Spatial resolution of Normalized Difference Vegetation Index and greenness exposure misclassification in an urban cohort
Spatial resolution of Normalized Difference Vegetation Index and greenness exposure misclassification in an urban cohort
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DOI：
10.1038/s41370-022-00409-w
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发表时间：
2022-01-29
影响因子：
4.5
通讯作者：
Fabian, M. Patricia
中科院分区：
文献类型：
--
作者：
Jimenez, Raquel B.;Lane, Kevin J.;Fabian, M. Patricia
背景：归一化植被指数（NDVI）是环境健康研究中广泛使用的绿色度衡量标准。高空间分辨率 NDVI 已变得越来越可用；目的：量化 NDVI 空间分辨率对绿化暴露错误分类的影响。方法：2016 年，使用来自 MODIS (250 m(2))、Landsat 8 (30 m(2))、Sentinel-2 (10 m(2)) 和国家农业局的 NDVI 对大波士顿地区 31,328 名儿童的绿化暴露进行了评估图像程序（NAIP，1 m(2)）。我们在可靠性评估框架下比较了多个缓冲区大小的连续和分类绿色度估计。使用 NAIP 数据作为参考来评估曝光错误分类。结果：对于较粗分辨率的 NDVI，绿度估计值更大，但曝光分布相似。连续估计显示一致性差且一致性高，而分类估计的一致性从差到强。分辨率差异越大、缓冲区越小、曝光分位数数量越大，曝光错误分类就越高。 MODIS 中改变绿度分位数的参与者比例较高 (11-60%)，其次是 Landsat 8 (6-44%) 和 Sentinel-2 (5-33%)。 意义：绿度暴露评估对 NDVI 的空间分辨率、聚集面积和暴露分位数数量敏感。绿色暴露决策应考虑特定健康结果和操作考虑的相关途径。
BACKGROUND: The Normalized Difference Vegetation Index (NDVI) is a measure of greenness widely used in environmental health research. High spatial resolution NDVI has become increasingly available; however, the implications of its use in exposure assessment are not well understood.OBJECTIVE: To quantify the impact of NDVI spatial resolution on greenness exposure misclassification.METHODS: Greenness exposure was assessed for 31,328 children in the Greater Boston Area in 2016 using NDVI from MODIS (250 m(2)), Landsat 8 (30 m(2)), Sentinel-2 (10 m(2)), and the National Agricultural Imagery Program (NAIP, 1 m(2)). We compared continuous and categorical greenness estimates for multiple buffer sizes under a reliability assessment framework. Exposure misclassification was evaluated using NAIP data as reference.RESULTS: Greenness estimates were greater for coarser resolution NDVI, but exposure distributions were similar. Continuous estimates showed poor agreement and high consistency, while agreement in categorical estimates ranged from poor to strong. Exposure misclassification was higher with greater differences in resolution, smaller buffers, and greater number of exposure quantiles. The proportion of participants changing greenness quantiles was higher for MODIS (11-60%), followed by Landsat 8 (6-44%), and Sentinel-2 (5-33%).SIGNIFICANCE: Greenness exposure assessment is sensitive to spatial resolution of NDVI, aggregation area, and number of exposure quantiles. Greenness exposure decisions should ponder relevant pathways for specific health outcomes and operational considerations.