• DocumentCode
    2783526
  • Title

    Winter wheat yield estimation model with MODIS normalized near-infrared spectral index

  • Author

    Wenpeng Lin ; Min Zhao ; Yunlong Liu ; Jun Gao ; Chenli Wang

  • Author_Institution
    Dept. of Geogr., Shanghai Normal Univ., Shanghai
  • fYear
    2008
  • fDate
    June 30 2008-July 2 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Terra/MODIS has spectral and spatial resolution advantage over NOAA/AVHRR. To probe into using MODIS near-infrared spectrum further, winter wheat yield estimation was taken as example in Hebei Province, China. Firstly, according to winter wheat biological characteristic, three MODIS near-infrared spectrum data were retrieved in heading stage, which central wavelength is 860 nm, 1240 nm and 1640 nm. Secondly, the normalized near-infrared spectral index (NNSI) is defined by every two near-infrared spectrum, such as (860 nm, 1240 nm), (860 nm, 1640 nm) and (1240 nm, 1640 nm). Thirdly, the statistical correlation analysis with yield were carried on and set up models for yield forecasting with NNSI. The result shows their coefficient correlations are greater than 0.77 and better than with NDVI. Especially the NNSI defined by (860 nm, 1640 nm), its coefficient correlation is 0.815. So NNSI can do well to forecast winter wheat yield. So we can conclude that normalized index in near-infrared spectrum can do better and more reliable than normalized index in visual and near-infrared spectrums for yield forecasting. And given play to the hysperspectral advantage of MODIS, it can service to crop condition monitoring and crop yield estimation of Ministry of Agriculture.
  • Keywords
    agriculture; crops; geophysical techniques; radiometry; statistical analysis; vegetation mapping; China; Hebei Province; MODIS near infrared spectrum; MODIS normalized near infrared spectral index; NNSI; Terra-MODIS; normalized near-infrared spectral index; statistical correlation analysis; wavelength 1240 nm; wavelength 1640 nm; wavelength 860 nm; winter wheat biological characteristics; winter wheat heading stage; winter wheat yield estimation model; yield forecasting; Agriculture; Biological system modeling; Condition monitoring; Crops; Information retrieval; MODIS; Predictive models; Probes; Spatial resolution; Yield estimation; Normalized Near-infrared spectral index; Terra/MODIS; winter wheat; yield estimation with remote sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Earth Observation and Remote Sensing Applications, 2008. EORSA 2008. International Workshop on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2393-4
  • Electronic_ISBN
    978-1-4244-2394-1
  • Type

    conf

  • DOI
    10.1109/EORSA.2008.4620316
  • Filename
    4620316