<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Remote Sensing | ISSUES | The Ohio State University</title><link>https://issues-osu.github.io/ISSUESlab/tag/remote-sensing/</link><atom:link href="https://issues-osu.github.io/ISSUESlab/tag/remote-sensing/index.xml" rel="self" type="application/rss+xml"/><description>Remote Sensing</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 04 Nov 2026 10:45:00 +0000</lastBuildDate><image><url>https://issues-osu.github.io/ISSUESlab/media/logo_hu2fedd529b9d9d7008e9f6968cd645fa1_199187_300x300_fit_lanczos_3.png</url><title>Remote Sensing</title><link>https://issues-osu.github.io/ISSUESlab/tag/remote-sensing/</link></image><item><title>Beyond Urban–Rural Binaries: Remote Sensing Indicators of Built Environment Risk for Firearm Injury in Cook County, Illinois</title><link>https://issues-osu.github.io/ISSUESlab/presentations/ncfrh/</link><pubDate>Wed, 22 Oct 2025 00:00:00 +0000</pubDate><guid>https://issues-osu.github.io/ISSUESlab/presentations/ncfrh/</guid><description>&lt;p>&lt;strong>Presented at the 2025 National Research Conference for the Prevention of Firearm-Related Harms&lt;/strong>, this study develops a remote-sensing–based framework to identify built environment risk factors for firearm injury in Cook County, Illinois. Using satellite-derived indicators of nighttime light intensity, impervious surface coverage, vegetation (NDVI), and built-up density merged with firearm injury data from 2020–2024, we fit spatial random forest models and Bayesian spatial Poisson models to quantify environmental predictors of firearm harm.&lt;/p>
&lt;p>Findings show that built environment characteristics—rather than traditional urban–rural categories—more accurately distinguish high-risk census tracts. High built-up intensity, fragmented greenness, and asymmetric nighttime activity remain strong predictors even after accounting for area-level deprivation. These results demonstrate the utility of remote sensing for identifying structural vulnerability and guiding place-based firearm injury prevention.&lt;/p>
&lt;h3 id="-presentation">📄 Presentation&lt;/h3>
&lt;p>
&lt;i class="fas fa-download pr-1 fa-fw">&lt;/i> Download the
&lt;a href="https://issues-osu.github.io/ISSUESlab/ISSUESlab/uploads/Innovations-in-Spatial-and-Data-Driven-Firearm-Risk.pdf" target="_blank">presentation here&lt;/a>
.&lt;/p></description></item><item><title>An assessment of opioid overdose mortality risk across the urban–rural continuum: Integrating satellite-derived and socioeconomic indicators</title><link>https://issues-osu.github.io/ISSUESlab/event/apha-2026-presentation-6/</link><pubDate>Wed, 04 Nov 2026 10:45:00 +0000</pubDate><guid>https://issues-osu.github.io/ISSUESlab/event/apha-2026-presentation-6/</guid><description>&lt;p>&lt;strong>Session:&lt;/strong> Built environment and community-based approaches to advancing health equity&lt;br>
&lt;strong>Program:&lt;/strong> Public Health Education and Health Promotion&lt;br>
&lt;strong>Date:&lt;/strong> Wednesday, November 4, 2026 | 10:45 AM – 11:00 AM&lt;/p></description></item></channel></rss>