Planning for Sustainable Green Urbanism: An Empirical Bottom-Up (Community-Led) Perspective on Green Infrastructure (GI) Indicators in Khyber Pakhtunkhwa (KP), Pakistan

Int J Environ Res Public Health. 2022 Sep 20;19(19):11844. doi: 10.3390/ijerph191911844.

Abstract

Rising vulnerability of the urban green infrastructure (UGI) is grabbing global attention, for which inclusive urban landscape and greening policies (ULGP) and frameworks are crucial to support green growth. As such, this research intends to explore the local community's perspective to assemble sustainable UGI indicators for vital taxonomy of the urban green space (UGS) elements, aiming to develop a multi-functional and sustainable UGI-indicator-based framework that is eco-friendly and supports green-resilient cities in Khyber Pakhtunkhwa (KP) province, Pakistan. An in-depth household survey was executed in three KP districts: Charsadda, Peshawar, and Mardan, placing self-administered 192 questionnaires while covering themes around climate change adaptation, urban resilience, and UGI. Relative importance index (RII) and the interquartile range (IQR) methods were set up for data analysis that revealed excellent reliability (α > 0.88) and internal consistency. The results confirmed community-based UGI indicators with a focus on promoting green-energy-saving strategies as e-imp (level 9, RII = 0.915), while other (ten) UGI indicators as important (RII = 0.811-0.894) and (eleven) as moderately important (RII = 0.738-0.792). These UGI indicators were found to be enhanced by UGS elements (RII ≥ 0.70). These findings provide a foundation for urban policy change and the development of a sustainable UGI framework to build an eco-regional paradigm for greener growth.

Keywords: KP, Pakistan; adaptation; climate change; community participation; urban green infrastructure.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cities
  • Climate Change*
  • Pakistan
  • Reproducibility of Results

Grants and funding

This research, as a part of the Ph.D. dissertation, was funded by the Deutscher Akademischer Austauschdienst (DAAD), Government of Germany, grant number 57381412. TU-Dortmund University, Germany, funded the Article Processing Charges (APCs).