Assessment the Quality of Life in Karachi City through the Integration of Space and Spatial Technologies
Bibliographic record
Abstract
This study is an attempt to map and measure the quality of life in the urban area of Karachi, Pakistan, by using Landsat-7 sensor, Enhanced Thematic Mapper (ETM+) combined with Census data through the state-of-the-art Geographic Information System (GIS). For this purpose, the physical environment of the city is determined by the variables of Normalized Difference Vegetation Index (NDVI), surface temperature and land cover/use. These are extracted from the satellite image data through various techniques of remote sensing. On the other hand, the socioeconomic variables were obtained from the 2000 Karachi District Census Reports, to represent the living environment of the city. Finally, the integration of the physical variables with the socioeconomic variables was conducted in a GIS framework using an aggregated Z Sum score approach, in order to derive the quality of life scores for the city of Karachi on the basis of Administrative-Spatial Units called Union Councils (UCs). The results effectively demonstrated the efficiency of the Index raster techniques to evaluate and map the quality of life over the study area. In addition, the GIS techniques also isolated the contributing variables that may be responsible for the spatial variability in the quality of life.
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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 | 0.002 | 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 | 0.001 |
| 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 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".