Multitemporal Analysis of Green Spaces in Manila, Philippines through a Green Index
Keywords: Change Detection, 3D Modeling, Urban Sustainability, Land Cover Change, Remote Sensing
Abstract. In a highly urbanizing settlement, such as the City of Manila, the presence of green spaces is crucial in achieving environmental quality objectives and nurturing sustainable local development. This study aimed to identify vegetation and built-up areas within Manila City across multiple remotely sensed images from 2018 to 2024. Sentinel-2 Level-2A products were processed for land cover classification, while canopy and building height datasets were used for three-dimensional analysis. Additionally, the researchers developed a Green Index, based on 3D modeling insights that considered citizen perspectives, area allocations, feature heights, and building density, which would serve as a valuable tool for decision makers in providing insights into the current state of green spaces within the city. Multitemporal analysis was conducted through ENVI's Thematic Change Detection Tool, classifying land cover changes between built- up and vegetation areas. Thematic change detection showed that at least 90% of Manila’s land cover remained unchanged from 2018 to 2024, and less than 2% of the area transitioned between built-up and vegetation classes, suggesting minimal efforts in either developing new green spaces or protecting existing ones. Further analysis using the Green Index revealed that a substantial portion of Manila is dominated by built-up areas with limited nearby vegetation, resulting in predominantly negative values on the green index maps. This finding highlights the urgent need for enhanced urban greening efforts to improve liveability and environmental resilience in Manila.
