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April 4, 2026Remote Sensing2 citationsOpen Access

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

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ZWZiyue WangAKAdhitya Marendra KiloesMAMd. Ali Akber

Key Points

  • The aim is to develop a framework for accurately delineating peri-urban areas through multiple indicators.
  • Developed a multi-dimensional framework using 18 indicators across six analytical dimensions.
  • Integrated data from remote sensing and GIS to create a composite scoring system.
  • Applied the framework to four major cities on Java Island for spatial analysis.
  • Validated findings with expert surveys in 25 districts of Jakarta and Bandung.
  • The framework effectively captured spatial heterogeneity of peri-urban areas.
  • The equal-weighted model showed significant agreement with expert assessments.
  • Statistical analysis indicated strong correlations with expert evaluations (e.g., Pearson's r = 0.517, p = 0.008).

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.

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69d0af1c659487ece0fa4f91https://doi.org/10.3390/rs18071062
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