The Broadband Serviceable Location Fabric (Fabric) is a dataset of all locations in the United States and its Territories where fixed broadband internet access service is or could be installed. The Fabric allows broadband availability data filers, the FCC, and other stakeholders to work from a single, standardized list of locations for the Broadband Data Collection (BDC). Aligning your dataset of locations—including coordinate data submitted to the High Cost Universal Broadband (HUBB) portal as part of USF compliance—with the Fabric is best thought of as a geospatial process. Joining your location data to locations in the Fabric based on the relative proximity of the locations offers the best chance of success. Relying solely on address matching or other non-geospatial processes is likely to produce poor and inaccurate results.
Approach
To align any coordinate-based data to the Fabric, it’s first good to ensure all locations represented in your data meet the FCC’s definition of a BSL. This article, About the Fabric: What a Broadband Serviceable Location (BSL) Is and Is Not, explains what types of locations are BSLs. Any locations in your data that do not meet those specifications will not be included in the Fabric and are unlikely to qualify for FCC High-Cost funding support.
There are multiple ways to match your coordinate data to BSLs in the Fabric, and this article covers one approach. In this example, we use a geospatial process to match a sample of coordinate-based data from the HUBB to the Fabric.
These are the steps we’ll be taking. In GIS software we load both the Fabric data and a list of location data (we’ll use sample data from HUBB). Next, within the GIS software, we join locations from the coordinate-based data—in this case, a sample of locations from the HUBB—to the Fabric based on proximity. The distance you use may vary based on ground conditions or structure types, but, in general, a distance of 10 to 15 meters will find most points that would be situated on the same structure. Finally, we’ll discuss some possible outcomes.
Example – “Join by Nearest” in QGIS
In the example that follows, we get into the details of an approach to align HUBB location data and BSLs in QGIS.
Step 1 – Open QGIS software and add HUBB and BDC data.
Using QGIS software (v. 3.28 was used for this example), select Layer > Data Source Manager > Delimited Text and follow the menus to add the HUBB and BDC points present in your area. In the screenshot below, a green star and blue circle are shown below to differentiate HUBB and BDC points. Your symbols will be different.
Step 2 –"Join attributes by nearest”
In QGIS, navigate to Processing > Toolbox to open the Toolbox. In the Toolbox, select Vector General > Join attributes by nearest.
Step 3 – Adjust Settings
In the Join attributes by nearest tool, start by setting your HUBB points as Input Layer and BDC points as Input Layer 2.
- To associate only the Broadband Serviceable Location (BSL) ID with your HUBB points (without carrying over all the attributes in the Fabric to the output), select the Location ID field in the “Layer 2 fields to copy...” field.
- The Maximum nearest neighbors will default to 1, and Maximum distance will default to “Not set.” With these settings, the tool will identify the single nearest neighbor regardless of how far away the neighboring point is. If you want to limit the possible nearest neighbors to points that are within, say, 10m, set Maximum distance to 0.00009 degrees.
Step 4 – Export a “Joined_layer” table.
After the tool has finished processing, you will see a Joined layer table in your Layers window, at the bottom left of your screen. This is shown below (the other layers shown below, Darke County, etc., will be different for you).
To export the resulting table, right-click the table, and Export it, as shown below.
In the “Save Vector Layer as...” window, select Comma Separated Value [CSV] as the Format type. Give your file an appropriate name and optionally edit the Export name text as shown below, so you can easily identify which IDs belong to HUBB and to BSL location in your exported table.
The resulting table, shown below, will display the BDC ID as “Location ID”. This is the association between HUBB points and BSL Location IDs.
It is important to check the distance between your original point and the matched BSL to ensure you are still able to offer service to the BSL identified within 10 business days for a standard installation fee. Unless you set a distance buffer when adjusting the settings for the Join Attributes by Nearest tool in step 3 above, you may get matches that are beyond 10-15 meters from the point included in your HUBB data.
Possible Outcomes
There are a number of possible outcomes from this process:
- HUBB locations and BSLs are well matched and on the same structures – The image below shows each HUBB location matched one-to-one with a BSL, and that the points are associated with a building footprint on the imagery.
- HUBB locations are not well matched to BSLs – Here, while one HUBB location is well matched to the Fabric, the HUBB location to the north is not on a structure and would not qualify as a BSL.
- Multiple HUBB locations match to a single BSL – In the following example, there are two HUBB locations on the same parcel as a single BSL. Both have the same address and represent the same structure as the BSL. This may be a duplicate entry in the HUBB dataset or it could indicate that there are two units at the same location. The Fabric includes a unit count for each BSL and inaccurate unit counts can be corrected by filing a challenge.
Other Considerations
While not recommended, you may also attempt to address match your data to the Fabric. For more information on that process, please review this article: Address Matching in Excel. Note that using a database process like address matching without geospatial analysis can lead to poor results. For example, the analysis might suggest adding a new BSL to the Fabric rather than updating the address on a location already in the Fabric. Or, if relying on commercially available geocoders to associate the address with specific latitude and longitude, the coordinates might fall on a road or miss any structure and so fail to meet the requirements for a successful challenge. Additionally, there are BSLs in the Fabric that, for one reason or another, lack addresses and which would not be possible to address match, or where the address may be incorrectly assigned.
If you discover locations in your data that you believe to be legitimate BSLs but are not currently in the Fabric, or have updates to other data in the Fabric, this article, How to Submit a Successful Bulk Fabric Challenge, provides guidance on the Bulk Fabric Challenge process. This process can also be used to challenge BSLs already in the Fabric to update the address, unit count, building type and more.