Geographic Object-based Image Analysis Change Detection in a Shrinking City: Detroit, Michigan, 2014-2018
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.
Bibliographic record
Abstract
<p>Over the last several decades, cities in America’s Rust Belt region have experienced population and economic declines – most notably, the City of Detroit. With increased property vacancies, many residential structures are abandoned and left vulnerable to degradation. In many cases, one of the answers is to demolish the structure, leaving a physical, permanent change to the urban fabric. The following study uses freely available very high-resolution (VHR) aerial ortho photographs to perform a remote sensing analysis through the application of Geographic Object Based Image Analysis (GEOBIA) methods. The research successfully generates the distinction between pervious and impervious land cover, and links those to parcel lot administrative boundaries within the City of Detroit. Additionally, it explores potential challenges and solutions for batch classification when performing change detection analysis using different sensors at varying spatial resolutions in diverse areas within the city.</p>
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it