黄土高原GOSIF的快速变化指数（RCI）数据集（2000-2023年）

GOSIF快速变化指数（RCI）数据集，基于GOSIF数据产品（https://global-ecosystem.s3.dualstack.us-west-2.amazonaws.com/GOSIF/GOSIF_005deg_8day.nc）计算，所用数据为8天合成的日光诱导叶绿素荧光（SIF）数据，空间分辨率为180弧秒。参考Otkin等（2014）提出的快速变化指数（RCI）计算公式，构建SIF-RCI指标，评估植被SIF信号的快速异常变化特征。通过对每个像元构建时间序列正态分布并进行归一化处理，计算得到与输入数据分辨率（180弧秒，约5公里）相同分辨率的GOSIF快速变化指数图。GOSIF快速变化指数数据，是识别和监测突发干旱等快速植被胁迫事件的重要基础数据，同时也是分析植被光合作用动态变化特征的关键指标。GOSIF Rapid Change Index (RCI) dataset is calculated based on the GOSIF data product (https://global-ecosystem.s3.dualstack.us-west-2.amazonaws.com/GOSIF/GOSIF_005deg_8day.nc). The input data is 8-day composite solar-induced chlorophyll fluorescence (SIF) data, with a spatial resolution of 180 arcseconds. Referring to the RCI calculation formula proposed by Otkin et al. (2014), the SIF-RCI index was constructed to evaluate the rapid abnormal change characteristics of vegetation SIF signals. By constructing a time-series normal distribution for each pixel and performing normalization processing, the GOSIF RCI map with the same resolution as the input data (180 arcseconds, approximately 5 km) was generated. The GOSIF RCI dataset is an important foundational data for identifying and monitoring rapid vegetation stress events such as sudden droughts, and also a key indicator for analyzing the dynamic changes of vegetation photosynthesis.

搜集汇总

背景与挑战

背景概述

黄土高原GOSIF的快速变化指数（RCI）数据集（2000-2023年）提供了黄土高原地区植被SIF信号的快速异常变化特征，空间分辨率为5公里，适用于监测突发干旱等植被胁迫事件和分析植被光合作用动态变化。