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 									<li><a href="https://github.com/mapbox/COGDumper">COGDumper</a> is an open source python library to read COG's internal tiles. It's a lightweigh library which doesn't need GDAL and can be installed with <code>pip install cogdumper</code>.
 									<li><a href="https://maxar.com">Maxar</a> delivers tiled COGs of their satellite imagery through their <a href="https://ard.maxar.com/docs">Analysis Ready Data</a> (ARD) product line. See their <a href="https://blog.maxar.com/earth-intelligence/2021/introducing-maxar-ard-accelerating-the-pixel-to-answer-workflow-with-analysis-ready-data">blog post</a> for more information.</li>
 									<li><a href="https://wiki.orfeo-toolbox.org/index.php/Monteverdi">Monteverdi</a>, the Orfeo ToolBox image viewer, can navigate in remote cloud optimized geotiff out of the box.</li>
-									<li><a href="http://geoserver.org">GeoServer</a> can leverage S3-hosted COGs by using the <a href="https://docs.geoserver.org/latest/en/user/community/cog/index.html">COG Support</a> community module.
+									<li><a href="http://geoserver.org">GeoServer</a> can leverage COGs by using the <a href="https://docs.geoserver.org/latest/en/user/community/cog/cog.html">COG Support</a> community module.
 									<li><a href="http://rasterframes.io/">RasterFrames</a> brings the power of Spark DataFrames to geospatial raster data, and is able to read Cloud Optimized GeoTIFF's using <a href="http://geotrellis.io">GeoTrellis</a>.
 									<li><a href="http://farmshots.com/">Farmshots</a> builds agriculture analytics on top of Planet’s Cloud Optimized GeoTIFF’s, pulling in just the needed field data and serving it up live to their customers.</li>
 									<li><a href="https://eosda.com/">Earth Observing System</a>’s Engine and Land Viewer are both able to leverage Cloud Optimized GeoTIFFs for live web tile serving and on the fly band math.</li>