ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume X-5/W4-2025
https://doi.org/10.5194/isprs-annals-X-5-W4-2025-127-2026
https://doi.org/10.5194/isprs-annals-X-5-W4-2025-127-2026
10 Feb 2026
 | 10 Feb 2026

Central Business District Likeliness Determination Using GIS, Volunteered Geographic Information, and Analytic Hierarchy Process: The Case of Quezon City, Philippines

Aaron Jairo D.C. Carrido, Gillian Wyn E. Amba, Cyril H. Guevara, and Alexis Richard C. Claridades

Keywords: Central Business Districts, GIS, Volunteered Geographic Information, AHP, MCDM, Weighted Overlay Analysis

Abstract. Central Business Districts (CBDs) are often described in qualitative terms, focusing on their function as urban centers of commerce, governance, and public activity. However, a standardized, data-driven method to delineate CBDs spatially and quantitatively remains a challenge in urban studies. This study addresses this gap by developing a quantifiable model to assess the likeliness of an area functioning as a CBD, using Quezon City—one of the largest and most economically dynamic cities in the Philippines—as the study area. Eleven (11) indicators were identified as the most significant criteria: proximity to primary roads, government offices, healthcare facilities, marketplaces, commercial establishments, recreational and social facilities, financial institutions, public transportation, average building height and volume, and population density. Using the Analytic Hierarchy Process to assign weights, a Weighted Overlay Analysis was implemented to produce the CBD-Likeliness Map. Results show that 37.19% of the land area of Quezon City exhibits CBD characteristics, the majority of which are non-commercial zones, suggesting economic activity is expanding beyond designated commercial areas. Unlike previous studies that primarily focused on either accessibility or physical morphology using remote sensing data, this study uniquely integrates both spatial configuration and functional characteristics. The result is a replicable framework for CBD likeliness assessment that can contribute to more informed urban policy and land-use planning decisions in rapidly urbanizing contexts.

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