Landscape character: a knowledge mapping analysis using CiteSpace

Zhuang, Qianda; Hussein, Mohd Kher; Ariffin, Noor Fazamimah Mohd; Yunos, Mohd Yazid Mohd

doi:10.1007/s13762-022-04279-5

Cited by 22 publications

(8 citation statements)

References 76 publications

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“…In the author analysis, Huo X and Xu XJ had the highest number of publications (45, 40) and h-index (23,23). The consistency and magnitude of their contributions over time indicate that they have always paid attention to this field of research.…”

Section: Discussionmentioning

confidence: 93%

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Global research into the relationship between electronic waste and health over the last 10 years: A scientometric analysis

Tian

Chen

et al. 2023

Front. Public Health

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IntroductionThe aims of this research were to conduct the first holistic and deep scientometric analysis of electronic waste and health and provide with the prediction of research trends and hot topics.MethodA comprehensive literature search was conducted via the Web of Science Core collection databases on 26 August 2022 to identify all articles related to electronic waste and health. A total of 652 records have been extracted from the Web of Science after applying inclusion and exclusion criteria and were analyzed using bibliometrix software of R-package, VOSviewer, and CiteSpace, visualized by tables and diagrams.ResultThe number of publications and total citations had shown a general growth trend from 2012 to 2021, with an average annual growth rate of 23.74%. Mainland China was the significant nation with the greatest number of publications, citations, and international links. The journal publishing the most was “Science of the Total Environment” (n = 56). Huo X and Hu XJ were the top two author contributing to this field with the highest h-index (23). Over time, the focus in this field shifted to exposure to heavy metal, polychlorinated biphenyls, polybrominated biphenyl ethers, and poly- and perfluorinated alkyl substances from electronic waste, and managements, such as hydrometallurgy.DiscussionBy this scientometric analysis, we found that the most active country, journal, organization and author contributing to this filed, as well as high impact documents and references and research hotspots. Also, we found that the hotspots might be exposure to toxic substances from electronic waste procession, its impact on human health and relevant managements. And evironmentally friendly materials to replace heavy metal mate rials, and environmentally friendly and effective recycling methods of electronic waste need to be further studied.

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Section: Discussionmentioning

confidence: 93%

“…The overlay map showed the co-authorship of countries, and the co-citation of references was also shown by the density map. Further, the keywords occurring more than five times were shown in the three visualizations of the co-occurrence analysis to identify important terms ( 23 ).…”

Section: Methodsmentioning

confidence: 99%

Global research into the relationship between electronic waste and health over the last 10 years: A scientometric analysis

Tian

Chen

et al. 2023

Front. Public Health

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“…CiteSpace articles are often published in foreign journals. For example, see [32][33][34]. In this study, NVivo 12 Plus (http://www.strong-vinda.com/, accessed on 4 November 2022) was used for content analysis, targeting highly cited papers on the subject of policy environment research, and we aimed to determine the basic value, main framework and main content in respect of the policy environment [35].…”

Section: Research Design 21 Research Methodologymentioning

confidence: 99%

China’s Policy Environment’s Development and Path from the Perspective of Policy Sustainability: A Visual Analysis Based on CNKI and WOS

Dai

et al. 2022

Sustainability

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In this paper, we examine China’s policy environment from the perspective of policy sustainability. Through our use of the CiteSpace and NVivo software, the literature on the policy environment is visualized using a knowledge graph analysis and a content analysis of highly cited papers. The analysis shows that: the number of published papers on “policy environment” is on the rise, and the research prospect is broad. There is a lack of communication and cooperation between domestic authors and a close relationship between international authors. The main research countries included the USA, Switzerland, Finland, Ireland, and Austria, etc. Domestic research focuses on vehicles for high-quality economic and social development, while international research focuses on theoretical model discussion. The domestic optimization path focuses on the transformation from “Sending blood” (“ShuXieShi”) to “Making blood” (“ZaoXieShi”), while the international research focuses on the main line of “public health and environmental protection”. Domestic research focuses on fostering a sound business environment, while international research focuses on the public, political and professional aspects of health and medical policy environment. On the whole, in the future, we should improve the adaptability of the policy environment, optimize the policy implementation environment, and establish the interaction mechanism of policy environment optimization to achieve policy optimization.

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“…The above operations can extract a series of important features from rural landscape images, including the distribution of land cover types and the spatial distribution of key natural resources. These features are extracted through the fusion analysis of GIS and CNN, and are further used to evaluate the ecological value of landscapes, monitor environmental changes, and predict future trends in landscape changes [12].…”

Section: Landscape Featuresmentioning

confidence: 99%

Integration of GIS and Artificial Intelligence Algorithms in Rural Landscape Protection and Planning

2024

jaip

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This article explored the application of the integration technology of GIS and artificial intelligence (AI) algorithms in rural landscape protection and planning. By analyzing the problems existing in traditional methods, the article elaborated on the necessity and feasibility of combining GIS (Geographic Information System) and CNN (Convolutional Neural Network) algorithms to improve data processing capabilities and strengthen comprehensive analysis capabilities. Through case studies and empirical analysis, the article demonstrated the practical application effect and potential of this fusion technology, providing a new perspective and method for the scientific planning and effective protection of rural landscapes. In the experimental stage, four experiments were designed to evaluate the performance of GIS and CNN fusion. In the first landscape basic feature extraction experiment, the CNN algorithm achieved an accuracy of 95% in extracting features from rural landscape images; the Multi-layer Perceptron algorithm achieved 85%; the RF (Random Forest) achieved an accuracy of 80%; the Support Vector Machine (SVM) achieved 82%. Although the CNN algorithm achieved a processing time of 2 seconds, it had a high accuracy advantage. In the second landscape diversity assessment experiment, the method of integrating GIS and CNN improved species richness by 15%, landscape heterogeneity by 20%, and landscape connectivity by 25%. In landscape change detection experiments, the fusion technology of GIS and CNN has significant advantages in capturing subtle landscape changes. In the experimental data conclusion, the fusion technology of GIS and CNN had a high performance advantage in improving rural planning and management processes.

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Landscape character: a knowledge mapping analysis using CiteSpace

Cited by 22 publications

References 76 publications

Global research into the relationship between electronic waste and health over the last 10 years: A scientometric analysis

Global research into the relationship between electronic waste and health over the last 10 years: A scientometric analysis

China’s Policy Environment’s Development and Path from the Perspective of Policy Sustainability: A Visual Analysis Based on CNKI and WOS

Integration of GIS and Artificial Intelligence Algorithms in Rural Landscape Protection and Planning

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