Resources Science ›› 2019, Vol. 41 ›› Issue (1): 176-184.doi: 10.18402/resci.2019.01.16

• Orginal Article • Previous Articles     Next Articles

Filling and comparison of the growth period data of agricultural meteorological stations

Zhe LIU1,2(), Xuli ZAN1,2, Wei LIU1,2, Diyou LIU1,2, Shaoming LI1,2(), Xiaodong ZHANG1,2, Dehai ZHU1,2   

  1. 1. College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    2. Key Laboratory of Remote Sensing for Agri-Hazards, Ministry of Agriculture, Beijing 100083, China
  • Received:2018-01-31 Online:2019-01-25 Published:2019-01-25

Abstract:

Accurate data of growth period are the basis for crop growth and production process information service. The crop growth period data recorded by agricultural meteorological include a lot of growth stage period information missing. Taking the Huang-Huai-Hai summer maize area as an example, this study calculated the accumulated temperature distribution ratio combining with the daily average temperature, and filled the information of the missing stage from 2002 to 2011. Ultimately this method filled the original growth period data of 13.8%, and the error of filling method was characterized. The results demonstrated that the errors in different growth stages were inconsistent, of which the error in milky maturity stage and maturity stage was the largest. In order to compare the difference between the growth period data of agricultural meteorological stations and the national maize regional test data, a variety of interpolation methods were applied to the two sets of data. By comparing MAE (Mean Absolute Error) and RMSE (Root Mean Square Error), we chosen the Ordinary Kriging method. We compared the interpolated insults and defined difference values between [0, 5] indicating a small difference, large difference at (5, 10], and extremely difference at (10, +∞). Our result shows that, with the exception of 2006 and 2007, the majority of the two sets growth period data difference are limited, in which the difference between the two sets of growth period data was the least appeared in 2003, 2005. The difference between the two sets of growth period data was the largest in 2006. In terms of average of multiple years, there is not a significant difference in most parts of the study area, accounting for 53% of the total number of the agricultural meteorological stations. This study can be used in the filling and comparison of growth stages data in other maize growing areas or other crops.

Key words: Huang-Huai-Hai summer maize area, growth period, regional test, spatial interpolation, comparative analysis