Urban Green Areas in Jeddah: Enhancing Environmental Sustainability and Weather Conditions
Bibliographic record
Abstract
This study investigates the extent and evolution of urban green areas in Jeddah, Saudi Arabia, emphasizing their role in environmental sustainability and weather conditions. Urban green spaces (UGS) in Jeddah have experienced significant changes due to rapid urbanization, which has diminished their availability and accessibility. Historically, the city’s growth led to the conversion of natural landscapes into built environments, exacerbating the decline in UGS. Recent urban planning policies, including the "Green Saudi Initiative," aim to address these challenges by integrating green infrastructure into urban development. Despite these efforts, the uneven distribution of UGS, influenced by socio-economic factors, remains a critical issue, limiting equitable access and utility. Furthermore, Jeddah’s hot desert climate and urban heat island (UHI) effect compound environmental challenges, affecting urban temperatures, energy consumption, and precipitation patterns. This research aims to review existing literature to understand the impact of UGS on environmental sustainability and explore the barriers and opportunities associated with their development. By examining these aspects, the study seeks to inform future urban planning and policy-making, fostering the creation of resilient and sustainable urban spaces in Jeddah.
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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 | 0.001 |
| Open science | 0.000 | 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".