Gesause National Park - Phenology MaxposMeanmean (2020)

Abstract: Phenological Annual Summary Statistics based on Ecosystem Functional Attribute framework. The result are based on S2 interpolated with a bayesian implementation of Harmonic Model.Methods: Details of the method can be found in Vicario S, Adamo M, Alcaraz-Segura D, Tarantino C (2019) Bayesian Harmonic Modelling of Sparse and Irregular Satellite Remote Sensing Time Series of Vegetation Indexes: A Story of Clouds and Fires. Remote Sens 12:83 . doi: 10.3390/rs12010083TechnicalInfo: The phenology is not a scalar variable but it is an ensamble of sub-variables all based on MCARI2 vegetation indexand for each one two statistics are given:expected value (mean) and a mask for all pixel with standard deviation of uncertianities larger than 10% the mean (CVmask)within the general name rule proposed:locality_variable_timestamp.extensionvariable formed in:Phenology-SubvariableStatisticsThe subvariables are:mean: mean value across the year - values range between 0-0.5stdintra: standard deviation of the value across the year - values range between 0-0.05maxpos: day of the year of the maximum value - values range between 0-0.5sdinter: standard deviation across years - values range between 0-0.05The statistics are:mean: Expected value of the subvariable across 100 simulationCVmask: 0-1 mask with value 1 for pixel with less than 10% of standard deviation compared to the meanThe timestamp refer to a year or to two years

摘要：基于生态系统功能属性框架的物候年度汇总统计。结果基于S2数据通过贝叶斯实现的谐波模型进行插值。方法：详细方法见Vicario S, Adamo M, Alcaraz-Segura D, Tarantino C (2019)《基于贝叶斯谐波模型的稀疏和不规则卫星遥感植被指数时间序列：云与火的叙事》。遥感12:83。doi: 10.3390/rs12010083技术信息：物候并非一个标量变量，而是由所有基于MCARI2植被指数的子变量组成的集合，对于每一个子变量，提供两个统计数据：期望值（均值）和标准差大于均值10%的所有像素的掩码（CVmask）。在提出的一般名称规则下，变量以：地域_变量_时间戳.扩展名变量的形式形成。子变量包括：均值：全年平均值，值域介于0-0.5之间；stdintra：全年值的标准差，值域介于0-0.05之间；maxpos：最大值对应的年天数，值域介于0-0.5之间；sdinter：跨年的标准差，值域介于0-0.05之间。统计数据包括：均值：子变量在100次模拟中的期望值；CVmask：0-1掩码，值为1表示像素的标准差与均值的比值小于10%。时间戳指代一年或两年。