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    <title>Geoneon | Case Studies</title>
    <link>https://case-studies.geoneon.com</link>
    <description>Explore Geoneon case studies and see how organisations use geospatial intelligence to map climate risks and support better decisions.</description>
    <language>en</language>
    <pubDate>Sun, 01 Nov 2026 12:11:58 GMT</pubDate>
    <dc:date>2026-11-01T12:11:58Z</dc:date>
    <dc:language>en</dc:language>
    <item>
      <title>Tracking urban heat, canopy and vulnerability across Adelaide</title>
      <link>https://case-studies.geoneon.com/climate-monitoring-adelaide</link>
      <description>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/climate-monitoring-adelaide" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/Geoneon%20Case%20Studies/Adelaide/geoneon-adelaide-heat-susceptibility-hero.png" alt="Tracking urban heat, canopy and vulnerability across Adelaide" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;Local Government&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Individual heat, canopy and demographic datasets show different parts of the urban climate challenge. Decision-makers also need a consistent way to compare those layers across places and reporting periods.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;A pilot across seven metropolitan Adelaide local government areas combined satellite-derived surface-temperature data, tree-canopy classification and vulnerability indicators into a repeatable framework for local comparison and adaptation planning.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Heat, Geoneon Vegetation&lt;/p&gt; 
 &lt;a href="https://smartsatcrc.com/"&gt; smartsatcrc.com &lt;/a&gt; 
&lt;/div&gt;</description>
      <content:encoded>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/climate-monitoring-adelaide" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/Geoneon%20Case%20Studies/Adelaide/geoneon-adelaide-heat-susceptibility-hero.png" alt="Tracking urban heat, canopy and vulnerability across Adelaide" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;Local Government&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Individual heat, canopy and demographic datasets show different parts of the urban climate challenge. Decision-makers also need a consistent way to compare those layers across places and reporting periods.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;A pilot across seven metropolitan Adelaide local government areas combined satellite-derived surface-temperature data, tree-canopy classification and vulnerability indicators into a repeatable framework for local comparison and adaptation planning.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Heat, Geoneon Vegetation&lt;/p&gt; 
 &lt;a href="https://smartsatcrc.com/"&gt; smartsatcrc.com &lt;/a&gt; 
&lt;/div&gt;  
&lt;img src="https://track-ap1.hubspot.com/__ptq.gif?a=7670802&amp;amp;k=14&amp;amp;r=https%3A%2F%2Fcase-studies.geoneon.com%2Fclimate-monitoring-adelaide&amp;amp;bu=https%253A%252F%252Fcase-studies.geoneon.com&amp;amp;bvt=rss" alt="" width="1" height="1" style="min-height:1px!important;width:1px!important;border-width:0!important;margin-top:0!important;margin-bottom:0!important;margin-right:0!important;margin-left:0!important;padding-top:0!important;padding-bottom:0!important;padding-right:0!important;padding-left:0!important; "&gt;</content:encoded>
      <category>Heat</category>
      <category>Local Government</category>
      <category>Vegetation</category>
      <pubDate>Sun, 01 Nov 2026 10:33:11 GMT</pubDate>
      <author>marketing@geoneon.com (Geoneon)</author>
      <guid>https://case-studies.geoneon.com/climate-monitoring-adelaide</guid>
      <dc:date>2026-11-01T10:33:11Z</dc:date>
    </item>
    <item>
      <title>How Geoneon Helped Greater Hobart Monitor Bushfire Exposure Across 94,000+ Buildings</title>
      <link>https://case-studies.geoneon.com/how-geoneon-helped-greater-hobart-monitor-bushfire-exposure-across-94000-buildings</link>
