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X-WR-CALNAME;VALUE=TEXT:Remote Sensing in Armed Conflicts - Dr. Ollie Ballinger, University College London
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SUMMARY:Remote Sensing in Armed Conflicts - Dr. Ollie Ballinger, University College London
DESCRIPTION:<p>	<strong>Speaker:</strong>  <a href="https://oballinger.github.io/" title="">Dr. Ollie Ballinger</a>, Centre for Advanced Spatial Analysis,  Faculty of the Built Environment, University College London </p><p>	<strong>Abstract:</strong></p><p>	<strong>Part 1: Battle Damage Detection</strong><br>In the context of recent, highly destructive conflicts in Gaza and Ukraine, reliable estimates of building damage are essential for an informed public discourse, human rights monitoring, and humanitarian aid provision. This paper introduces a new method for building damage detection-- the Pixel-Wise T-Test (PWTT). Using a combination of freely-available synthetic aperture radar imagery and statistical change detection, the PWTT generates accurate conflict damage estimates across a wide area at regular time intervals. Despite being simple and lightweight, the algorithm achieves building-level accuracy statistics surpassing state of the art methods that use deep learning and high resolution imagery. </p><p>	<drupal-media data-entity-type="media" data-entity-uuid="203b9397-0c01-4aaf-b823-385d535ccb52" alt="ukraine damage" data-view-mode="hwp_large"></drupal-media><br><br><strong>Part 2: Dark Ship to Ship Transfer Detection</strong><br>Despite extensive research into ship detection via remote sensing, no studies identify ship-to-ship transfers in satellite imagery. Given the importance of transshipment in illicit shipping practices, this is a significant gap. I train a convolutional neural network to accurately detect 4 different types of cargo vessel and two different types of Ship-to-Ship transfer in PlanetScope satellite imagery. I then elaborate a pipeline for the automatic detection of suspected illicit ship-to-ship transfers by cross-referencing satellite detections with vessel borne GPS data. Finally, I apply this method to the Kerch Strait between Ukraine and Russia to identify over 400 dark transshipment events since 2022. </p><p>	<drupal-media data-entity-type="media" data-entity-uuid="e7c6e678-0aed-44e7-9486-aa607c6cea8c" alt="ship transfers" data-view-mode="hwp_medium"></drupal-media></p><p>	The speaker will be remote.</p><p>	Lunch will be served to those in attendance. </p><p>	<a href="https://harvard.zoom.us/j/96945115108?pwd=BPpSXfvjewbqsGzCkB44ZyvGvct6Zs.1" title="">Zoom link </a> for remote attendees.</p><p>	 </p>
LOCATION:1737 Cambridge St, Cambridge, MA.  CGIS North, Knafel Building, Room K450
STATUS:CONFIRMED
DTSTART:20241015T160000Z
DTEND:20241015T170000Z
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