Resilience Capacities and Liveability in Algiers: A Morphological Approach
Bibliographic record
Abstract
Cities in North Africa are increasingly affected by extreme urban heat due to climate change and excessive urbanization. Monitoring Land Surface Temperature (LST) and its interactions with urban morphology reveals significant impacts on urban comfort and quality of life, as identified by the Lively City Index (LCI). In this paper, Algiers with its extreme temperature 40 to 45°C and an LCI negatively correlated with LST is used as a case study to develop an analytical methodology linking LST distribution, spectral indices, liveability, and urban morphology to improve urban resilience and liveability. The methodology is based mainly on the use of LST mapping drawn from satellite images to evaluate aspects of urban morphology that mitigate heat effects and help enhance liveability. Based on the significant negative correlation between NDBI and LST, the study demonstrates that urban morphology plays a crucial role in thermal comfort. It also shows that morphological adaptation capacity depends on the level of absorption capacity and the identification of existing adaptation potentials to establish urban resilience to heat and improve liveability.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".