2000-2019年全国三大粮食作物1km物候数据集

本数据集涵盖了2000-2019年中国玉米、小麦和水稻的三个关键物候期在一年中出现的日期（儒略日，DOY）。基于GLASS LAI遥感产品，利用农业气象站长期观测的物候记录，根据作物物候曲线特征定义了每种作物的三个关键物候期的拐点和峰值，结合拐点法和阈值法识别出LAI特征曲线对应的拐点和峰值，最终得到每个作物像元的关键物候期在一年中出现的日期。基于全国436个农业气象站点近十多年的观测数据对数据集进行验证，三种作物的物候期提取的均方根误差（RMSE）均小于10天。其中，水稻、小麦和玉米关键物候期的RMSE分别为5.3、5.5和6.7天。

This dataset contains the dates (Julian Day, DOY) of the three key phenological periods for maize, wheat and rice across China during 2000–2019. Leveraging the GLASS LAI remote sensing product and long-term phenological records from agro-meteorological stations, the inflection points and peak values corresponding to the three key phenological periods of each crop were defined based on the characteristics of crop phenological curves. By combining the inflection point method and threshold method, the inflection points and peak values of the LAI characteristic curves were identified, and thus the occurrence dates of the key phenological periods for each crop pixel within a year were finally derived. The dataset was validated using observational data from 436 national agro-meteorological stations over the past 10+ years. The root mean square error (RMSE) of phenological period extraction for all three crops was less than 10 days. Specifically, the RMSE values for the key phenological periods of rice, wheat and maize were 5.3, 5.5 and 6.7 days, respectively.

搜集汇总

背景与挑战

背景概述

该数据集提供了2000年至2019年中国玉米、小麦和水稻三大粮食作物在1公里空间分辨率下的关键物候期日期，数据基于GLASS LAI遥感产品并结合地面气象站观测，通过拐点法和阈值法提取，经验证均方根误差小于10天，具有较高的精度和实用性，适用于农业监测、气候变化研究等领域。