The health benefits of exposure to trees and plants is a rapidly expanding field of study. Research has shown that exposure is associated with improvements in a wide range of health outcomes including cardiovascular disease, birth outcomes, respiratory disease, cancer, mental health and all-cause mortality¹. One of the challenges that these studies face is characterizing participants’ exposure to trees and plants. A common approach is to use the normalized difference vegetation index, a greenness index typically derived from satellite imagery. Reliance on the normalized difference vegetation index is understandable; for decades, the imagery required to calculate the normalized difference vegetation index has been available for the entire Earth’s surface and is updated at regular intervals. However, the normalized difference vegetation index may do a poor job of fully characterizing the human experience of being exposed to trees and plants, because scenes with the same normalized difference vegetation index value can appear different to the human eye. We demonstrate this phenomenon by identifying sites in Portland, Oregon that have the same normalized difference vegetation index value as a large, culturally significant elm tree. These sites are strikingly different aesthetically, suggesting that use of the normalized difference vegetation index may lead to exposure misclassification. Where possible, the normalized difference vegetation index should be supplemented with other exposure metrics.

接触树木和植物对健康的益处是一个迅速扩大的研究领域。研究表明，暴露与多种健康结果的改善有关，包括心血管疾病、出生结果、呼吸系统疾病、癌症、心理健康和全因死亡率¹. 这些研究面临的挑战之一是描述参与者对树木和植物的暴露情况。一种常见的方法是使用归一化差异植被指数，这是一种通常来自卫星图像的绿色指数。依赖归一化的植被指数是可以理解的；几十年来，计算归一化差异植被指数所需的图像一直可用于整个地球表面，并定期更新。然而，归一化差异植被指数可能无法充分表征人类暴露于树木和植物的体验，因为具有相同归一化差异植被指数值的场景在人眼看来可能会有所不同。我们通过识别波特兰的地点来证明这一现象，俄勒冈州与具有文化意义的大型榆树具有相同的归一化差异植被指数值。这些地点在美学上存在显着差异，这表明使用归一化差异植被指数可能会导致暴露错误分类。在可能的情况下，标准化差异植被指数应辅以其他暴露指标。