Merge pull request #193036 from MicrosoftDocs/main

merge main to live, Sunday 4 PM

Author: jborsecnik

articles/orbital/geospatial-reference-architecture.md

@@ -44,7 +44,7 @@ It should be noted as well that many of these options are optional and could be
 
 This pattern takes the approach of using Azure native geospatial capabilities while at the same time taking advantage of some 3rd party tools and open-source software tools.
 
-The most significant difference between this approach and the previous flow diagram is the use of FME on from Safe Software, Inc. which can be acquired from the Azure Marketplace. FME allows geospatial architects to integrate various type of geospatial data which includes CAD (for Azure Maps Creator), GIS, BIM, 3D, point clouds, LIDAR, etc. There are 450+ integration options, and can speed up the creation of many data transformations through its functionality. Implementation, however, is based on the usage of a virtual machine, and has therefore limits in its scaling capabilities. The automation of FME transformations might be reached using FME API calls with the use of Azure Data Factory and/or with Azure Functions. Once the data is loaded in Azure SQL, for example, it can then be served in GeoServer and published as a Web Feature Service (vector) or Web Mapping Tile Service (raster) and visualized in Azure Maps web SDK or analyzed with QGIS for the desktop along with the other [Azure Maps base maps](../azure-maps/supported-map-styles.md).
+The most significant difference between this approach and the previous flow diagram is the use of FME from Safe Software, Inc. which can be acquired from the Azure Marketplace. FME allows geospatial architects to integrate various type of geospatial data which includes CAD (for Azure Maps Creator), GIS, BIM, 3D, point clouds, LIDAR, etc. There are 450+ integration options, and can speed up the creation of many data transformations through its functionality. Implementation, however, is based on the usage of a virtual machine, and has therefore limits in its scaling capabilities. The automation of FME transformations might be reached using FME API calls with the use of Azure Data Factory and/or with Azure Functions. Once the data is loaded in Azure SQL, for example, it can then be served in GeoServer and published as a Web Feature Service (vector) or Web Mapping Tile Service (raster) and visualized in Azure Maps web SDK or analyzed with QGIS for the desktop along with the other [Azure Maps base maps](../azure-maps/supported-map-styles.md).
 
    :::image type="content" source="media/geospatial-3rd-open-source-software.png" alt-text="Diagram of Azure and 3rd Party tools and open-source software." lightbox="media/geospatial-3rd-open-source-software.png":::