A scientometric analysis and visualization of global research on brownfields
2019
Lin, Hongli | Zhu, Yuming | Ahmad, Naveed | Han, Qingye
Brownfields have attracted increasing attentions from both researchers and practitioners. However, few studies have attempted to make a comprehensive and quantitative review on this topic. This study conducted a scientometric review on the brownfield research from 1995 to 2017 using CiteSpace. The knowledge structure, hot topics, research trends, and gaps were analyzed based on the co-author, co-word, co-citation, and clusters analysis. Six hundred thirty articles from the Web of Science core collection database were selected as the research samples. Results revealed that the research focus has changed from soil remediation technologies to sustainable regeneration methods. The most vital development in brownfield research occurred in the USA, England, Canada, Germany, and China. “Brownfield,” “heavy metal,” “remediation,” “redevelopment,” and “sustainability” were the most frequently used keywords. Whereas “management” and “biodiversity” received citation bursts in recent years. Existing researches mainly concentrated on subject categories of environmental sciences ecology, environmental sciences, engineering, environmental studies, engineering environmental, and urban studies. Sustainable regeneration, urban brownfields’ regeneration, mental distribution, coal-mine brownfield, and ecosystem service were the identified co-citation clusters and represented the hot topics and emerging trends. The research gaps can serve as a motivation to research on the next generation of brownfields to support the sustainable development. This study provides researchers and practitioners an extensive and intensive understanding of the salient research themes and trends of brownfields’ research worldwide.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par National Agricultural Library
Découvrez la collection de ce fournisseur de données dans AGRIS