黄土高原 1km分辨率逐8天GPP-RCI数据集(2001-2020年)
收藏国家地球系统科学数据中心2025-12-31 更新2026-02-07 收录
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黄土高原 1km分辨率逐8天GPP-RCI数据集(2001-2020年)，基于GPP数据产品（https://doi.org/10.5067/MODIS/MOD17A2H.061）计算，所用数据为8天MOD17A2H版6的初级总生产率（GPP）产品，空间分辨率为500米。参考Otkin等（2014）提出的快速变化指数（RCI）计算公式，构建GPP-RCI指标，评估植被GPP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，以及重采样处理计算得到分辨率约1公里的GPP快速变化指数图。GPP快速变化指数数据，是分析植被胁迫的重要基础数据。
The 1km-resolution 8-day composite GPP-RCI dataset for the Loess Plateau (2001–2020) was developed based on the GPP product (https://doi.org/10.5067/MODIS/MOD17A2H.061). The source data is the 8-day MOD17A2H Version 6 Gross Primary Productivity (GPP) product with a spatial resolution of 500 meters. The GPP-RCI index was constructed following the Rapid Change Index (RCI) formula proposed by Otkin et al. (2014) to evaluate rapid anomalous change characteristics of vegetation GPP signals. The ~1-kilometer-resolution GPP Rapid Change Index maps were generated by fitting a normal distribution to the time series of each pixel, performing normalization processing, and conducting resampling operations. The GPP Rapid Change Index data serves as a critical foundational dataset for vegetation stress analysis.
提供机构：
河南理工大学
创建时间：
2025-12-29
