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Detecting and predicting spatial and interannual patterns of temperate forest springtime phenology in the eastern U.S.

机译:检测和预测东方温带森林春天候选的空间和际模式。

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摘要

We performed a diagnostic analysis of AVHRR-NDVI and gridded, temperature data for the deciduous forests of the eastern U.S., calibrating temperature accumulation model with satellite data for 1982–1993. The model predicts interannual variability in onset date based upon year-to-year changes in springtime temperature. RMS error over the period ranges from 6.9 days in the northern portion of the domain to 10.7 days in the south. The analysis revealed a relationship between temperature accumulation and satellite derived onset date (rank correlation = 0.31–0.62). The required temperature accumulation threshold can be expressed as a function of mean temperature (R2 of 0.90) to facilitate predictive analysis of phenological onset, or when remote sensing data are unavailable.
机译:我们对东方美国东部落叶林的AVHRR-NDVI和网格,温度数据进行了诊断分析,校准了1982-1993的卫星数据的温度累积模型。该模型在春季温度变化的年度变化上预测了发病日期的续变度。在域名北部的6.9天内,周期的rms错误范围为10.7天。该分析揭示了温度累积和卫星衍生的发作日期之间的关系(等级相关= 0.31-0.62)。所需的温度累积阈值可以表示为平均温度(R2为0.90)的函数,以便于验证性发作的预测分析,或者遥感数据不可用。

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