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Record W2147193204 · doi:10.1115/ipc2004-0390

The Role of Aerial Photograph Interpretation in Natural Hazard and Risk Assessment

2004· article· en· W2147193204 on OpenAlexaffabout
Selina Tribe, Mark Leir

Bibliographic record

Venue2004 International Pipeline Conference, Volumes 1, 2, and 3 · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsBGC Engineering (Canada)
Fundersnot available
KeywordsTerrainAerial photographyPipeline transportHazardAerial photosPipeline (software)Interpretation (philosophy)Aerial surveyComputer scienceRemote sensingNatural (archaeology)Hazard analysisField (mathematics)CartographyGeographyEnvironmental scienceEngineeringArchaeology

Abstract

fetched live from OpenAlex

Aerial photograph interpretation is an accurate and economical method of assessing terrain conditions and natural hazards affecting pipelines and other linear facilities. Completed in advance of vehicle and helicopter-based reconnaissance, it provides a comprehensive site overview that cannot be obtained at ground level. Aerial photograph interpretation helps construct and confirm preliminary hazard and stream-crossing inventories, understand hazard mechanisms, and estimate hazard volume and activity. Time series photo interpretation uses several sets of aerial photographs taken of the same area in different years to track changes in terrain, stream patterns and land-use over time. In addition, aerial photographs are superior navigation tools in the field. These points are illustrated using examples from pipelines in British Columbia and Alberta. This work will be of interest to managers of pipelines throughout western Canada, and to those involved with pipeline route selection through mountainous regions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.297
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

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

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 head0.221
Teacher spread0.218 · 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 teacher head, 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

Citations4
Published2004
Admission routes2
Has abstractyes

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Same venue2004 International Pipeline Conference, Volumes 1, 2, and 3Same topicLandslides and related hazardsFrench-language works237,207