• DocumentCode
    2527877
  • Title

    Assessment of wind-induced environmental lodging stress for maize based on GIS

  • Author

    Mi, Chunqiao ; Zhang, Xiaodong ; Li, Shaoming ; Yang, Jianyu ; Zhu, Dehai ; Yang, Yang ; Liu, Zhe

  • Author_Institution
    Coll. of Inf. & Electr. Eng., China Agric. Univ., Beijing, China
  • fYear
    2011
  • fDate
    June 29 2011-July 1 2011
  • Firstpage
    467
  • Lastpage
    470
  • Abstract
    Lodging in maize is one of the major problems in maize production worldwide. This study is to assess environmental lodging stress for maize based on probability analysis of extreme wind event in maize vegetative stage. A total of 687 growing counties in Huang-Huai-Hai Plain, China were chosen as study area. There were 148 meteorology stations with daily extreme wind speed data in recent 59 years. At first, for each station, the maximum value of daily extreme wind speed in maize vegetative stage (MEWSV for short) was calculated yearly, and the mean and standard deviation of MEWSV in all stations were interpolated into all growing counties. Then, the probability distribution of MEWSV was simulated using Gumbel distribution and Normal distribution, and the result showed that Gumbel distribution was better. At last, for each growing counties, the probability of extreme wind event (that MEWSV was equal or higher than 19m/s) was calculated based on Gumbel distribution, and the assessed stress values were divided into 5 levels and visualized in GIS using a thematic map. It showed us clearly that most growing counties in the northwest of the study area had very severe lodging stress. In order to validate the obtained results, some field survey data were used in current study and it showed that they were consistent in general. But this method using meteorology data to indirectly measure the environmental lodging stress is less costly and more operational than the traditional field-based survey approach, especially when the region to be evaluated is very large. This study can facilitate the identification of better-adapted growing environments, so as to reduce the risk and loss of lodging in maize.
  • Keywords
    geographic information systems; meteorology; normal distribution; probability; China; GIS; Gumbel distribution; Huang-Huai-Hai Plain; MEWSV; maize production; maize vegetative stage; meteorology; normal distribution; probability analysis; wind induced environmental lodging stress; Gaussian distribution; Mathematical model; Stress; Stress measurement; Wind speed; GIS; Gumbel distribution; environmental lodging stress; lodging in maize; wind;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2011 IEEE International Conference on
  • Conference_Location
    Fuzhou
  • Print_ISBN
    978-1-4244-8352-5
  • Type

    conf

  • DOI
    10.1109/ICSDM.2011.5969089
  • Filename
    5969089