This work presents the integration of the PySAL Gi hotspot detection in QGIS. This plugin is a first step towards the insertion of PySAL in QGIS which would improve drastically the QGIS Exploratory Spatial Data Analysis functionalities. The hotspot detection is illustrated with the analysis of shared GPS sport tracks during weekdays and weekends. A heatmap is compared with the result of the Gi hot spots analysis. Some remarks which may improve the quality of the paper: (1) Heatmaps: Usually, the heatmaps are computed with a Kernel Density Estimation (which is statistically well defined). Does the heatmap plugin implement a KDE or is it a blackbox function? (2) In p.5 "The main drawback of using heatmaps lies in the fact that both, the type of density function and the visualization parameters -adopted to produce the output map- strongly affect the result." does not agree with the KDE literature which says that the type of density functions has less impact than the choice of the proper threshold. (VA Epanechnikov. Non-parametric estimation of a multivariate probability density. Theory of Probability and its Applications, 1969) (3) Waypoints: Do the GPX tracks have the same sampling rate (for instance one point per minute). If no, did you resample the tracks to have a more homogeneous dataset? (4) Spatial unit: Why did you choose the municipalities rather than an other spatial unit (for instance a regular grid)?
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