Built-Up Area Changes, Spatial Pattern and Urban Sprawling in Kedungsepur Metropolitan Area
Bibliographic record
Abstract
Kedungsepur is a metropolitan city in Indonesia designated as a national strategic area.With the increasing population, the demand for land for urban activities has also risen, leading to the conversion of undeveloped land into built-up areas.However, few studies have measured land use changes in developing countries, especially in metropolitan areas.This article delves deeper into this subject.While the development of big cities in Indonesia has led to physical expansion, uncontrolled growth has caused urban sprawl in the urban fringe of the core city and suburban areas, as well as in the metropolitan context comprising core and satellite cities. Planning the city's physical growth is crucial to prevent uncontrolled and sporadic urban sprawl.Urban sprawl studies in Indonesian metropolitan areas, particularly those using highresolution satellite images, are still uncommon.This article uses Sentinel 2A imagery to qualitatively interpret urban sprawl patterns and quantitatively analyze spatial patterns using the nearest neighborhood analysis technique in ArcGIS software.The results reveal that the Kedungsepur Metropolitan Area is experiencing a sprawling leapfrog type of urban sprawl.These findings are crucial for monitoring and improving urban spatial planning in the future.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".