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Discussion papers
https://doi.org/10.5194/essd-2019-110
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2019-110
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: data description paper 21 Aug 2019

Submitted as: data description paper | 21 Aug 2019

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Earth System Science Data (ESSD).

ChinaCropPhen1km: A high-resolution crop phenological dataset for three staple crops in China during 2000–2015 based on LAI products

Yuchuan Luo1, Zhao Zhang1, Yi Chen2, Ziyue Li1, and Fulu Tao2,3 Yuchuan Luo et al.
  • 1State Key Laboratory of Earth Surface Processes and Resource Ecology, Key Laboratory of Environmental Change and Natural Hazards, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • 2Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 3College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

Abstract. Crop phenology provides essential information for land surface phenology dynamics monitoring and modelling, and crop management and production. Most previous studies mainly investigated crop phenology at site scale, however, land surface phenology dynamics monitoring and modelling at a large-scale need a high-resolution spatially explicit information on crop phenology dynamics. In this study, we proposed a method to retrieve 1km-grid crop phenological dataset for three main crops from 2000 to 2015 based on GLASS LAI products. First, we compared three common smoothing methods and chose the most suitable methods for different crops and regions. Then, we developed an optimal filter-based phenology detection (OFP) approach which combined both inflexion- and threshold-based method and detected the key phenological stages of three staple crops at 1km spatial resolution across China. Finally, we established a high resolution gridded-phenology product for three staple crops in China during 2000–2015, named as ChinaCropPhen1km. Compared with the intensive phenological observations from the Agricultural Meteorological Stations of China Meteorological Administration, the dataset had a high accuracy with errors of retrieved phenological date less than 10 days, and represented the spatiotemporal patterns of the observed phenological dynamics at site scale fairly well. The well-validated dataset can be applied for many purposes including improving agricultural system or earth system modelling over a large area.

DOI of the referenced dataset: https://doi.org/10.6084/m9.figshare.8313530 (Luo et al., 2019).

Yuchuan Luo et al.
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ChinaCropPhen1km: A high-resolution crop phenological dataset for three staple crops in China during 2000-2015 based on LAI products Y. Luo, Z. Zhang, Y. Chen, Z. Li, and F. Tao https://doi.org/10.6084/m9.figshare.8313530

Yuchuan Luo et al.
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Short summary
For the first time, we generated a 1-km gridded-phenology product for three staple crops in China during 2000–2015, named as ChinaCropPhen1km. Compared with the phenological observations from the Agricultural Meteorological Stations, the dataset had a high accuracy with errors of retrieved phenological date less than 10 days. The well-validated dataset is sufficiently reliable for many applications including improving the agricultural system or earth system modelling over a large area.
For the first time, we generated a 1-km gridded-phenology product for three staple crops in...
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