A study on Singapore's vegetation cover and land use change using remote sensing

Goh, Yun Si; Leong, Jing Wen; Yean, Seanglidet; Lee, Bu-Sung; Ngo, Kang Min; Edwards, Peter

doi:10.1145/3557922.3567480

Cited by 2 publications

(1 citation statement)

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“…It is then surmised in the analysis and discussion sections in the form of wellbeing features such as exposure to green visually, noise dampening and comfort. processed them using an object-based approach [40] with Simple Non-Iterative Clustering (SNIC) for feature segmentation, Grey Level Co-occurrence Matrix (GLCM) for texture index extraction, and Random Forest (RF) for nal classi cation, resulted from our previous work [41]. The resulting classi ed image comprised seven categories of land use, allowing us to calculate top-down greenery coverage accurately (See Supplemental Material Figure S1).…”

Section: Methodsmentioning

confidence: 99%

Connecting human wellbeing, urban trees, and greenspace in Singapore: Alternative novel approaches.

Edwards,

Yean,

Goh

et al. 2024

Preprint

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There is growing recognition that urban trees play a vital role in human wellbeing. Singapore, as a “City in a Garden”, provides an interesting case study to examine urban trees and sound attenuation and mobility. Using innovative modelling and spatial data, we examined the placement of trees and the effects of their canopies on noise levels in high rise buildings. We found that tree canopies and multiple layers of vegetation deliver between 1 and 3 db of attenuation. This vegetation also improved shading. Mobility modelling shows that Singaporeans fondness for greenspace and trees continues. Top reasons for park visits includ nature reserves, neighbourhood parks and tourist attractions. Our integration of remote sensing, ecology, and social science is of critical importance in more fully understanding the interconnection and integration of urban greenspace, trees and wellbeing. These insights can enhance decision-making processes, underscoring the value of holistic approaches to sustainable urban development.

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Section: Methodsmentioning

confidence: 99%