Quest of Urban Growth Monitoring from Myth to Reality
Bibliographic record
Abstract
The Earth's surface is changing rapidly, mainly because of the anthropogenic interventions. At many point of times, these changes are local, regional, national, and even global in scale, interconnected both horizontally and vertically. Some changes have natural causes, such as earthquakes or floods. Other changes, such as urban expansion, agricultural intensification, resource extraction, and water resources development are examples of human-induced change that have significant impacts upon people, the economy and resources. As the urban growth in the world as major element of change, the appraisal and monitoring of these areas is a matter of great concern for a quality life of human beings. For this purpose, an appropriate and instantaneous technology is required to monitor the unwanted change. Hence, the main objective of this paper is to monitor the spatial extension of urban growth of the Metropolitan Karachi during 1955-2010 using different data sets and series of satellite imageries. In addition to that the growth corridors have also determined both in terms of magnitude and direction. The spatial change detected through successive satellite imageries has revealed a gigantic change from 1955 to 2010. The averageannual growth rate of the Metropolis has taken place at an outstanding 13.35 %. It has been also found that the increase in urban growth has been noted towards the East and West of the city mainly but due to rapid expansion of housing schemes in north-eastern part of the city an enormous urban growth has taken place there as well. The paper has also revealed the utility of the Geo-Informatics for the monitoring of urban growth.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".