      <description>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/how-geoneon-helped-greater-hobart-monitor-bushfire-exposure-across-94000-buildings" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hs-fs/hubfs/Case%20Studies/Greater%20Hobart%20Bushfire%20Exposure/pacls-greater-hobart-hero.webp?width=1258&amp;amp;height=895&amp;amp;name=pacls-greater-hobart-hero.webp" alt="Bushfire exposure mapping around homes and roads in Greater Hobart." class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;Emergency Management&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Local governments needed consistent spatial evidence to understand where buildings and communities were more exposed to bushfire and where preparedness and mitigation warranted greater attention.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;More than 94,000 buildings across 132 Greater Hobart suburbs assessed, with 4,225 buildings — 4.5% — classified from Moderately High to Extremely High bushfire exposure in the 2024 assessment.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Wildfire&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://www.nema.gov.au/"&gt;National Emergency Management Agency (NEMA)&lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;</description>
      <content:encoded>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/how-geoneon-helped-greater-hobart-monitor-bushfire-exposure-across-94000-buildings" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hs-fs/hubfs/Case%20Studies/Greater%20Hobart%20Bushfire%20Exposure/pacls-greater-hobart-hero.webp?width=1258&amp;amp;height=895&amp;amp;name=pacls-greater-hobart-hero.webp" alt="Bushfire exposure mapping around homes and roads in Greater Hobart." class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;Emergency Management&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Local governments needed consistent spatial evidence to understand where buildings and communities were more exposed to bushfire and where preparedness and mitigation warranted greater attention.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;More than 94,000 buildings across 132 Greater Hobart suburbs assessed, with 4,225 buildings — 4.5% — classified from Moderately High to Extremely High bushfire exposure in the 2024 assessment.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Wildfire&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://www.nema.gov.au/"&gt;National Emergency Management Agency (NEMA)&lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;  
&lt;img src="https://track-ap1.hubspot.com/__ptq.gif?a=7670802&amp;amp;k=14&amp;amp;r=https%3A%2F%2Fcase-studies.geoneon.com%2Fhow-geoneon-helped-greater-hobart-monitor-bushfire-exposure-across-94000-buildings&amp;amp;bu=https%253A%252F%252Fcase-studies.geoneon.com&amp;amp;bvt=rss" alt="" width="1" height="1" style="min-height:1px!important;width:1px!important;border-width:0!important;margin-top:0!important;margin-bottom:0!important;margin-right:0!important;margin-left:0!important;padding-top:0!important;padding-bottom:0!important;padding-right:0!important;padding-left:0!important; "&gt;</content:encoded>
      <category>Wildfire</category>
      <category>Emergency Management</category>
      <pubDate>Sun, 01 Nov 2026 10:32:14 GMT</pubDate>
      <author>marketing@geoneon.com (Geoneon)</author>
      <guid>https://case-studies.geoneon.com/how-geoneon-helped-greater-hobart-monitor-bushfire-exposure-across-94000-buildings</guid>
      <dc:date>2026-11-01T10:32:14Z</dc:date>
    </item>
    <item>
      <title>How Geoneon Helped Prioritise Flood Early-Warning Planning Across Nine Provinces in Lao PDR</title>
      <link>https://case-studies.geoneon.com/laos-flood</link>
      <description>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/laos-flood" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/laos-flood-hero-hires.webp" alt="Flood susceptibility modelling across Lao PDR" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;International Development&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Early warning systems need more than flood hazard maps. Decision-makers also need to understand where buildings, villages, and vulnerable communities are most exposed so preparedness efforts can be prioritised.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Geoneon developed a screening-level flood susceptibility, exposure, vulnerability and risk assessment across nine provinces of Lao PDR. The assessment analysed more than 2.75 million buildings, identifying 310,403 buildings (11.3%) in moderate-to-extreme flood exposure categories, corresponding to more than 0.5 m of modelled flooding, and 30 villages where at least 90% of buildings fell within these categories.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Flood&lt;/p&gt; 
&lt;/div&gt;</description>
