Table of Contents

ABSTRACT

Urban parks provide social and ecological benefits; yet, numerous parks experience inadequate connection and inconsistent environmental efficacy. This study presents a comprehensive methodology to assess and improve a park’s spatial accessibility while reducing its operating carbon emissions. Employing Central Park in New Damietta City, Egypt, as a case study, we use space syntactic segment analysis (normalized global integration, NAIN; connection) and visibility graph analysis (VGA) to evaluate the current layout against a proposed redesign. We assess daily CO₂ emissions resulting from visitor presence and electricity consumption, employing a genetic algorithm to optimise a combination of locally appropriate tree species that mitigate these emissions within designated planting sites. The results indicate that the mean NAIN climbed from 0.67 to 0.69 (maximum 0.92 to 0.95), while the mean VGA visual integration went from 6.1 to 7.6, suggesting enhanced legibility and visual accessibility of places; the mean connection remained same at 4. The projected “busy-day” total is 25,382.59 kg CO₂/day, and the optimised afforestation strategy fully offsets this amount within site limitations. The paradigm connects spatial measures to implementable environmental strategies, providing a pragmatic approach for enhancing urban parks’ accessibility and ecological resilience.

Keywords: space syntax analysis, environmental impact, axial route selection, urban parks, genetic algorithms