A Multi-Dimensional Indicator Framework for Peri-Urban Area Delineation: Insights from Equal- and AHP-Weighted Models in Java, Indonesia

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Authors: Ziyue Wang, Adhitya Marendra Kiloes, Md. Ali Akber, Bagus Setiabudi Wiwoho, Ammar Abdul Aziz
Cited by: 2
References: 74

Abstract

Peri-urban areas (PUAs), as transitional zones between urban and rural regions, play a critical role in supporting food systems and agricultural livelihoods, yet they are increasingly pressured by rapid urban expansion. Reliable spatial delineation of PUAs remains challenging, as administrative boundaries often fail to capture their functional and spatial heterogeneity. This study proposes a multi-dimensional, spatially explicit framework to delineate peri-urban areas using Indonesia as a case study. Eighteen indicators representing six analytical dimensions—land use/land cover, economic, demographic, infrastructural, spatial accessibility, and landscape structure—were derived from remote sensing and GIS-based data sources and integrated into a composite scoring system using equal-weighted and AHP-weighted approaches. The framework was applied to four major cities on Java Island (Jakarta, Surabaya, Bandung, and Yogyakarta) to generate continuous peri-urban probability surfaces, which were validated using expert surveys across 25 districts in the Jakarta and Bandung metropolitan areas. The results show that the framework effectively captures the spatial heterogeneity and gradients of peri-urban areas, with the equal-weighted approach exhibiting statistically significant agreement with expert assessments (Pearson’s r = 0.517, p = 0.008; Spearman’s ρ = 0.522, p = 0.008; Kendall’s τ = 0.387, p = 0.008), consistently outperforming the AHP-weighted model across all validation metrics. The proposed approach provides a transferable spatial mapping framework for monitoring peri-urban dynamics in rapidly urbanizing regions using remote sensing and GIS.

Fields of Study & Subjects

Urban Agriculture and Sustainability Land Use and Ecosystem Services Soil and Land Suitability Analysis

Publication details

Journal / source
Remote Sensing
Publisher
MDPI AG
Volume
18
Issue
7
Pages
1062–1062
Publication date
2 April 2026
Language
EN