A 30 m annual maize phenology dataset from 1985 to 2020 in China

[摘要] Crop phenology indicators provide essential informationon crop growth phases, which are highly required for agroecosystemmanagement and yield estimation. Previous crop phenology studies were mainlyconducted using coarse-resolution (e.g., 500 m) satellite data, such as themoderate resolution imaging spectroradiometer (MODIS) data. However,precision agriculture requires higher resolution phenology information ofcrops for better agroecosystem management, and this requirement can be metby long-term and fine-resolution Landsat observations. In this study, wegenerated the first national maize phenology product with a fine spatialresolution (30 m) and a long temporal span (1985–2020) in China, using allavailable Landsat images on the Google Earth Engine (GEE) platform. First,we extracted long-term mean phenological indicators using the harmonicmodel, including the v3 (i.e., the date when the third leaf is fullyexpanded) and the maturity phases (i.e., when the dry weight of maize grainsfirst reaches the maximum). Second, we identified the annual dynamics ofphenological indicators by measuring the difference in dates when thevegetation index in a specific year reaches the same magnitude as itslong-term mean. The derived maize phenology datasets are consistent within situ observations from the agricultural meteorological stations and thePhenoCam network. Besides, the derived fine-resolution phenology datasetagrees well with the MODIS phenology product regarding the spatialpatterns and temporal dynamics. Furthermore, we observed a noticeabledifference in maize phenology temporal trends before and after 2000, whichis likely attributable to the changes in temperature and precipitation,which further altered the farming activities. The extracted maize phenologydataset can support precise yield estimation and deepen our understanding ofthe future agroecosystem response to global warming. The data are availableat https://doi.org/10.6084/m9.figshare.16437054 (Niu et al., 2021).

[学科分类] 眼科学