首页> 外文会议>Asian conference on remote sensing >DEPICTION OF CLIMATE ZONES IN THE CONTERMINOUS UNITED STATES USING REMOTE SENSING: APPLICATION TO VULNERABILITY ASSESSMENT AND PUBLIC HEALTH
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DEPICTION OF CLIMATE ZONES IN THE CONTERMINOUS UNITED STATES USING REMOTE SENSING: APPLICATION TO VULNERABILITY ASSESSMENT AND PUBLIC HEALTH

机译:使用遥感描述美国附近的​​气候区:在脆弱性评估和公共健康中的应用

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Identification of areas with comparable weather patterns has the potential to substantially improve forecasting of adverse health outcomes, disturbances in ecosystems, and infrastructure damages caused by extreme meteorological events. We aimed to design informative climate classification for assessing vulnerability and health risks. We proposed to define climate zones for the Conterminous United States using remote sensing and to compare it with the Koppen-Geiger divisions. Using the nationwide database of hospitalizations, maintained by the Centers of Medicare and Medicaid Services, we examined the utility of the unsupervised classification based on a time series of Normalized Difference Vegetation Index (NDVI) to assess vulnerability to extreme weather, defined by the likelihood of extreme cold weather, the number of residents prone to adverse effects, and the rate of severe health outcomes relevant to exposure to cold among older adults. Individual biweekly MODIS NDVI image composites from July 2002 to July 2012 were aggregated, masked, and compiled into a 229-dimensional dataset. Longitudinal and temporal data redundancies were reduced by extracting the first 12 principal components. A "majority" 15×15 convolution was applied to the classification output. Locations of climate zones were determined by k-means unsupervised classification. NDVI-based zones exhibited a high degree of similarity with KSppen-Geiger divisions and a well-defined separation by the annual and seasonal temperature and precipitation values. We determined that relatively warm and humid south eastern region had the largest population at risk (10.9 million) and the highest rate of hospitalizations due to exposure to cold (28.3 cases per 10,000 persons-at-risk). The dry south-western region had the lowest rate of hypothermia hospitalizations (14.6 cases per 10,000 persons-at-risk). Although vulnerability assessment and public health study was limited to a relatively short period 1991-2006 and exposures to cold weather among adults aged 65 and older, the proposed method demonstrates strong potentials for public health applications.
机译:确定具有可比的天气模式的区域有可能大大改善对不利健康结果,生态系统扰动以及极端气象事件造成的基础设施破坏的预测。我们旨在设计信息丰富的气候分类,以评估脆弱性和健康风险。我们建议使用遥感方法为美国本土定义气候区,并将其与Koppen-Geiger分区进行比较。使用由Medicare和Medicaid Services中心维护的全国住院数据库,我们根据标准化差异植被指数(NDVI)的时间序列评估了无监督分类的效用,以评估对极端天气的脆弱性,其定义为极端寒冷的天气,容易受到不良影响的居民人数,以及与老年人暴露于寒冷相关的严重健康后果的比率。将2002年7月至2012年7月的每两周一次的MODIS NDVI图像合成进行汇总,屏蔽和编译为229维数据集。通过提取前12个主要成分,减少了纵向和时间上的数据冗余。将“多数” 15×15卷积应用于分类输出。气候区的位置由k-均值无监督分类确定。基于NDVI的区域与KSppen-Geiger分区显示出高度相似性,并通过年度和季节温度和降水值进行了明确定义的分隔。我们确定相对温暖和潮湿的东南部地区受威胁的人口最多(1,090万),因暴露于寒冷而住院率最高(每10,000人处于危险中28.3例)。西南干旱地区的低温住院治疗率最低(每10,000人中有14.6例处于危险中)。尽管脆弱性评估和公共卫生研究仅限于1991-2006年相对较短的时间,并且65岁及以上的成年人暴露于寒冷的天气中,但所提出的方法显示出在公共卫生应用方面的强大潜力。

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