A 30m/5d GPP dataset for Hulunbuir, China (2023)

This dataset was generated based on EC-LUE model using harmolized Landsat-Sentinel-2 dataset(HLS) and ERA5-Land dataset. First, the Savitzky-Golay filter was applied to reconstruct time-series Normalized Difference Vegetation Index (NDVI) data with a spatial resolution of 30m and a temporal resolution of 5 days. Then, climate parameters were calculated based on ERA5-Land data. Finally, we computed GPP using EC-LUE model. This dataset contains a total of 49 GeoTiff files, including Hulunbeier's March-October 2023 GPP data with a spatial resolution of 30m and a temporal resolution of 5 days.

本数据集基于EC-LUE模型，结合匀质化Landsat-Sentinel-2数据集（Harmonized Landsat-Sentinel-2，简称HLS）与ERA5-Land数据集生成。首先，采用Savitzky-Golay滤波器对空间分辨率为30米、时间分辨率为5天的时间序列归一化差分植被指数（Normalized Difference Vegetation Index，NDVI）数据进行重构；随后，基于ERA5-Land数据集计算气候参数；最后，通过EC-LUE模型计算总初级生产力（Gross Primary Productivity，GPP）。本数据集共计包含49个GeoTiff格式文件，涵盖呼伦贝尔地区2023年3月至10月的GPP数据，其空间分辨率为30米、时间分辨率为5天。

搜集汇总

背景与挑战

背景概述

该数据集是一个关于中国呼伦贝尔地区2023年3月至10月的30米/5天GPP（总初级生产力）数据集，基于EC-LUE模型生成，包含49个GeoTiff文件，适用于草地生态系统研究。