全球0.05°ENSO事件植被异常变化指数数据集(2010-2020)

植被异常变化指数描述了植被在去除长期的其他因素（如温室效应等）影响下的趋势化变化后，所表现出来的年际或季节异常波动现象。全球ENSO事件植被异常变化指数数据集（2010-2020）将基于MODIS等卫星遥感数据反演的叶面积指数数据作为植被参数数据，根据去趋势化后的植被数据采用标准分数z-score值提取植被异常变化指数，并将该时间段内厄尔尼诺和拉尼娜事件期间的VAI分别按月进行平均，得到厄尔尼诺和拉尼娜两类ENSO事件期间的VAI产品。该数据集的时间覆盖范围为2010-2020年的ENSO事件期间，空间覆盖范围为全球，空间分辨率为0.05°（~5km）。数据集的投影方式为地理投影，存储为*.tif 格式。The Vegetation Abnormality Change Index (VAI) describes the interannual or seasonal abnormal fluctuations of vegetation after eliminating the trending changes driven by long-term confounding factors such as the greenhouse effect. The Global ENSO Event Vegetation Abnormality Change Index Dataset (2010–2020) uses leaf area index (LAI) data retrieved from satellite remote sensing data including MODIS as vegetation parameter data. The VAI is extracted using the standard z-score based on the detrended vegetation data. Then, the VAI values during El Niño and La Niña events within this 2010–2020 period are averaged monthly respectively to obtain the VAI products for the two types of ENSO events (El Niño and La Niña). The temporal coverage of this dataset is during ENSO events from 2010 to 2020, with global spatial coverage and a spatial resolution of 0.05° (~5 km). The dataset adopts geographic projection and is stored in *.tif format.

搜集汇总

背景与挑战

背景概述

该数据集为全球范围2010-2020年ENSO事件期间的植被异常变化指数产品，空间分辨率0.05°（约5公里），基于MODIS等卫星遥感叶面积指数数据，通过去趋势处理和z-score标准化方法计算得出，重点反映厄尔尼诺和拉尼娜事件对植被的异常影响。数据以.tif格式存储，适用于全球生态变化和气候事件研究。