English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The built environment has been postulated to have an impact on neighborhoodcrime rates, however, measures of the built environment can be subjective anddiffer across studies leading to varying observations on its association withcrime rates. Here, we illustrate an accurate and straightforward approach toquantify the impact of the built environment on neighborhood crime rates fromhigh-resolution satellite imagery. Using geo-referenced crime reports andsatellite images for three United States cities, we demonstrate how imagefeatures consistently identified using a convolutional neural network canexplain up to 82% of the variation in neighborhood crime rates. Our resultssuggest the built environment is a strong predictor of crime rates, and thiscan lead to structural interventions shown to reduce crime incidence in urbansettings.

Using Deep Learning and Satellite Imagery to Quantify the Impact of the Built Environment on Neighborhood Crime Rates