<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Aerial Imagery on Michael Mommert</title><link>https://mommermi.github.io/tags/aerial-imagery/</link><description>Recent content in Aerial Imagery on Michael Mommert</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Thu, 26 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://mommermi.github.io/tags/aerial-imagery/index.xml" rel="self" type="application/rss+xml"/><item><title>AI-Based Methods for the Detection and Characterization of Traditional Orchards</title><link>https://mommermi.github.io/research/2026_03_26-einsatz_ki-basierter_methoden_zur_detektion_und_charakterisierung_von_streuobstbestaenden/</link><pubDate>Thu, 26 Mar 2026 00:00:00 +0000</pubDate><guid>https://mommermi.github.io/research/2026_03_26-einsatz_ki-basierter_methoden_zur_detektion_und_charakterisierung_von_streuobstbestaenden/</guid><description>&lt;p&gt;Traditional orchards are among the most species-rich habitats in Central Europe. Especially in southern Germany, their loosely scattered, tall-trunked fruit trees have shaped the landscape for centuries. Yet these orchards have been in decline for decades.&lt;/p&gt;
&lt;p&gt;Although traditional orchards are legally protected, there is still no up-to-date and complete overview of where they can actually be found. But exactly this knowledge would be the basis for protecting and maintaining them in a targeted way. Surveying all orchards on foot is hardly feasible given the vast area involved, and it would be far too expensive.&lt;/p&gt;</description></item><item><title>Urban Vegetation Mapping from High-Resolution Aerial Imagery with Deep Learning</title><link>https://mommermi.github.io/research/2026_03_26-urban_vegetation_mapping_from_high-resolution_aerial_imagery_with_deep_learning/</link><pubDate>Thu, 26 Mar 2026 00:00:00 +0000</pubDate><guid>https://mommermi.github.io/research/2026_03_26-urban_vegetation_mapping_from_high-resolution_aerial_imagery_with_deep_learning/</guid><description>&lt;p&gt;Trees, parks, lawns and hedges are more than just pleasant to look
at. Urban greenery helps keep cities cool on hot summer days and soaks
up rainwater that would otherwise flood streets and overwhelm
drains. To plan, manage and protect these green spaces, cities need to
know exactly where vegetation grows. Detailed vegetation maps also
feed into computer simulations that help cities prepare for heat waves
and heavy rainfall.&lt;/p&gt;
&lt;p&gt;Such maps can be created from aerial and satellite images with the
help of artificial intelligence. Until now, however, most of these
approaches have been complex to set up and required powerful,
expensive computers.&lt;/p&gt;</description></item></channel></rss>