Toward sustainable stormwater management: Understanding public appreciation and recognition of urban Low Impact Development (LID) in the San Francisco Bay Area

Darnthamrongkul, Wilasinee; Mozingo, Louise A.

doi:10.1016/j.jenvman.2021.113716

Cited by 38 publications

(15 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A general positive public sentiment toward China’s urban regeneration has been confirmed, with an overall ratio of positive to negative comments of 2.3:1 and an arithmetic mean of SI of 4.01 (under an overall confidence level of 0.88). In comparison with previous studies that conducted local and web questionnaire surveys on specific renovation projects [ 16 , 17 , 32 ], our results appear to be more pessimistic. This may be due to the fact that we used a more comprehensive and extensive dataset, and more complaints and questioning were revealed.…”

Section: Discussioncontrasting

confidence: 84%

“…Using social network analysis methods, Cao and Tang compared networks of public space layouts and residents’ daily behaviors in urban regeneration, and evaluated the effects of the regeneration process [ 31 ]. A study conducted by Darnthamrongkul and Mozingo examined the responses of users regarding 16 urban stormwater management projects located in the San Francisco Bay Area, thereby providing empirical insights into how citizens are implementing low-impact urban regeneration practices [ 32 ]. Based on qualitative research and a narrative survey methodology, Jelili et al evaluated an urban regeneration program implemented in Lagos Island and found that resident input should be encouraged in order to achieve effective resident cooperation [ 33 ].…”

Section: Literature Review and Backgroundmentioning

confidence: 99%

See 1 more Smart Citation

Public sentiment analysis on urban regeneration: A massive data study based on sentiment knowledge enhanced pre-training and latent Dirichlet allocation

Chen¹,

Ru-liang²

2023

PLoS ONE

View full text Add to dashboard Cite

Background Public satisfaction is the ultimate goal and an important determinant of China’s urban regeneration plan. This study is the first to use massive data to perform sentiment analysis of public comments on China’s urban regeneration. Methods Public comments from social media, online forums, and government affairs platforms are analyzed by a combination of Natural Language Processing, Knowledge Enhanced Pre-Training, Word Cloud, and Latent Dirichlet Allocation. Results (1) Public sentiment tendency toward China’s urban regeneration was generally positive but spatiotemporal divergences were observed; (2) Temporally, public sentiment was most negative in 2020, but most positive in 2021. It has remained consistently negative in 2022, particularly after February 2022; (3) Spatially, at the provincial level, Guangdong posted the most comments and Tibet, Shanghai, Guizhou, Chongqing, and Hong Kong are provinces with highly positive sentiment. At the national level, the east and south coastal, southwestern, and western China regions are more positive, as opposed to the northeast, central, and northwest regions; (4) Topics related to Shenzhen’s renovations, development of China’s urban regeneration and complaints from residents are validly categorized and become the public’s key focus. Accordingly, governments should address spatiotemporal disparities and concerns of local residents for future development of urban regeneration.

show abstract

Section: Discussioncontrasting

confidence: 84%

Section: Literature Review and Backgroundmentioning

confidence: 99%

Public sentiment analysis on urban regeneration: A massive data study based on sentiment knowledge enhanced pre-training and latent Dirichlet allocation

Chen¹,

Ru-liang²

2023

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…Another study took the advantage of ISM to find key drivers that trigger floods from glacial lakes (Trivedi et al, 2021). Darnthamrongkul and Mozingo (2021) studied users' reactions to some LID introduced for sustainable storm water management in the San Francisco Bay Area and results revealed the positive effects of these structures in satisfying public expectations. Another study used stakeholders' perceptions to cover the gap of using LID for industrial sustainable storm water management and identified technological feasibility limitation, institutional inertia, and cognitive shortage as the main barriers (Wang & van Roon, 2021).…”

Section: Interpretive Structural Modelingmentioning

confidence: 99%

A soft systems methodology and interpretive structural modeling framework for Green infrastructure development to control runoff in Tehran metropolis

Saeedi

Tabrizi

Bahremand

et al. 2022

Natural Resource Modeling

View full text Add to dashboard Cite

Green Infrastructure Development (GID) is a wellknown method for dealing with runoff control and mitigating the urbanization effects on hydrological cycles. Other than hydrological factors, GID is obviously intertwined with many socioeconomic, environmental, and aesthetic considerations, constraints, and drivers. Human perceptions are valuable resources to distinguish these considerations and can be derived from unstructured information using a systematic method. The purpose of this article is to exhibit how the perceptions of stakeholders were derived in Tehran for a conceptual model of green infrastructure development. For this, we applied a combination of Soft Systems Methodology (SSM) and Interpretive Structural Modeling (ISM). The results revealed the main stakeholders, their relationships and responsibility, main obstacles for GID, and the conceptual system of activities for GIs development in Tehran. Based on the results, actions for improving the

show abstract

“…Still, it should be considered in the future together as depending on the context it could offer positive welfare effects (benefits) (Darnthamrongkul and Mozingo, 2021;Jensen et al, 2019;Ureta et al, 2021).…”

Section: Alternative Scenario: Constructed Wetlandmentioning

confidence: 99%

Cost-benefit of green infrastructures for water management: A sustainability assessment of full-scale constructed wetlands in Northern and Southern Italy

García-Herrero

Lavrnić²,

Guerrieri³

et al. 2022

Ecological Engineering

View full text Add to dashboard Cite

Toward sustainable stormwater management: Understanding public appreciation and recognition of urban Low Impact Development (LID) in the San Francisco Bay Area

Cited by 38 publications

References 22 publications

Public sentiment analysis on urban regeneration: A massive data study based on sentiment knowledge enhanced pre-training and latent Dirichlet allocation

Public sentiment analysis on urban regeneration: A massive data study based on sentiment knowledge enhanced pre-training and latent Dirichlet allocation

A soft systems methodology and interpretive structural modeling framework for Green infrastructure development to control runoff in Tehran metropolis

Cost-benefit of green infrastructures for water management: A sustainability assessment of full-scale constructed wetlands in Northern and Southern Italy

Contact Info

Product

Resources

About