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Record W2981330059 · doi:10.4095/219817

Block Adjustement of Landsat-7 ETM+ Images

2001· report· en· W2981330059 on OpenAlex
Th Toutin, Y Carbonneau, René Chénier

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicSatellite Image Processing and Photogrammetry
Canadian institutionsnot available
Fundersnot available
KeywordsBlock (permutation group theory)Remote sensingComputer scienceComputer graphics (images)GeographyGeologyCartographyMathematicsGeometry

Abstract

fetched live from OpenAlex

This research study shows the potential of large image-block adjustment with nadir viewing sensor images. The method uses the geometric correction system developed for multi-source images at the Canada Centre for Remote Sensing. The results with 15 Landsat-7 ETM+ images show that the same accuracy can be obtained with a large image block than with a single image using the same number of ground control points (GCPs). The number of GCPs depends on cartographic data accuracy to reduce the propagation of GCP error in the least-square block adjustment. To insure consistency and convergence in the block adjustment, strips of same-path and date images has to be generated. Furthermore, elevation tie points (with known elevation value) are used in the overlaps (North-South and East-West) because the viewing-angle differences of overlapping images are small: less than 1º in North-South overlaps and less than 10º in East-West overlaps.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.787
Threshold uncertainty score1.000

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 head0.029
GPT teacher head0.275
Teacher spread0.246 · 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