Measuring Urban Sprawl, Coalescence, and Dispersal: A Case Study of Pordenone, Italy
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
A critical challenge of global change is managing the uncontrolled spread of cities into their surrounding rural and other land. The phenomenon of urban ‘sprawl’ is well known, but it remains controversial because there are no universal definitions about its etiology, nor of the causes and variables related to it. The goal of this study is to depict the temporal trend of sprawl, so as to identify a ‘sprawl signature’ and its evolution for the Italian Province of Pordenone focusing exclusively on spatial dispersion features. Data were compiled from multitemporal remote sensing and used to delimit urban expansion over time. We aim to describe the spatiotemporal patterns associated with urban sprawl using the perspective of the cyclical urban growth theory and focusing on measures that can detect the degree of spatial dispersion during time related to sprawl both in past and projected urban forms. Exactly how the spatiotemporal patterns of urban growth are identified is crucial for urban planners, as knowledge of them allows more efficient calibration of policies to control land-use change in order to satisfy specific needs of the population and prevent the risks and costs related to sprawl.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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