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Spatio-temporal statistical models for PM10 time series in ..:
, In:
2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS)
,
Zandi, Sara
;
Ghobakhlou, Akbar
;
Whalley, Jacqueline
- p. 1-4 , 2024
Link:
https://doi.org/10.1109/MIGARS61408.2024.10544723
RT T1 <cTitle>2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS)</cTitle>: T1 <Title>Spatio-temporal statistical models for PM10 time series in Auckland</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10544723&Exemplar=1&LAN=DE A1 Zandi, Sara A1 Ghobakhlou, Akbar A1 Whalley, Jacqueline YR 2024 K1 Interpolation K1 Meteorological factors K1 Atmospheric modeling K1 Time series analysis K1 Urban areas K1 Market research K1 Spatiotemporal phenomena K1 PM10time series K1 spatio-temporal models SP 1 OP 4 LK http://dx.doi.org/https://doi.org/10.1109/MIGARS61408.2024.10544723 DO https://doi.org/10.1109/MIGARS61408.2024.10544723 SF ELIB - SuUB Bremen
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