Spatial Modeling of Factors Affecting Building Density: A Case Study of Hamedan City
Notice bibliographique
Résumé
The process of growth and development of Iranian cities indicates that the unbalanced and uncoordinated growth of the city with the lack of planning and inappropriate design has led to the creation of a heterogeneous structure in the cities. Therefore, from the point of view of urban planning, the category of density is one of the most essential tools for controlling and developing the city. The results show that construction in Hamadan does not have a balanced distribution and a regular pattern. This unbalanced process has caused the population and activity to be concentrated in some specific areas, which has left its negative effects and created conditions where only a few areas and neighborhoods are on the path of development and the rest of the areas remain in stagnation and inactivity. The ever-increasing demand for housing, the high profitability of construction in privileged neighborhoods, and the municipality’s income dependence on construction have caused the formation and continuation of a vicious cycle, the result of which is the increase of spatial inequality and injustice in the city of Hamadan.References- Antoniucci, V., & Marella, G. (2018). Is social polarization related to urban density? Evidence from the Italian housing market. Journal of Landscape and Urban planning, 177, 340-349. - Artmann, M., Kohler, M., Meinel, G., Gan, J., & Ioja, I. C. (2017). How smart growth and green infrastructure can mutually support each other—A conceptual framework for compact and green cities. Journal Ecological Indicators, 96, 10-22.- Balram, Sh., & Dragicevic, S. (2005). Attitudes toward urban land use planning: Integrating questionnaire survey and collaborative GIS techniques to improve attitude measurements. 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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».