      <content:encoded>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/laos-flood" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/laos-flood-hero-hires.webp" alt="Flood susceptibility modelling across Lao PDR" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;International Development&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Early warning systems need more than flood hazard maps. Decision-makers also need to understand where buildings, villages, and vulnerable communities are most exposed so preparedness efforts can be prioritised.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Geoneon developed a screening-level flood susceptibility, exposure, vulnerability and risk assessment across nine provinces of Lao PDR. The assessment analysed more than 2.75 million buildings, identifying 310,403 buildings (11.3%) in moderate-to-extreme flood exposure categories, corresponding to more than 0.5 m of modelled flooding, and 30 villages where at least 90% of buildings fell within these categories.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Flood&lt;/p&gt; 
&lt;/div&gt;  
&lt;img src="https://track-ap1.hubspot.com/__ptq.gif?a=7670802&amp;amp;k=14&amp;amp;r=https%3A%2F%2Fcase-studies.geoneon.com%2Flaos-flood&amp;amp;bu=https%253A%252F%252Fcase-studies.geoneon.com&amp;amp;bvt=rss" alt="" width="1" height="1" style="min-height:1px!important;width:1px!important;border-width:0!important;margin-top:0!important;margin-bottom:0!important;margin-right:0!important;margin-left:0!important;padding-top:0!important;padding-bottom:0!important;padding-right:0!important;padding-left:0!important; "&gt;</content:encoded>
      <category>Flood</category>
      <category>International Development</category>
      <pubDate>Sun, 01 Nov 2026 10:31:21 GMT</pubDate>
      <author>marketing@geoneon.com (Geoneon)</author>
      <guid>https://case-studies.geoneon.com/laos-flood</guid>
      <dc:date>2026-11-01T10:31:21Z</dc:date>
    </item>
    <item>
      <title>Tracking Vegetation Change Across the Pacific Over Time</title>
      <link>https://case-studies.geoneon.com/pacific-vegetation</link>
      <description>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/pacific-vegetation" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/Pacific-Hero.webp" alt="Vegetation-height map of Choiseul Island, Solomon Islands" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;International Development&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Pacific Island countries need consistent and repeatable vegetation data across large and remote regions, but traditional approaches such as LiDAR and field campaigns are difficult to scale and maintain over time.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Geoneon developed a quarterly vegetation height dataset at 10 m resolution using Sentinel-2 imagery, covering multiple Pacific Island countries from 2020 to 2025. The dataset enables vegetation structure mapping and ongoing monitoring of clearing, degradation, and regrowth across the region.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Vegetation&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://digitalearthpacific.org/"&gt; digitalearthpacific.org &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;</description>
      <content:encoded>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/pacific-vegetation" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/Pacific-Hero.webp" alt="Vegetation-height map of Choiseul Island, Solomon Islands" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;International Development&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Pacific Island countries need consistent and repeatable vegetation data across large and remote regions, but traditional approaches such as LiDAR and field campaigns are difficult to scale and maintain over time.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Geoneon developed a quarterly vegetation height dataset at 10 m resolution using Sentinel-2 imagery, covering multiple Pacific Island countries from 2020 to 2025. The dataset enables vegetation structure mapping and ongoing monitoring of clearing, degradation, and regrowth across the region.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Vegetation&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://digitalearthpacific.org/"&gt; digitalearthpacific.org &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;  
&lt;img src="https://track-ap1.hubspot.com/__ptq.gif?a=7670802&amp;amp;k=14&amp;amp;r=https%3A%2F%2Fcase-studies.geoneon.com%2Fpacific-vegetation&amp;amp;bu=https%253A%252F%252Fcase-studies.geoneon.com&amp;amp;bvt=rss" alt="" width="1" height="1" style="min-height:1px!important;width:1px!important;border-width:0!important;margin-top:0!important;margin-bottom:0!important;margin-right:0!important;margin-left:0!important;padding-top:0!important;padding-bottom:0!important;padding-right:0!important;padding-left:0!important; "&gt;</content:encoded>
