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Dynamic Assessment of Urban Carrying Capacity Load Number Using the Enhanced UCCLN Model

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  • Marissa Liponhay

    (Analytics Computing and Complex Systems Laboratory (ACCeSs@AIM), Asian Institute of Management, 123 Paseo de Roxas, Makati City 1229, Philippines)

  • Alyssa Valerio

    (Analytics Computing and Complex Systems Laboratory (ACCeSs@AIM), Asian Institute of Management, 123 Paseo de Roxas, Makati City 1229, Philippines)

  • Glydel Fornan

    (Analytics Computing and Complex Systems Laboratory (ACCeSs@AIM), Asian Institute of Management, 123 Paseo de Roxas, Makati City 1229, Philippines)

  • Christian Alis

    (Analytics Computing and Complex Systems Laboratory (ACCeSs@AIM), Asian Institute of Management, 123 Paseo de Roxas, Makati City 1229, Philippines)

  • Christopher Monterola

    (Analytics Computing and Complex Systems Laboratory (ACCeSs@AIM), Asian Institute of Management, 123 Paseo de Roxas, Makati City 1229, Philippines)

Abstract

The sustainability of cities often changes as rapid urban developments and population growth affect the carrying capacity. Understanding the dynamics of carrying capacity becomes crucial for tourist-oriented cities. This study focused on Baguio City, the “Summer Capital of the Philippines”, attracting large crowds on holidays and actively promoting various events on other days, thus having temporal context variations classified as regular days, days with events, and holidays. Using the enhanced urban carrying capacity load number (EUCCLN) model, the changes in the load number (LN) are calculated for different temporal contexts based on spatial indicators grouped into air, traffic, economy and waste. The city experiences the worst pressures on air quality during holidays, with 99.23% of the districts at very high to critical levels, followed by regular days and days with events. However, the total LN during holidays is balanced by favorable economic conditions with only 9.23% of the districts at the critical level. EUCCLN effectively pinpoints areas that are at critical states at any given time, advocating targeted government monitoring. We demonstrate that nighttime light, for places with no available economic data, can be used as a proxy to highlight areas requiring improved urban vibrancy. This work suggests that monitoring urban pressures using EUCCLN can easily be extended to real time with nowcasting indicator data.

Suggested Citation

  • Marissa Liponhay & Alyssa Valerio & Glydel Fornan & Christian Alis & Christopher Monterola, 2023. "Dynamic Assessment of Urban Carrying Capacity Load Number Using the Enhanced UCCLN Model," Sustainability, MDPI, vol. 16(1), pages 1-19, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:35-:d:1303374
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    References listed on IDEAS

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    1. Doll, Christopher N.H. & Muller, Jan-Peter & Morley, Jeremy G., 2006. "Mapping regional economic activity from night-time light satellite imagery," Ecological Economics, Elsevier, vol. 57(1), pages 75-92, April.
    2. Hamed Taherdoost, 2017. "Decision Making Using the Analytic Hierarchy Process (AHP); A Step by Step Approach," Post-Print hal-02557320, HAL.
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