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<oembed><version>1.0</version><provider_name>Inverse Problems Research Group</provider_name><provider_url>https://sites.uef.fi/inverse</provider_url><title>Remote sensing of forest - Inverse Problems Research Group</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="J2vCasAhxS"&gt;&lt;a href="https://sites.uef.fi/inverse/research-areas/remote-sensing-of-forest/"&gt;Remote sensing of forest&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://sites.uef.fi/inverse/research-areas/remote-sensing-of-forest/embed/#?secret=J2vCasAhxS" width="600" height="338" title="&#x201C;Remote sensing of forest&#x201D; &#x2014; Inverse Problems Research Group" data-secret="J2vCasAhxS" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>Remote sensing of forest Global and local environmental changes are modifying forest ecosystems rapidly. The consequences of ecosystem changes on biodiversity, functioning of forests, and provision of ecosystem services are largely unclear. The analysis of ecosystem changes in different spatial scales is scientifically challenging. Reliable data of forest characteristics is a fundamental requirement for analysing [&hellip;]</description><thumbnail_url>https://sites.uef.fi/inverse/wp-content/uploads/sites/43/2020/06/RemoteSensingOfForest_ALS.png</thumbnail_url></oembed>

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