Spatiotemporal measurement of urbanization levels based on multiscale units: A case study of the Bohai Rim Region in China
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
Urbanization is a complex process reflecting the growth, formation and development of cities and their systems. Measuring regional urbanization levels within a long time series may ensure healthy and harmonious urban development. Based on DMSP/OLS nighttime light data, a human—computer interactive boundary correction method was used to obtain information about built-up urban areas in the Bohai Rim region from 1992 to 2012. Consequently, a method was proposed and applied to measure urbanization levels using four measurement scale units: administrative division, land-sea location, terrain feature, and geomorphological types. Our conclusions are: 1) The extraction results based on DMSP/OLS nighttime light data showed substantial agreement with those obtained using Landsat TM/ETM+ data on spatial patterns. The overall accuracy was 97.70% on average, with an average Kappa of 0.79, indicating that the results extracted from DMSP/OLS nighttime light data were reliable and could well reflect the actual status of built-up urban areas. 2) Bohai Rim’s urbanization level has increased significantly, demonstrating a high annual growth rate from 1998 to 2006. Areas with high urbanization levels have relocated evidently from capital to coastal cities. 3) The distribution of built-up urban areas showed a certain degree of zonal variation. The urbanization level was negatively correlated with relief amplitude and altitude. A high level of urbanization was found in low altitude platforms and low altitude plains, with a gradual narrowing of the gap between these two geomorphological types. 4) The measurement method presented in this study is fast, convenient, and incorporates multiple perspectives. It would offer various directions for urban construction and provide reference values for measuring national-level urbanization.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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