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The identification and prioritization of locations for neighborhood-scale flood resiliency intervention within the network of basic education facilities (BEF) has not received any attention in past urban planning studies involving cities in developing countries. This analytical gap persists despite the scarce resources among growing cities affecting their pursuit of larger catchment-scale or city-scale interventions. The importance of prioritizing locations for flood resiliency intervention aligns with the global Sustainable Development Goal (SDG) 11 (Sustainable Cities and Communities) and Sendai framework indicators D3 and D6 on reducing the damage to critical infrastructure (educational facilities) and the number of disruptions to basic education services attributed to disasters, respectively. In this context, the research adopted the Kernel Density Estimation (KDE) technique in identifying BEF cluster areas as reference points to compare susceptibility based on flood exposure levels. This approach was tested within the CAMANAVA flood catchment area in Metro Manila, Philippines. Six (6) cluster locations with high KDE value emerged and were consequently ranked based on the overlay of two (2) flood hazard exposure factors or attributes: (1) total student population susceptible and exposed to inundation; and (2) total count of BEF susceptible to inundation. The cluster area with a combined high count of susceptible BEF and high exposure in the student population is considered a top priority location for cost-efficient flood resiliency intervention. The cluster locations with high susceptibility to flood inundation also provide planning information for local government units and the education department in conceptualizing and implementing alternative learning strategies. By integrating KDE and exposure factors, the study demonstrated the importance of spatial scale in urban planning.

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Identification and Ranking of Spatial Clusters of Flood Prone Basic Education Facilities in the CAMANAVA Area, Metro Manila, Philippines Using Kernel Density Estimation Technique and Attribute Overlay Analysis

  • 会议论文

  • 发表日期：

    2025年

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  • Ronnie H. Encarnacion,
  • Dina C. Magnaye,
  • Niña Jeselle S. Magpile,
  • Alvin John A. Pajo

摘要

The identification and prioritization of locations for neighborhood-scale flood resiliency intervention within the network of basic education facilities (BEF) has not received any attention in past urban planning studies involving cities in developing countries. This analytical gap persists despite the scarce resources among growing cities affecting their pursuit of larger catchment-scale or city-scale interventions. The importance of prioritizing locations for flood resiliency intervention aligns with the global Sustainable Development Goal (SDG) 11 (Sustainable Cities and Communities) and Sendai framework indicators D3 and D6 on reducing the damage to critical infrastructure (educational facilities) and the number of disruptions to basic education services attributed to disasters, respectively. In this context, the research adopted the Kernel Density Estimation (KDE) technique in identifying BEF cluster areas as reference points to compare susceptibility based on flood exposure levels. This approach was tested within the CAMANAVA flood catchment area in Metro Manila, Philippines. Six (6) cluster locations with high KDE value emerged and were consequently ranked based on the overlay of two (2) flood hazard exposure factors or attributes: (1) total student population susceptible and exposed to inundation; and (2) total count of BEF susceptible to inundation. The cluster area with a combined high count of susceptible BEF and high exposure in the student population is considered a top priority location for cost-efficient flood resiliency intervention. The cluster locations with high susceptibility to flood inundation also provide planning information for local government units and the education department in conceptualizing and implementing alternative learning strategies. By integrating KDE and exposure factors, the study demonstrated the importance of spatial scale in urban planning.