ChinaCropPhen1km a high-resolution crop phenological dataset for three staple crops in China during 2000–2015 based on leaf area index (LAI) products

摘要

Crop phenology provides essential information for monitoring and modeling landsurface phenology dynamics and crop management andproduction. Most previous studies mainly investigated crop phenology at the sitescale; however, monitoring and modeling land surface phenology dynamics ata large scale need high-resolution spatially explicit information on cropphenology dynamics. In this study, we produced a 1 km grid crop phenologicaldataset for three main crops from 2000 to 2015 based on Global Land SurfaceSatellite (GLASS) leaf area index (LAI) products, called ChinaCropPhen1km.First, we compared three common smoothing methods and chose the mostsuitable one for different crops and regions. Then, we developed an optimalfilter-based phenology detection (OFP) approach which combined boththe inflection- and threshold-based methods and detected the key phenologicalstages of three staple crops at 1 km spatial resolution across China.Finally, we established a high-resolution gridded-phenology product forthree staple crops in China during 2000–2015. Compared with the intensivephenological observations from the agricultural meteorological stations(AMSs) of the China Meteorological Administration (CMA), the dataset had highaccuracy, with errors of the retrieved phenological date being less than 10 d, andrepresented the spatiotemporal patterns of the observed phenologicaldynamics at the site scale fairly well. The well-validated dataset can beapplied for many purposes, including improving agricultural-system or earth-system modeling over a large area (DOI of the referenced dataset:https://doi.org/10.6084/m9.figshare.8313530; Luo et al., 2019).