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Record W7106020492 · doi:10.7939/83404

Assessing and rating telecommunication infrastructure by social importance and physical vulnerability to wildfire in Alberta, Canada

2025· dissertation· en· W7106020492 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsResilience (materials science)Vulnerability (computing)PhoneService (business)Critical infrastructureEmergency managementGeographic information systemTelecommunications serviceService provider

Abstract

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Wildfires pose a significant threat to public safety, making effective communication among responding agencies and with the public crucial during escalated wildfire situations. However, telecommunication vulnerabilities to wildfire have been largely overlooked in fire risk and human dimensions research. In Alberta, a significant proportion of telecommunications infrastructure is positioned in fire-prone regions of the province, with over 600 cellular telecommunications sites contained within the Forest Protection Area (FPA). Proactive mitigation measures such as fuel treatments can reduce the potential risk to and build resilience in communication infrastructure, further strengthening the overall resilience of rural and remote communities. Although, with finite resources available, prioritization is needed to effectively mitigate the risk at the most important and vulnerable towers. This study had two primary objectives. First, I investigated telecommunications vulnerabilities to wildfire in Alberta, Canada with the following objectives: (1) determine the extent of cell phone coverage in Alberta in relation to service demand areas (SDAs); (2) identify to what extent telecommunications infrastructure and SDAs are exposed to potential wildfire; and (3) identify SDAs that have high wildfire exposure and potentially limited cell coverage. I used a fire exposure metric, directional vulnerability assessments, and communications viewshed to identify fire-exposed regions that lack telecommunications coverage and identify the infrastructure most at risk within the province of Alberta. Public safety was assessed through the analysis of Service Demand Areas (SDAs) in relation to gaps in telecommunications coverage and fire exposure. Second, I sought to develop a systematic rating system based on physical vulnerability to wildfire and social importance with the goal of providing a framework for rating telecommunication infrastructure based on multiple factors of vulnerability to allow service providers and forest managers to prioritize those for structure protection or build resilience around those that are lacking. A heterogeneous pattern of telecommunications coverage is distributed across the province, influenced by population densities and roads, and obstructed by terrain. A significant number of telecommunications towers were distributed in areas of high fire exposure (n = 186), possessing hundreds of potential pathways viable to fire transmission. Thousands of kilometres of roadway and hiking trails lack sufficient telecommunications coverage in tandem with being exposed to wildfire. The Grande Prairie and Slave Lake Forest Areas are highlighted as containing the greatest number of telecommunications towers that are both physically vulnerable to fire-induced damage and hold a large social importance. This study provides a comprehensive analysis of the current state of the vulnerabilities to wildfire within the telecommunications network in Alberta. Results and findings reported herein may inform wildfire resilience and mitigation plans, fuel treatments, and future improvements of telecommunications infrastructure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.191
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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