      <category>Vegetation</category>
      <category>International Development</category>
      <pubDate>Sun, 01 Nov 2026 10:30:28 GMT</pubDate>
      <author>marketing@geoneon.com (Geoneon)</author>
      <guid>https://case-studies.geoneon.com/pacific-vegetation</guid>
      <dc:date>2026-11-01T10:30:28Z</dc:date>
    </item>
    <item>
      <title>Mapping wildfire exposure along critical freight routes in Dundas</title>
      <link>https://case-studies.geoneon.com/wildfire-impact-dundas</link>
      <description>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/wildfire-impact-dundas" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hs-fs/hubfs/Geoneon%20Case%20Studies/Dundas/geoneon-dundas-freight-corridor-hero.png?width=1691&amp;amp;height=1125&amp;amp;name=geoneon-dundas-freight-corridor-hero.png" alt="Side-by-side aerial imagery and mapped freight vulnerability along parallel road and rail corridors near Norseman, Western Australia." class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;Infrastructure &amp;amp; Utilities&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;The Shire of Dundas needed clearer evidence of where important freight routes and supply-chain infrastructure intersected with elevated wildfire conditions.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Spatial analysis identified corridor sections exposed to elevated modelled wildfire conditions, providing an evidence base for preparedness, access review and prioritisation.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Wildfire&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://www.dundas.wa.gov.au/"&gt; www.dundas.wa.gov.au &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;</description>
      <content:encoded>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/wildfire-impact-dundas" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hs-fs/hubfs/Geoneon%20Case%20Studies/Dundas/geoneon-dundas-freight-corridor-hero.png?width=1691&amp;amp;height=1125&amp;amp;name=geoneon-dundas-freight-corridor-hero.png" alt="Side-by-side aerial imagery and mapped freight vulnerability along parallel road and rail corridors near Norseman, Western Australia." class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;Infrastructure &amp;amp; Utilities&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;The Shire of Dundas needed clearer evidence of where important freight routes and supply-chain infrastructure intersected with elevated wildfire conditions.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Spatial analysis identified corridor sections exposed to elevated modelled wildfire conditions, providing an evidence base for preparedness, access review and prioritisation.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Wildfire&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://www.dundas.wa.gov.au/"&gt; www.dundas.wa.gov.au &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;  
&lt;img src="https://track-ap1.hubspot.com/__ptq.gif?a=7670802&amp;amp;k=14&amp;amp;r=https%3A%2F%2Fcase-studies.geoneon.com%2Fwildfire-impact-dundas&amp;amp;bu=https%253A%252F%252Fcase-studies.geoneon.com&amp;amp;bvt=rss" alt="" width="1" height="1" style="min-height:1px!important;width:1px!important;border-width:0!important;margin-top:0!important;margin-bottom:0!important;margin-right:0!important;margin-left:0!important;padding-top:0!important;padding-bottom:0!important;padding-right:0!important;padding-left:0!important; "&gt;</content:encoded>
      <category>Wildfire</category>
      <category>Infrastructure &amp; Utilities</category>
      <pubDate>Sun, 01 Nov 2026 10:29:35 GMT</pubDate>
      <author>marketing@geoneon.com (Geoneon)</author>
      <guid>https://case-studies.geoneon.com/wildfire-impact-dundas</guid>
      <dc:date>2026-11-01T10:29:35Z</dc:date>
    </item>
    <item>
      <title>Mapping Tree Canopy to Support Urban Greening Decisions in Hobart</title>
      <link>https://case-studies.geoneon.com/mapping-tree-canopy-hobart</link>
