• DocumentCode
    2882600
  • Title

    To Obtain the Planting Area of Corn Crop Based on MODIS Satellite Data

  • Author

    Zhang, Jiahua ; Feng, Lili ; Yao, Fengmei

  • Author_Institution
    Sch. of Geosci., Yangtze Univ., Jingzhou, China
  • fYear
    2012
  • fDate
    1-3 June 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The MODIS satellite data was used to extract corn planting area in Northeast China (including Heilongjiang, Jilin and Liaoning Provinces) in this paper. The support vector machine (SVM) method was adopted for the classification to extract the distribution of corn in the sampling area through the HJ satellite imageries, the MODIS-EVI data stacked by different time series was masked by the classification results. Then the EVI time series curves of the corn in the sampling area were used to analyze the curve of corn in the sampling area and get the standard curve of corn in Northeast China. The absolute mean distance between MODIS-EVI time series and the standard curve deriving from sampling area was calculated, and the maximum possible corn distribution was obtained considering different thresholds with different regions. Finally, we compared the distribution of corn in Northeast China according to MODIS data results and actual corn distribution in Heilongjiang Province. The result showed that the obtaining precision of corn planting area is about 74%. It is concluded that the MODIS image can be utilized for the extraction of the crop planting area.
  • Keywords
    radiometry; vegetation; EVI time series curves; HJ satellite imageries; Heilongjiang Province; MODIS image; MODIS satellite data; MODIS-EVI data; MODIS-EVI time series; Northeast China; SVM method; corn crop planting area; corn distribution; support vector machine; Agriculture; Data mining; MODIS; Remote sensing; Spatial resolution; Standards; Time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-0872-4
  • Type

    conf

  • DOI
    10.1109/RSETE.2012.6260795
  • Filename
    6260795