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Modelling spatio-temporal data with multiple seasonalities: The NO2 Portuguese case

Title
Modelling spatio-temporal data with multiple seasonalities: The NO2 Portuguese case
Type
Article in International Scientific Journal
Year
2017
Authors
Monteiro, A
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. View Authenticus page Without ORCID
Menezes, R
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. View Authenticus page Without ORCID
Journal
Title: Spatial StatisticsImported from Authenticus Search for Journal Publications
Vol. 22
Pages: 371-387
ISSN: 2211-6753
Publisher: Elsevier
Other information
Authenticus ID: P-00M-R05
Abstract (EN): This study aims at characterizing the spatial and temporal dynamics of spatio-temporal data sets, characterized by high resolution in the temporal dimension which are becoming the norm rather than the exception in many application areas, namely environmental modelling. In particular, air pollution data, such as NO2 concentration levels, often incorporate also multiple recurring patterns in time imposed by social habits, anthropogenic activities and meteorological conditions. A two-stage modelling approach is proposed which combined with a block bootstrap procedure correctly assesses uncertainty in parameters estimates and produces reliable confidence regions for the space-time phenomenon under study. The methodology provides a model that is satisfactory in terms of goodness of fit, interpretability, parsimony, prediction and forecasting capability and computational costs. The proposed framework is potentially useful for scenario drawing in many areas, including assessment of environmental impact and environmental policies, and in a myriad applications to other research fields.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 17
Documents
File name Description Size
1-s2.0-S2211675316301701-main 1329.86 KB
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