      <description>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/mapping-tree-canopy-hobart" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/Geoneon%20Case%20Studies/Hobart/geoneon-hobart-canopy-hero.png" alt="Satellite imagery of Hobart with mapped tree canopy highlighted in teal" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;Local Government&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;The City of Hobart needed a consistent, city-wide baseline to understand where tree canopy was distributed, how it changed between 2017 and 2022, and where urban greening efforts should be prioritised.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Geoneon’s satellite-based canopy mapping supported the City of Hobart’s State of the Canopy report with comparable 2017 and 2022 evidence. The City reported a two per cent loss of canopy on private land, while public-land canopy remained broadly stable, and used suburb and planning-zone breakdowns to guide targeted urban greening.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Vegetation&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://www.hobartcity.com.au/"&gt; www.hobartcity.com.au &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;</description>
      <content:encoded>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/mapping-tree-canopy-hobart" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/Geoneon%20Case%20Studies/Hobart/geoneon-hobart-canopy-hero.png" alt="Satellite imagery of Hobart with mapped tree canopy highlighted in teal" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;Local Government&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;The City of Hobart needed a consistent, city-wide baseline to understand where tree canopy was distributed, how it changed between 2017 and 2022, and where urban greening efforts should be prioritised.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Geoneon’s satellite-based canopy mapping supported the City of Hobart’s State of the Canopy report with comparable 2017 and 2022 evidence. The City reported a two per cent loss of canopy on private land, while public-land canopy remained broadly stable, and used suburb and planning-zone breakdowns to guide targeted urban greening.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Vegetation&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://www.hobartcity.com.au/"&gt; www.hobartcity.com.au &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;  
&lt;img src="https://track-ap1.hubspot.com/__ptq.gif?a=7670802&amp;amp;k=14&amp;amp;r=https%3A%2F%2Fcase-studies.geoneon.com%2Fmapping-tree-canopy-hobart&amp;amp;bu=https%253A%252F%252Fcase-studies.geoneon.com&amp;amp;bvt=rss" alt="" width="1" height="1" style="min-height:1px!important;width:1px!important;border-width:0!important;margin-top:0!important;margin-bottom:0!important;margin-right:0!important;margin-left:0!important;padding-top:0!important;padding-bottom:0!important;padding-right:0!important;padding-left:0!important; "&gt;</content:encoded>
      <category>Local Government</category>
      <category>Vegetation</category>
      <pubDate>Sun, 01 Nov 2026 10:28:37 GMT</pubDate>
      <author>marketing@geoneon.com (Geoneon)</author>
      <guid>https://case-studies.geoneon.com/mapping-tree-canopy-hobart</guid>
      <dc:date>2026-11-01T10:28:37Z</dc:date>
    </item>
    <item>
      <title>How Geoneon Helped Launceston Build the Evidence Base for Its Urban Greening Strategy</title>
      <link>https://case-studies.geoneon.com/launceton-urban-forest-strategy</link>
      <description>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/launceton-urban-forest-strategy" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/launceston-canopy-hero.webp" alt="Urban canopy classification across Launceston" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;Local Government&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;The City of Launceston needed a clearer way to respond to rising heatwave risk and the urban heat island effect, especially where lower canopy cover overlapped with more vulnerable populations.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Geoneon established a 2021 canopy baseline of 19.5% across an 85.2 km² urban and peri-urban project area, analysed land surface temperature and population vulnerability, and identified priority areas for urban greening. The evidence helped lay the foundation for the City’s Urban Greening Strategy.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Heat, Geoneon Vegetation&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://www.launceston.tas.gov.au/"&gt; www.launceston.tas.gov.au/ &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;</description>
