Street-view and traditional greenness metrics with adults' sitting time in high-density living in Hong Kong: Comparing associations, air pollution and noise roles, and population heterogeneity

Zhang, Ting; Huang, Bo; Yan, Yizhen; Lin, Yinyi; Wong, Hung; Wong, Samuel Yeung‐Shan; Chung, Roger Yat‐Nork

doi:10.1016/j.scitotenv.2023.161778

Cited by 11 publications

(1 citation statement)

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“…[35]. Applications for object-based image analyses in environmental biology include habitat and land-use mapping [36], environmental and biodiversity monitoring [35,37], as well as water quality monitoring [38]. We hypothesized that common secondary microplastic particles [12] of polypropylene, polyethylene terephthalate, and low-density polyethylene suspended in an aquatic mesocosm under different mixing conditions could be detected using pixel intensities (e.g., red, blue, green, average, and total) extracted from digital images of the water surface.…”

Section: Introductionmentioning

confidence: 99%

Detection of Secondary Microplastics in an Aquatic Mesocosm by Means of Object-Based Image Analysis

Carmona-Valdivieso,

Valdivieso,

Carmona-Galindo

2023

Microplastics

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When plastics are discarded, they do not biodegrade and instead break down over time into progressively smaller particles, termed secondary microplastics, which adversely impact biota and human health as well as persist in the environment for centuries. Our research objective was to evaluate the capabilities of object-based image analyses in detecting compositionally varied microplastics suspended in an aquatic mesocosm under no-slip and turbulent water conditions. We found that the presence of polypropylene, polyethylene terephthalate, and low-density polyethylene microplastic pollution in both single-type and mixed-type suspensions was not detectable by either average red (R), average blue (B), average green (G), or average RBG pixel intensities, but was significantly detectable by means of total RBG pixel intensity from digital imagery of the surface-water. Our findings suggest that object-based image analyses of surface waters to quantify pixel information is better suited for monitoring the presence and absence of suspended microplastics, rather than for the stepwise determination of microplastic concentrations. We propose the development of a smartphone application to facilitate citizen-science monitoring of microplastic contamination as well as comment on future applications utilizing drone imagery to boost cloud-based mapping spatiotemporal plumes.

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