Liliana Caramelo

Space-time clustering analysis performance of an aggregated dataset

This study focuses on the use of space-time permutation scan statistics (STPSS) to assess both the existence and the statistical significance of clusters on aggregated datasets. The investigated case study is represented from the Portuguese Rural Fire Database (PRFD) where the fire occurrences are georeferenced to an administrative unit level. The main goals are: (i) assessing the robustness of the STPSS to correctly detect clusters on aggregated datasets; (ii) testing the existence of space-time clustering in the PRFD; and (iii) characterizing the detected clusters. A synthetic database was designed to assess the potential bias introduced by aggregation of the data on the performance of the STPSS method. Results confirmed the ability of the STPSS to correctly identify clusters, regarding their number, location, and spatio-temporal dimensions and provided recommendations about the parameters setting of the scanning window. Finally, a discussion of the identified clusters on the PRFD is presented. Display Omitted We used space-time permutation scan statistics (STPSS).Assessment of STPSS over an aggregated synthetic dataset.STPSS is able to correctly detect significant space-time fire clusters in Portugal.Detection performance depends on the characteristics of the scanning window and database.Detected clusters were characterized by socioeconomic and environmental factors.

The use of relative residues in fitting experimental data: an example from fluid mechanics

A curve fitting model is presented which minimizes the sum of squares of relative residues and expressions for the fit coefficients and their respective errors are derived. The new model is compared to the normal least squares model, using as an example the Reynolds number-drag coefficient data for a sphere. The results show that the best fit was obtained with the new model, indicating it may provide a useful tool for data analysis.

Spatial and Temporal Variability of the Surface Air Temperature over the Duero Basin (Iberian Peninsula)

In this study we have investigated the spatial and temporal variability of 48 year annual temperature series for 40 meteorological stations distributed in the Duero Basin.