      <content:encoded>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/launceton-urban-forest-strategy" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/launceston-canopy-hero.webp" alt="Urban canopy classification across Launceston" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;Local Government&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;The City of Launceston needed a clearer way to respond to rising heatwave risk and the urban heat island effect, especially where lower canopy cover overlapped with more vulnerable populations.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Geoneon established a 2021 canopy baseline of 19.5% across an 85.2 km² urban and peri-urban project area, analysed land surface temperature and population vulnerability, and identified priority areas for urban greening. The evidence helped lay the foundation for the City’s Urban Greening Strategy.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Heat, Geoneon Vegetation&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://www.launceston.tas.gov.au/"&gt; www.launceston.tas.gov.au/ &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;  
&lt;img src="https://track-ap1.hubspot.com/__ptq.gif?a=7670802&amp;amp;k=14&amp;amp;r=https%3A%2F%2Fcase-studies.geoneon.com%2Flaunceton-urban-forest-strategy&amp;amp;bu=https%253A%252F%252Fcase-studies.geoneon.com&amp;amp;bvt=rss" alt="" width="1" height="1" style="min-height:1px!important;width:1px!important;border-width:0!important;margin-top:0!important;margin-bottom:0!important;margin-right:0!important;margin-left:0!important;padding-top:0!important;padding-bottom:0!important;padding-right:0!important;padding-left:0!important; "&gt;</content:encoded>
      <category>Heat</category>
      <category>Local Government</category>
      <category>Vegetation</category>
      <pubDate>Sun, 01 Nov 2026 10:27:54 GMT</pubDate>
      <author>marketing@geoneon.com (Geoneon)</author>
      <guid>https://case-studies.geoneon.com/launceton-urban-forest-strategy</guid>
      <dc:date>2026-11-01T10:27:54Z</dc:date>
    </item>
    <item>
      <title>Identifying 24,221 Buildings with Higher Wildfire Exposure: How Bhutan Prioritised Wildfire Preparedness</title>
      <link>https://case-studies.geoneon.com/bhutan-wildfire-preparedness</link>
      <description>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/bhutan-wildfire-preparedness" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/Geoneon%20Website%202026/Case%20Studies/Bhutan/bhutan-wildfire-hero.webp" alt="Wildfire severity map across Bhutan’s mountainous terrain" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;International Development&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Bhutan needed a clear way to see where wildfire risk overlaps with communities and buildings, so authorities could prioritise preparedness and mitigation.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Geoneon developed the Bhutan Forest Fire Exposure Index, assessing more than 400,000 buildings and identifying 24,221 — 5.9% of buildings assessed — classified from Relatively High to Extremely High forest fire exposure.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Wildfire&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://ofs.dofps.gov.bt/"&gt; ofs.dofps.gov.bt/ &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;</description>
      <content:encoded>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/bhutan-wildfire-preparedness" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hubfs/Geoneon%20Website%202026/Case%20Studies/Bhutan/bhutan-wildfire-hero.webp" alt="Wildfire severity map across Bhutan’s mountainous terrain" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;International Development&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Bhutan needed a clear way to see where wildfire risk overlaps with communities and buildings, so authorities could prioritise preparedness and mitigation.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Geoneon developed the Bhutan Forest Fire Exposure Index, assessing more than 400,000 buildings and identifying 24,221 — 5.9% of buildings assessed — classified from Relatively High to Extremely High forest fire exposure.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Geoneon Wildfire&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://ofs.dofps.gov.bt/"&gt; ofs.dofps.gov.bt/ &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;  
