The coronavirus disease 2019 (COVID-19) pandemic has had tremendous and extensive
impacts on the people's daily activities. In Chicago, the numbers of crime fell considerably …

The analysis of geographically referenced data, specifically point data, is predicated on the
accurate geocoding of those data. Geocoding refers to the process in which geographically …

We propose a scalable agent-based crime simulation model based on the routine activity
theory. It uses census data and time geography to create a synthetic population with …

Using law enforcement data from four Midwest communities, we document the similarities
and differences between criminal nonfatal and fatal shooting incidents, including the spatial …

Objectives To investigate spatial pattern data signatures in residential burglary resulting
from the crime drop. Methods Geo-referenced crime data, 2003–2016, representing …

Objectives To test for statistically significant changes in crime rates across neighbourhoods
in Saskatoon, Canada resulting from social restrictions within the natural experiment of the …

Police targeting hot spots of crime tends to disproportionately burden minorities via stops
and arrests. This work attempts to reduce disproportionate minority contact by formulating a …

Background A key issue in the analysis of many spatial processes is the choice of an
appropriate scale for the analysis. Smaller geographical units are generally preferable for …

The present research analyses a local variation of the problem of violence in Brazil and
focuses on Florianópolis, the capital of the state of Santa Catarina, long considered the …

Geocoding consists in converting a textual description of a location into coordinates. Hence,
geocoding a dataset of events has to be carried out before performing a spatial analysis of …