2019
DOI: 10.1016/j.envint.2019.02.008
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Associations of green space metrics with health and behavior outcomes at different buffer sizes and remote sensing sensor resolutions

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Cited by 110 publications
(59 citation statements)
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References 39 publications
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“…However, this is challenging. The most widespread approaches to assessing green space use available land cover datasets, satellite images, or aerial photographs [ 74 , 75 , 76 ] are susceptible to the modifiable areal unit problem (MAUP) [ 77 ]. Varying scales or shapes are employed to represent and measure spatial zones leads to the statistical bias.…”
Section: Discussionmentioning
confidence: 99%
“…However, this is challenging. The most widespread approaches to assessing green space use available land cover datasets, satellite images, or aerial photographs [ 74 , 75 , 76 ] are susceptible to the modifiable areal unit problem (MAUP) [ 77 ]. Varying scales or shapes are employed to represent and measure spatial zones leads to the statistical bias.…”
Section: Discussionmentioning
confidence: 99%
“…The findings of our study revealed that the residents of Kaunas highly scored the quality of their residential neighborhood, specifically noting that public transport met their needs in the district, and that they had good opportunities for walking to reach the city’s green spaces or parks. Data from the PHENOTYPE project showed that the association between different health indices and the NDVI depends on buffer size, possibly due to the visual impact of the green space seen from home [ 38 ]. In Kaunas, about 95% of the citizens see green spaces from home and have convenient access to a city park by walking from homes for 10 min or less.…”
Section: Discussionmentioning
confidence: 99%
“…To ensure a better characterization of green space quality and accessibility, it is suggested to use satellite data combined with data of other analytical tools used for the estimation of indicators of surface greenness. Time-activity based exposure to green space might reduce exposure misclassification [ 38 ].…”
Section: Strengths and Limitations Of The Studymentioning
confidence: 99%
“…locations [20,21]. While circumventing many limitations of administrative areas, there is a lack of consensus on the appropriate buffer size.…”
Section: Gis-based Buffers Centered On People's Residentialmentioning
confidence: 99%
“…Other studies used remote sensing data to capture environmental characteristics (e.g., green space). Although this type of data varies in spatial resolution (ranging from 2 m to 30 m), there seems to be no significant impact of the sensor spatial resolution on identifying the associations with environments [21].…”
Section: Gis-based Buffers Centered On People's Residentialmentioning
confidence: 99%