&lt;img src="https://track-ap1.hubspot.com/__ptq.gif?a=7670802&amp;amp;k=14&amp;amp;r=https%3A%2F%2Fcase-studies.geoneon.com%2Fbhutan-wildfire-preparedness&amp;amp;bu=https%253A%252F%252Fcase-studies.geoneon.com&amp;amp;bvt=rss" alt="" width="1" height="1" style="min-height:1px!important;width:1px!important;border-width:0!important;margin-top:0!important;margin-bottom:0!important;margin-right:0!important;margin-left:0!important;padding-top:0!important;padding-bottom:0!important;padding-right:0!important;padding-left:0!important; "&gt;</content:encoded>
      <category>Wildfire</category>
      <category>International Development</category>
      <pubDate>Sun, 01 Nov 2026 10:19:05 GMT</pubDate>
      <author>marketing@geoneon.com (Geoneon)</author>
      <guid>https://case-studies.geoneon.com/bhutan-wildfire-preparedness</guid>
      <dc:date>2026-11-01T10:19:05Z</dc:date>
    </item>
    <item>
      <title>Mapping multi-hazard infrastructure exposure in Bhutan</title>
      <link>https://case-studies.geoneon.com/bhutan-infrastructure-vulnerability</link>
      <description>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/bhutan-infrastructure-vulnerability" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hs-fs/hubfs/Geoneon%20Case%20Studies/Bhutan%20Infrastructure/geoneon-bhutan-infrastructure-hero-clean.png?width=1730&amp;amp;height=844&amp;amp;name=geoneon-bhutan-infrastructure-hero-clean.png" alt="Three-dimensional value-weighted flood exposure view of infrastructure around Phuentsholing, Bhutan" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;International Development&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Bhutan needed a consistent regional view of where buildings, roads and power infrastructure intersected with flood and slope-instability susceptibility.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Across approximately 400 km², mapped infrastructure, susceptibility classes and replacement-value estimates were combined into value-weighted screening layers for closer investigation and planning.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Custom Climate Risk Analysis&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://www.dlgdm.gov.bt/"&gt; www.dlgdm.gov.bt/ &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;</description>
      <content:encoded>&lt;div class="hs-featured-image-wrapper"&gt; 
 &lt;a href="https://case-studies.geoneon.com/bhutan-infrastructure-vulnerability" title="" class="hs-featured-image-link"&gt; &lt;img src="https://case-studies.geoneon.com/hs-fs/hubfs/Geoneon%20Case%20Studies/Bhutan%20Infrastructure/geoneon-bhutan-infrastructure-hero-clean.png?width=1730&amp;amp;height=844&amp;amp;name=geoneon-bhutan-infrastructure-hero-clean.png" alt="Three-dimensional value-weighted flood exposure view of infrastructure around Phuentsholing, Bhutan" class="hs-featured-image" style="width:auto !important; max-width:50%; float:left; margin:0 15px 15px 0;"&gt; &lt;/a&gt; 
&lt;/div&gt; 
&lt;div class="geoneon-case-overview"&gt; 
 &lt;p&gt;&lt;strong&gt;Industry&lt;/strong&gt;&lt;br&gt;International Development&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Challenge&lt;/strong&gt;&lt;br&gt;Bhutan needed a consistent regional view of where buildings, roads and power infrastructure intersected with flood and slope-instability susceptibility.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;br&gt;Across approximately 400 km², mapped infrastructure, susceptibility classes and replacement-value estimates were combined into value-weighted screening layers for closer investigation and planning.&lt;/p&gt; 
 &lt;p&gt;&lt;strong&gt;Key Product&lt;/strong&gt;&lt;br&gt;Custom Climate Risk Analysis&lt;/p&gt; 
 &lt;p&gt;&lt;a href="https://www.dlgdm.gov.bt/"&gt; www.dlgdm.gov.bt/ &lt;/a&gt;&lt;/p&gt; 
&lt;/div&gt;  
&lt;img src="https://track-ap1.hubspot.com/__ptq.gif?a=7670802&amp;amp;k=14&amp;amp;r=https%3A%2F%2Fcase-studies.geoneon.com%2Fbhutan-infrastructure-vulnerability&amp;amp;bu=https%253A%252F%252Fcase-studies.geoneon.com&amp;amp;bvt=rss" alt="" width="1" height="1" style="min-height:1px!important;width:1px!important;border-width:0!important;margin-top:0!important;margin-bottom:0!important;margin-right:0!important;margin-left:0!important;padding-top:0!important;padding-bottom:0!important;padding-right:0!important;padding-left:0!important; "&gt;</content:encoded>
      <category>Flood</category>
      <category>International Development</category>
      <pubDate>Sun, 01 Nov 2026 10:14:12 GMT</pubDate>
      <author>marketing@geoneon.com (Geoneon)</author>
      <guid>https://case-studies.geoneon.com/bhutan-infrastructure-vulnerability</guid>
      <dc:date>2026-11-01T10:14:12Z</dc:date>
    </item>
  </channel>
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