urban planning.

Keywords

road accidents; spatial analysis; socioeconomic factors; decision tree classifier

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