Chapter Project on Measuring Rural Broadband Complete

Chapter Project on Measuring Rural Broadband Complete

At the beginning of 2017, the San Francisco Bay Area Chapter teamed up with the Geographical Information Center (GIC), California State University, Chico to carry out a research project, “Bridging California’s Rural/Urban Digital Divide with Mobile Broadband”. The project was funded by the generous support of the SF Bay Area ISOC Chapter through the Internet Society’s Beyond the Net funding program. The project was carried out in collaboration with Valley Vision and USDA Rural Development.

This year-long project is now complete, thanks to the hard work of a network of people including:

  • Susan Strachen (GIC, CSU, Chico)
  • Tyler Boyle (GIC, CSU, Chico)
  • Leah Symekher (SF Bay ISOC Chapter Board)
  • Robyn Krock (Valley Vision)
  • Trish Kelly (Valley Vision)
  • Robert Tse (USDA)
  • Susannah Gray (SF Bay ISOC ChapterBoard)
  • Eve Edelson (SF Bay ISOC Chapter Board)
  • Jenna Spagnolo (SF Bay ISOC Chapter Member)
  • Ilda Simao (Internet Society)

Project Report

You can find the Executive Summary below for a quick overview of our findings. Below that, you’ll find the full report.

Executive Summary

The CSU Chico Geographical Information Center, Valley Vision, USDA Rural Development and the San Francisco Bay Area Chapter of the Internet Society collaborated on a research project focused on mobile broadband availability in farm fields to examine two questions:

  • What is the existing service to support precision agriculture needs in farm fields themselves as opposed to nearby public roads where testing typically occurs?
  • How does increasing granularity of testing mobile broadband speeds affect eligibility under the 4 Mbps download/1 Mbps upload threshold for the USDA Rural Utilities Service Community Connect Grant program?

Using the CalSPEED mobile broadband measurement tool developed by CSU Monterey Bay for the California Public Utilities Commission, the project incorporated two phases of testing. Phase 1 focused on a more granular identification of performance characteristics across the rural areas of Yolo County, as compared to the testing grid for the CPUC testing program. In March of 2017, the GIC conducted tests at 155 sites in the areas of Yolo County. The sampling locations were all located on public roads and were intended to identify areas for further testing at the farm field level. Phase 1 identified three areas of low broadband performance, along Highway 16 in western Yolo County (the Capay Valley), along the southern border of Yolo County between Winters and Davis and in the southeastern part of the county in the Sacramento-San Joaquin Delta near Courtland. Phase 2 implemented testing on seven farms within the fields themselves, with five farms located in areas predicted to be low performing by Phase 1 and two farms located in areas predicted to be high performing by Phase 1.

The results indicate a number of important aspects of mobile broadband service in the farm fields. First, for two of the low performance area farms, no single provider offers suitable mobile coverage under California’s standard. These farmers cannot access mobile-based precision agriculture technologies for all of their property unless they establish multiple subscriptions. Given that the adoption rate for sensor-based technologies that can reduce water and chemical input is already so low, these types of barriers only further limit adoption. Second, locations without LTE coverage are more likely to be unserved.

Statistical analysis of the results show that interpolation used for the statewide and Phase 1 testing overstates the availability of mobile speeds meeting the 4 Mbps threshold for the USDA Community Connect Grant program. For the two providers that are typically considered to provide the most robust rural service (AT&T and Verizon), the statewide testing predicted much higher speeds than are actually available for the 0 – 4 Mbps tier. The Phase 1 countywide testing reduced the error for the 0 – 4 Mbps tier in all cases, but the error was still biased to over- predicting speeds. The variation between statewide results, countywide Phase 1 results and farm field Phase 2 results indicate that the USDA eligibility threshold for Community Connects grant funding is much more likely to be accurate at the density used for the Phase 1 testing than at the CPUC statewide testing density.

The results of the testing program raise two policy considerations. The California Public Utilities Commission is the nationwide leader in independent mobile broadband testing. It is, to our knowledge, the only state that conducts scientifically rigorous mobile broadband performance measurements, analyzes the resulting data and publishes reports documenting trends and identifying deficiencies in service. Even with this significant investment of resources by the agency, the data showed improved accuracy can be gained as granularity increases from the statewide testing (1,190 samples over the state of California) to the Phase 1 countywide testing (155 samples over the County of Yolo). The data showed that the granularity was most beneficial when statewide testing indicated very low speeds (below 4/1 Mbps). The challenge in addressing the benefits of granularity is the tradeoff between cost and the value that the increased accuracy would bring. That value is related to the second policy consideration.

The speed threshold of 4 Mbps download/1 Mbps upload is important as it defines eligibility for the USDA RUS Community Connect Grant program. The data indicate that the statewide program is challenged to establish accurate speeds at the very low speed tiers. If USDA RUS utilizes the statewide data to determine eligibility in California, then eligible areas will be erroneously determined ineligible. The discrepancy is likely related to the interpolation calculations that are done between measured sites in the statewide program. Examination of that interpolation is beyond the scope of this project, but future research can use the Yolo County data to assess that methodology. Also, variability of signal across the farm field also indicates that even those areas that might generally provide speeds at 4/1 Mbps can have significant areas where signal is not sufficient to serve production needs. 

Final Project Report

More Information

You can find out more about this project, precision agriculture and how the Internet is changing the farming here.


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