Dear Colleagues,

Remote sensing has helped providing input parameters and validating model outputs for crop growth simulation models. An integrated crop simulation system has been developed to facilitate the assimilation of moderate resolution (about 1 km) remote sensing data with crop growth simulation models. Remote sensing parameters, such as leaf area index (LAI) and vegetation index can be compared with values simulated from crop models. Remote sensing LAI and vegetation index can also be applied individually or jointly to readjust the input parameters for crop models in order to get a better performance. Users can choose the input variables in the automatic readjustment process, such as planting date, planting density, row space, and nitrogen application. In the initial phase, the system has automated the assimilation of CSM-CERES-Maize with MODIS data and has been successfully applied to estimate regional corn yield in Indiana, USA (Fang et al., 2008, 2011).

For more information, contact
  Hongliang FANG, Ph.D, Professor
  LREIS, Institute of Geographic Sciences and Natural Resources Research
  Chinese Academy of Sciences
  11A Datun Road, Beijing, 100101, China
  Tel: +86 10 6488 8005
  Fax: +86 10 6488 9630
  Email: [log in to unmask]

Thank you for your attention.

Regards,
Hongliang

Fang, H., S. Liang, G. Hoogenboom, 2011. Integration of MODIS products and a crop simulation model for crop yield estimation. International Journal of Remote Sensing, 32(4): 1039-1065.

Fang, H., S. Liang, G. Hoogenboom, J. Teasdale, and M. Cavigelli, 2008. Crop yield estimation through assimilation of remotely sensed data into the CSM-CERES-Maize model. International Journal of Remote Sensing, 29(10): 3011-3032.