Next Article in Journal
Mapping Very-High-Resolution Evapotranspiration from Unmanned Aerial Vehicle (UAV) Imagery
Next Article in Special Issue
Modeling Past, Present, and Future Urban Growth Impacts on Primary Agricultural Land in Greater Irbid Municipality, Jordan Using SLEUTH (1972–2050)
Previous Article in Journal
Assessment of Rainfall-Induced Landslide Distribution Based on Land Disturbance in Southern Taiwan
Previous Article in Special Issue
Utilizing Urban Geospatial Data to Understand Heritage Attractiveness in Amsterdam
Article

CrimeVec—Exploring Spatial-Temporal Based Vector Representations of Urban Crime Types and Crime-Related Urban Regions

1
Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria
2
Boston Area Research Initiative, School of Public Policy and Urban Affairs, Northeastern University, Boston, MA 02115, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Wolfgang Kainz and Maria Antonia Brovelli
ISPRS Int. J. Geo-Inf. 2021, 10(4), 210; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10040210
Received: 24 February 2021 / Revised: 20 March 2021 / Accepted: 22 March 2021 / Published: 1 April 2021
(This article belongs to the Special Issue Geodata Science and Spatial Analysis in Urban Studies)
The traditional categorization of crime types relies on a hierarchical structure, from high-level categories to lower-level subtypes. This tree-based classification treats crime types as mutually independent when they do not branch from the same higher-level category, therefore lacking inter-category semantic relations. The issue then extends over crime distribution analysis of urban regions, often reporting statistics based on crime type counts, but neglecting implicit relations between different crime categories. Our study aims to fill this information gap, providing a more complete understanding of urban crime in both qualitative and quantitative terms. Specifically, we propose a vector-based crime type representation, constructed via unsupervised machine learning on temporal and geographic factors. The general idea is to define crime types as “related” if they often occur in the same area at the same time span, regardless of any initial hierarchical categorization. This opens to a new metric of comparison that goes beyond pre-defined structures, revealing hidden relationships between crime types by generating a vector space in a completely data-driven manner. Crime types are represented as points in this space, and their relative distances disclose stronger or weaker semantic relations. A direct application on urban crime distribution analysis stands out in the form of visualization tools for intuitive data investigations and convenient comparison measures on composite vectors of urban regions. Meaningful insights on crime type distributions and a better understanding of urban crime characteristics determine a valuable asset to urban management and development. View Full-Text
Keywords: crime types; urban regions; embeddings; Word2vec; unsupervised learning; spatial-temporal analysis crime types; urban regions; embeddings; Word2vec; unsupervised learning; spatial-temporal analysis
Show Figures

Figure 1

MDPI and ACS Style

Crivellari, A.; Ristea, A. CrimeVec—Exploring Spatial-Temporal Based Vector Representations of Urban Crime Types and Crime-Related Urban Regions. ISPRS Int. J. Geo-Inf. 2021, 10, 210. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10040210

AMA Style

Crivellari A, Ristea A. CrimeVec—Exploring Spatial-Temporal Based Vector Representations of Urban Crime Types and Crime-Related Urban Regions. ISPRS International Journal of Geo-Information. 2021; 10(4):210. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10040210

Chicago/Turabian Style

Crivellari, Alessandro, and Alina Ristea. 2021. "CrimeVec—Exploring Spatial-Temporal Based Vector Representations of Urban Crime Types and Crime-Related Urban Regions" ISPRS International Journal of Geo-Information 10, no. 4: 210. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10040210

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop