Background and objective: Climate change and its impact on carbon storage in urban trees is a topic that has received increasing attention. Related studies focusing on data collection and analysis-based programs, such as the Forestry Inventory Analysis (FIA) programme in the US, have presented remarkable approaches to obtaining integrated analysis estimates and its management structure from a long-term perspective. This study explored the FIA programme in the context of long-term management in relation to tree carbon-related data collection and analysis.Methods: For the analysis, this study employed bibliometric methods (network using VOSviewer and coordinated analysis using NVivo) and an analytical framework. The case study is based on FIA-related driver changes of the keywords 'carbon' and 'tree' as well as the FIA management structure, using place-keeping theory as an integrated analytical framework and as the approach to long-term management.Results: Analysing FIA shows long-term management which has run since 2010, revealing key issues and significant terms in six dimensions of place-keeping analytical frameworks: public-private partnership-based data collection and political support in policy, central and local government-integrated fundraising from income generation, active governance-formed community activities in governance, alliance-structured networks in partnerships, integrated or unified estimated structures in evaluation, and maintenance. The case analysis reveals the necessity of a long-term management approach that incorporates a carbon storage estimate-focused policy, integrated income-partnerships, expanded active governance, Private Public Community Partnership (PPCP) multi-sector partnerships, and data platform settings.Conclusion: Newly emerging urban tree management structures should be reflected first on establishing an integrated carbon neutrality-based estimating system and secondly, on building long-term management approaches to the system. This will ultimately allow for climate change adaptation to approach carbon neutrality.
This study attempts to identify the direction of urban regeneration projects in declining areas by using the concept of urban resilience to cope with climate change and disaster. To this end, urban resilience was classified into a Green Resilient Infrastructure (GRI) and an Interactive Safety System (ISS), through a review of previous studies, and categorized into vulnerability, adaptability, and transformability. A total of 12 detailed indicators were derived and indexed using Euclidean distance. Using the indicators, three Korean urban regeneration targets, in Daegu, Mokpo, and Seosan, were selected to evaluate resilience before and after the urban regeneration plan. Consequently, the postplanning resilience index improved in all three target sites, compared to before the regeneration plan. Additionally, previously the regeneration plan showed lower index values in comparison to places not designated as urban regeneration areas. These results suggest that urban resilience needs to be considered in future urban regeneration projects, and that resilience indicators can be used as a means to set the direction of urban regeneration projects. To improve the overall resilience of a region, these indices can help local government establish a reference point for urban resilience in its region.
Background and objective: There have been increasing correlations between the keywords 'carbon' and 'tree' in response to issues related to climate change adaptation. Given this, a study that explores how these keywords relate to issues on climate change adaptation would be significant contribution to the literature. Therefore, this study aims to determine the correlation between these keywords and their network.Methods: To address the aim, the study employed a bibliometric analysis using the VOSviewer software to conduct network-mapping interface analysis using co-occurrence-based visualization and quantification. A two-step approach was applied: the first approach identifies recent driver changes of the keywords 'carbon' and 'tree' and further meaningful keywords. The second approach conducts an in-depth network mapping analysis based on the results drawn by the first approach.Results: The results suggested that, first, 'carbon' and 'tree' were shown to reflect the assessment system and contemporary issues based on the keywords 'carbon sequestration' and 'climate change.' In addition, 'biomass,' 'tree growth,' 'tree ring' and 'trade-off' were shown to be important keywords, which indicated the need for an in-depth correlation analysis. Second, 'biomass' was the key factor in the assessment system for 'carbon sequestration,' in which 'tree growth' and 'tree ring' were included. Third, the network analysis did not report varying results on 'trade-off' compared to 'carbon' and 'tree' with respect to the basic issues on climate change.Conclusion: The conventional assessment system based on the keywords 'carbon' and 'tree' should be improved by incorporating the issues drawn from the keywords 'biomass' and 'trade-off' so that it may reflect the latest contemporary needs. The network analysis on the keywords 'carbon' and 'tree' nevertheless indicated that the two keywords were at the centre of the latest contemporary issues and the assessment system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.