Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 5 of 5 for “"Spatiotemporal modelling"”.
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Spatiotemporal modelling in biology: from transcriptional regulation to plasmid positioning
Here I describe how cycles of mathematical modelling and experimenting have advanced our quantitative understanding of two different processes: transcriptional regulation of the floral repressor FLOWERING LOCUS C (FLC ) in Arabidopsis thaliana and spatial positioning of low copy number plasmids in …
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Geostatistical spatiotemporal modelling with application to the western king prawn of the Shark Bay managed prawn fishery
… methodology has been employed in the modelling of spatiotemporal data from various scientific fields by viewing the data as realisations of space-time random functions. Traditional geostatistics aims to model the spatial variability of a process so, in order to incorporate a time …
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Modelling the Transmission of Dengue Fever Based on Spatial and Temporal Patterns
… host, and vector interactions result in complex spatiotemporal patterns in dengue disease. Moreover, it has been previously indicated that the dengue fever epidemic is due to several climatic, social, environmental, and biological factors, and these factors vary from place to place and with time. …
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Integration of Satellite Remote Sensing and Ground-based Measurement for Modelling the Spatiotemporal Distribution of Fine Particulate Matter at a Regional Scale
… seeks to advance the methodologies involved in spatiotemporal analysis of air quality that integrates remotely-sensed data and in situ measurement. Aerosol optical depth (AOD) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) is analyzed to estimate fine particulate matter …
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Multiscale Spatial and Temporal Modelling of Fine Particulate Matter (PM2.5) from Wildfire Smoke Using Remote Sensing and Statistical Methods
… predict PM2.5 concentration over space and time. Spatiotemporal models were built to perform a comprehensive analysis of wildfire PM2.5 concentrations, for each recent year over the study region: Land Use Regression (LUR), Linear Mixed Effect (LME), and Artificial Neural Network (ANN). Predictor …