Trash, Cities, and Politics: Urban Environmental Problems in Indonesia

Indonesia ◽  
2017 ◽  
Vol 103 (1) ◽  
pp. 73-90 ◽  
Author(s):  
Jean-Jacques Dethier
Keyword(s):  
Environmental Problems ◽  
Urban Environmental Problems

The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems

2011 ◽  
Vol 31 (2) ◽  
pp. 273-288 ◽  
Author(s):  
Fei Chen ◽  
Hiroyuki Kusaka ◽  
Robert Bornstein ◽  
Jason Ching ◽  
C. S. B. Grimmond ◽  
...  
Keyword(s):  
System Development ◽  
Environmental Problems ◽  
Urban Modelling ◽  
Development Evaluation ◽  
Modelling System ◽  
Urban Environmental Problems

scholarly journals Can Urban Environmental Problems Be Accurately Identified? A Complaint Text Mining Method

2021 ◽  
Vol 11 (9) ◽  
pp. 4087
Author(s):  
Yaran Jiao ◽  
Chunming Li ◽  
Yinglun Lin
Keyword(s):  
Text Mining ◽  
Semantic Network ◽  
Semantic Networks ◽  
Environmental Problems ◽  
Pollution Sources ◽  
Unstructured Data ◽  
Guangzhou City ◽  
Individual Health ◽  
Sensory Features ◽  
Urban Environmental Problems

With the popularization of social networks, the abundance of unstructured data regarding environmental complaints is rapidly increasing. This study established a text mining framework for Chinese civil environmental complaints and analyzed the characteristics of environmental complaints, including keywords, sentiment, and semantic networks, with two–year environmental complaints records in Guangzhou city, China. The results show that the keywords of environmental complaints can be effectively extracted, providing an accurate entry point for solving environmental problems; light pollution complaints are the most negative, and electromagnetic radiation complaints have the most fluctuating emotions, which may be due to the diversity of citizens’ perceptions of pollution; the nodes of the semantic network reveal that citizens pay the most attention to pollution sources but the least attention to stakeholders; the edges of the semantic network shows that pollution sources and pollution receptors show the most concerning relationship, and the pollution receptors’ relationships with pollution behaviors, sensory features, stakeholders, and individual health are also highlighted by citizens. Thus, environmental pollution management should not only strengthen the control of pollution sources but also pay attention to these characteristics. This study provides an efficient technical method for unstructured data analysis, which may be helpful for precise and smart environmental management.

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