Residential Landscape Management Practices and Environmental Contributions to ESG

To meet sustainability principles and adhere to environmentally friendly practices, private companies are required to contribute to Environmental, Social, and Governance (ESG). Developing countries in Southeast Asia face significant challenges in implementing ESG within residential areas due to rapid economic growth and urban expansion pressures, even though optimal landscape management—particularly in township-scale residential developments—has the potential to generate substantial contributions, especially to the Environmental (E) dimension. This study aims to examine the relationship between land-use configuration and optimal landscape management practices of two residential clusters with different characteristics in enhancing environmental contributions. Five indicators, such as tree biodiversity, land use, greenhouse gas emissions, waste management, and water sources, were selected to evaluate environmental performance. Descriptive quantitative analysis was used to examine tree diversity data, carbon stock, green open space (GOS) area, the percentage of processed green waste, and water source volume. Both clusters excel in providing GOS (>30% of the total area) and green waste processing (100%), but only achieved a moderate level in tree biodiversity. Cluster B has a higher carbon stock potential (64.53 tons/ha) due to the presence of large-sized and mature trees, while Cluster A excels in water resource provision because of the availability of a lake with a high-water volume. The findings demonstrate that land-use configuration should not only account for the provision of green open spaces but also incorporate blue open spaces to support water self-sufficiency. Plant species selection emerges as a critical factor in enhancing biodiversity and increasing carbon storage capacity. These results underscore the necessity for highly detailed residential landscape management planning, accompanied by regular evaluation, to achieve more optimal environmental contributions.