<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Projects | ASIL</title><link>https://gge-asil.netlify.app/projects/</link><atom:link href="https://gge-asil.netlify.app/projects/index.xml" rel="self" type="application/rss+xml"/><description>Projects</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sun, 19 May 2024 00:00:00 +0000</lastBuildDate><image><url>https://gge-asil.netlify.app/media/logo.svg</url><title>Projects</title><link>https://gge-asil.netlify.app/projects/</link></image><item><title>Climate Resilience Geospatial Intelligence</title><link>https://gge-asil.netlify.app/projects/climate-resilience-geospatial-intelligence/</link><pubDate>Wed, 04 Mar 2026 00:00:00 +0000</pubDate><guid>https://gge-asil.netlify.app/projects/climate-resilience-geospatial-intelligence/</guid><description>&lt;p&gt;This project applies geospatial intelligence to evaluate climate-related urban risk and adaptation scenarios.&lt;/p&gt;
&lt;h2 id="objectives"&gt;Objectives&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Quantify urban heat and flood vulnerability&lt;/li&gt;
&lt;li&gt;Connect environmental indicators with built-form characteristics&lt;/li&gt;
&lt;li&gt;Produce decision-ready maps and indicators for local partners&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="methods"&gt;Methods&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Satellite and aerial remote sensing&lt;/li&gt;
&lt;li&gt;Terrain and hydrologic modeling&lt;/li&gt;
&lt;li&gt;Machine learning for hazard mapping and trend analysis&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="impact"&gt;Impact&lt;/h2&gt;
&lt;p&gt;The project supports evidence-based adaptation planning for communities and public agencies.&lt;/p&gt;</description></item><item><title>Urban Digital Twin Platform</title><link>https://gge-asil.netlify.app/projects/urban-digital-twin-platform/</link><pubDate>Wed, 04 Mar 2026 00:00:00 +0000</pubDate><guid>https://gge-asil.netlify.app/projects/urban-digital-twin-platform/</guid><description>&lt;p&gt;This project develops scalable workflows for generating and updating urban digital twins from mobile mapping, airborne LiDAR, and optical imagery.&lt;/p&gt;
&lt;h2 id="objectives"&gt;Objectives&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Build LoD2-ready city models for planning and engineering use&lt;/li&gt;
&lt;li&gt;Improve camera-LiDAR registration and quality control&lt;/li&gt;
&lt;li&gt;Support downstream climate, hazard, and infrastructure analytics&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="methods"&gt;Methods&lt;/h2&gt;
&lt;ul&gt;
&lt;li&gt;Multimodal segmentation and feature extraction&lt;/li&gt;
&lt;li&gt;Geometry-aware registration pipelines&lt;/li&gt;
&lt;li&gt;Quality assessment using field and reference datasets&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="impact"&gt;Impact&lt;/h2&gt;
&lt;p&gt;Outputs support municipal planning, emergency preparation, and data-driven infrastructure management.&lt;/p&gt;</description></item></channel></rss>