UETN - Broadband (BEAD) Challenge

[nathankota]

Benefit Hypothesis:

Assist a fellow state agency in crafting a grant proposal that will benefit the largest number of students.

Acceptance Criteria:

• Proof of concept gap analysis classifying locations into FCC/NTIA speed tiers based on UGRC broadband data
• Compare classification by UGRC broadband data with classification by FCC fabric data
• Perform gap analysis on broader dataset

[nathankota]

Sprint 1 Tasks

• [x] Student data gap analysis within broadband gap analysis

[nathankota]

Sprint 4 Tasks

• Waiting for data and permission to use data from the school districts

• If/when data comes in, it will be a similar process as for the original BSL challenge: do some mapping and provide back to districts/local gov's to determine which points they want to submit in a challenge

• [x] Load and compare each district's data to address pts

• [x] Figure out a way to get an automated first-guess check (geocode against addr pts? spatial distance check of geocoded pts to addr pts?

• [x] Work with Hank and Denise to manually review identified pts

• [ ] ~Prepare files for submission to FCC~

• [ ] ~Upload by 6 Sep 23~

[nathankota]

Sprint 5 Tasks

• [x] Complete review of as many areas as possible
• [x] Prepare and submit challenges

[nathankota]

@jacobdadams do you think the objective is completed and can be closed for Q1? Are there any objectives/"features" for Q2?

[nathankota]

Here's a breakdown of the numbers as requested.

This includes all the districts except Jordan and Davis. As noted, we prioritized the smaller, rural districts first as addresses there are least likely to be captured by other data that feed into the BSL machine. This meant we didn't get to Jordan at all, and only had a chance to look through a few Davis points before the submission deadline. I was able to look at Washington Co SD's addresses, as they include a lot of the rural areas in SW Utah.

Of the 22 LEAs that we investigated, we geocoded a total of 67,869 addresses. 61,436 of these geocoded to within 100 feet of an existing BSL point and were assumed to have an existing BSL point in the fabric.

There were 1,586 address that did not geocode. We set these aside to return to if we had the time, as manually placing a point takes longer than evaluating an existing point. We ran out of time and weren't able to return to these non-geocoding addresses.

This left 4,847 addresses that we evaluated to see if there was an associated BSL or if we needed to add one. Of these, we identified 1,726 addresses to be added.

There were three common types of missing BSLs that we found. First, houses that were straight up missing. This includes mobile home communities that were often missing points for many structures. The student addresses give us evidence to say "add these trailers." Second, sometimes there were BSLs on outbuildings or neighboring structures but not the home itself. We included these in the points to add, but I don't know how successful these challenges will be. Third, there was a lot of new growth in some areas, especially Washington County. This may be caught by CostQuest's automated processes, but hopefully our adding them will insure they get included. A subset of these points are infill development throughout the state where the imagery doesn't show a structure yet, but the presence of both an address point from the county and a student address from the school district provides enough evidence that there should be a point.

Have a great Monday!

Jake Adams Utah Geospatial Resource Center (UGRC) 385-499-0786 jdadams@utah.gov https://gis.utah.gov/