Ruliana, Rosmini Maru, Zulkifli Rais, Ansari Saleh Ahmar
This study aims to analyze the characteristics of green space in mitigating carbon dioxide (CO2) levels in Makassar City by integrating Structural Equation Modeling (SEM) with Nonparametric Spline methods. Data were collected from 251 observation points, which were mapped using ArcGIS, along with satellite imagery captured between September 27 and October 1, 2024. The data were used to identify land use fractions, including shrub vegetation, non-shrub vegetation, roads, residential areas, and water bodies. The variables analyzed include Net CO2, green space characteristics (shrub and non-shrub fractions), non-green space characteristics (residential, industrial, commercial, road, sea, and drainage systems), and meteorological factors (temperature, humidity, and solar radiation). The results indicate that the optimal model for green space characteristics was found at the knot point 36, with a minimum Generalized Cross Validation (GCV) value of 27,644.53. This model divides the area into two regions: those with less than 36% green space and those with more than 36% green space. An increase in green space is generally associated with a reduction in CO2 levels. Conversely, the best model for non-green space characteristics was found at the knot point 66, with a minimum GCV value of 27,644.18. An increase in non-green space above 66% associated with a significantly greater rise in CO₂ levels. This study provides data-driven recommendations for urban planning and green space management, utilizing statistical modeling and spatial data visualization to inform strategies for reducing CO2 emissions in Makassar City. © 2025, Politeknik Negeri Padang. All rights reserved.
Statistics Study Program, Universitas Negeri Makassar, Makassar, Indonesia; Geography Department, Universitas Negeri Makassar, Makassar, Indonesia
