Title. Methodological considerations in fine-scale spatial analysis: point pattern investigation of discarded syringes used in public injection of illicit drugs Mapping and Analysis for Public Safety September 2005 Savannah, Georgia
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Methodological considerations in fine-scale spatial analysis: point pattern investigation of discarded syringes used in public injection of illicit drugs
Mapping and Analysis for Public SafetySeptember 2005Savannah, Georgia
Luc de Montigny ([email protected])University of WashingtonUrban Design and Planning
Analyze the distribution of syringes found in the most active hard-drug use neighborhood of Montréal, Canada.
Crime – like disease – is often analyzed for large areas (states, counties, cities).
Large extents usually mean low resolution (big units of analysis) and aggregation of data.
Discrete events are pooled; point values become area counts (points -> surface).
Traditional geo/spatial statistical analyses can be used. Underlying assumptions effectively hold.
Assuming an exhaustive sampling strategy (e.g., documentation of all police reports), units of analysis that do not host an event represent a none-event.
There is a difference between “zero” and “no data.”
*D (d )=Kcases(d ) - Kcontrols(d )
Luc de Montigny – MAPS – 2005Random Labeling – Results
Non-flat curve* indicates difference between spatial distribution of cases from distribution of controls: clustering over and above that of environmental heterogeneity.
Peaks outside the simulation envelope should be considered significant.
K1: observations (cases)
K2: non-observations (controls)
PVC lines represent the boundary of the area that contains 90% of the volume of a probability density distribution; on average 90% of the points that were used to generate the KDE are contained within the lines.
Luc de Montigny – MAPS – 2005KDE – Syringe Points
The “smoothed” surface represents the intensity of discarded syringes within the search radius, or bandwidth (100m) of any given location in the study area (i.e., for every grid cell).
Here the sample frame is converted to a grid (10m), and the centroid of each cell is used for the purposes of the kernel density estimation.
Luc de Montigny – MAPS – 2005KDE – Sample Frame
The ratio surface represents, for each grid cell, the syringe point KDE value divided by the square of the sample frame KDE value.
Luc de Montigny – MAPS – 2005KDE – Syringe/Sample Ratio
Luc de Montigny – MAPS – 2005 syringe point KDE value divided by the square of the sample frame KDE value.KDE – Comparison
A comparison of how syringe points cluster in the study area (simple density estimate), to how those same points cluster within the sample space (the ratio between the two density estimates).
These results suggest that the distribution (clustering) of syringes is due to factors other than the distribution of opportunity.
Luc de Montigny – MAPS – 2005 syringe point KDE value divided by the square of the sample frame KDE value.Caveats and Limitations
Luc de Montigny – MAPS – 2005 syringe point KDE value divided by the square of the sample frame KDE value.Summary
This research would not be possible without the hard work and collaboration of Spectre de rue, Montréal.