A FRAMEWORK FOR MEASURING GEOSPATIAL AMENITY ACCESSIBILITY IN THE PHILIPPINES
With rapid urbanization, Philippine urban planners and the government face concerns on attaining economic growth and development amidst the growing spatial inequality to social infrastructures, housing imbalances, and inadequate services to urban dwellers. A necessary step to mitigate these issues i...
Guardado en:
| Autores principales: | , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/16f72b9c58e34018851e47fe17d80ecc |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | With rapid urbanization, Philippine urban planners and the government face concerns on attaining economic growth and development amidst the growing spatial inequality to social infrastructures, housing imbalances, and inadequate services to urban dwellers. A necessary step to mitigate these issues is to study spatial characteristics with adequate and robust data, which is hardly available in developing countries. In line with this, the paper introduces a framework for measuring geospatial amenity accessibility, using Hansen’s gravitation model with the acquired amenities data from OpenStreetMap implemented as Project OHANA (Open-source Heatmap and Analytics for Nationwide Amenities Accessibility in the Philippines). Amenity accessibility findings are discussed for the Philippine regions and disaggregated analysis for the National Capital Region. Validations are made through observations and related literature. To further highlight the applicability of incorporating amenity accessibility data, two use cases were made: (1) on the local government revenue and amenity accessibility relationship, and (2) on concerns to equity of health amenity accessibility across the elderly population. While the findings match with country observations and related literature, the researchers suggest further enhancement of the framework through incorporation of demand and weight factors, and refinements to data inputs and processing to improve the accuracy of analyses. |
|---|