An integrated web-based air pollution decision support system – a prototype

Leung, Yee; Leung, Kwong Sak; Wong, Man Hong; Mak, Terrence; Cheung, Kwan Yau; Lo, Leung Yau; Yi, Wei; Dong, Yi

doi:10.1080/13658816.2018.1460752

Cited by 12 publications

(2 citation statements)

References 39 publications

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“…The concept of crowdsourcing is often conflated with such concepts as Volunteered Geographic Information -VGI (Goodchild 2007), contributed data (Harvey 2013), neogeography (Turner 2006), Public Participation GIS (Ramsey 2010), and the use of social media platforms employed in data production through photos, video and text (Leung et al 2018). Although these concepts are not necessarily synonymous, they all describe data contributed by the public at large leveraged by wide-spread technologies such as GPS, mobile devices, Internet connectivity, and Web-2 apps.…”

Section: Spatially Explicit Mca With Crowdsourced Datamentioning

confidence: 99%

Emerging trends and research frontiers in spatial multicriteria analysis

Malczewski

Jankowski

2020

International Journal of Geographical Information Science

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A majority of research on Spatial Multicriteria Analysis (SMCA) has been spatially implicit. Typically, SMCA uses conventional (aspatial) multicriteria methods for analysing and solving spatial problems. This paper examines emerging trends and research frontiers related to the paradigm shift from spatially implicit to spatially explicit multicriteria analysis. The emerging trend in SMCA has been spatially explicit conceptualizations of multicriteria problems focused on multicriteria analysis with geographically varying outcomes and local multicriteria analysis. The research frontiers align with conceptual and structural elements of SMCA and pertain to, among others, theoretical frameworks, problem structuring, model parameter derivation, decision problem contextualization, scale representation, treatment of uncertainties, and the very meaning of decision support. The paper also identifies research directions and challenges associated with developing spatially explicit multicriteria methods and integrating concepts and approaches from two distinct fields: GIS and multicriteria analysis.

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Section: Spatially Explicit Mca With Crowdsourced Datamentioning

confidence: 99%

Emerging trends and research frontiers in spatial multicriteria analysis

Malczewski

Jankowski

2020

International Journal of Geographical Information Science

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“…También es útil mostrar la serie temporal completa con la tendencia del período analizado [Elangasinghe et al, 2014]. Para permitir comparaciones diarias, mensuales y anuales de la variabilidad de la contaminación del aire es conveniente emplear una tabla de calendario para una fácil visualización [Leung et al, 2018].…”

Section: Iiiii Reportes Y Visualizacionesunclassified

Elaboración e implementación de una propuesta metodológica para la evaluación y gestión de la calidad del aire mediante el enfoque de la ciencia de datos

Represa¹

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Data Mining Paradigm in the Study of Air Quality

et al. 2019

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Air pollution is a serious global problem that threatens human life and health, as well as the environment. The most important aspect of a successful air quality management strategy is the measurement analysis, air quality forecasting, and reporting system. A complete insight, an accurate prediction, and a rapid response may provide valuable information for society's decision-making. The data mining paradigm can assist in the study of air quality by providing a structured work methodology that simplifies data analysis. This study presents a systematic review of the literature from 2014 to 2018 on the use of data mining in the analysis of air pollutant measurements. For this review, a data mining approach to air quality analysis was proposed that was consistent with the 748 articles consulted. The most frequent sources of data have been the measurements of monitoring networks, and other technologies such as remote sensing, low-cost sensors, and social networks which are gaining importance in recent years. Among the topics studied in the literature were the redundancy of the information collected in the monitoring networks, the forecasting of pollutant levels or days of excessive regulation, and the identification of meteorological or land use parameters that have the most substantial impact on air quality. As methods to visualise and present the results, we recovered graphic design, air quality index development, heat mapping, and geographic information systems. We hope that this study will provide anchoring of theoretical-practical development in the field and that it will provide inputs for air quality planning and management. Keywords Air quality . Environmental management . Air pollution . Data miningHighlights & 748 papers were published between 2014 and 2018 using data mining algorithms in the analysis of air pollutants. & 48 were selected and rigorously analyzed, from which a data mining approach was proposed for air quality management.

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An integrated web-based air pollution decision support system – a prototype

Cited by 12 publications

References 39 publications

Emerging trends and research frontiers in spatial multicriteria analysis

Emerging trends and research frontiers in spatial multicriteria analysis

Elaboración e implementación de una propuesta metodológica para la evaluación y gestión de la calidad del aire mediante el enfoque de la ciencia de datos

Data Mining Paradigm in the Study of Air Quality

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