Liu Zhaoli, Huang Tieqing, Wan Enpu, Zhang Yangzhen. STUDY ON MODEL FOR REMOTE SENSING ESTIMATION OF MAIZE YIELD[J]. Chinese Geographical Science, 1998, 8(2): 161-167.
Citation: Liu Zhaoli, Huang Tieqing, Wan Enpu, Zhang Yangzhen. STUDY ON MODEL FOR REMOTE SENSING ESTIMATION OF MAIZE YIELD[J]. Chinese Geographical Science, 1998, 8(2): 161-167.

STUDY ON MODEL FOR REMOTE SENSING ESTIMATION OF MAIZE YIELD

  • Publish Date: 1998-06-20
  • Through analysis of perpendicular vegetation index (PVI) from combination of visible and near infrared spectrums reflecting the feature of crop reflectance, we come to the conclusion that the index can better indicate crop instantaneous photosynthesis whereas people generally regard it as the representation of crop leaf area index(LAI). Exploration of crop photosynthesis within a day and its period of duration leads to production of photosynthetic vegetation index (PST) that can reflect the whole crop accumulated photosynthesis, which means the total biomass produced by crop, moreover the method simulating PST is put forward by employment of multi temporal spectrum parameters. On the basis of the achievements mentioned above, a new comprehensive model for remote sensing estimation of maize yield is established, which can comprehensively show major physiological actions of maize and the course of its yield formation, organically integrate various effective ways of crop yield estimation. It lays a solid foundation for carrying out remote sensing estimation of maize yield on a large scale.
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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STUDY ON MODEL FOR REMOTE SENSING ESTIMATION OF MAIZE YIELD

Abstract: Through analysis of perpendicular vegetation index (PVI) from combination of visible and near infrared spectrums reflecting the feature of crop reflectance, we come to the conclusion that the index can better indicate crop instantaneous photosynthesis whereas people generally regard it as the representation of crop leaf area index(LAI). Exploration of crop photosynthesis within a day and its period of duration leads to production of photosynthetic vegetation index (PST) that can reflect the whole crop accumulated photosynthesis, which means the total biomass produced by crop, moreover the method simulating PST is put forward by employment of multi temporal spectrum parameters. On the basis of the achievements mentioned above, a new comprehensive model for remote sensing estimation of maize yield is established, which can comprehensively show major physiological actions of maize and the course of its yield formation, organically integrate various effective ways of crop yield estimation. It lays a solid foundation for carrying out remote sensing estimation of maize yield on a large scale.

Liu Zhaoli, Huang Tieqing, Wan Enpu, Zhang Yangzhen. STUDY ON MODEL FOR REMOTE SENSING ESTIMATION OF MAIZE YIELD[J]. Chinese Geographical Science, 1998, 8(2): 161-167.
Citation: Liu Zhaoli, Huang Tieqing, Wan Enpu, Zhang Yangzhen. STUDY ON MODEL FOR REMOTE SENSING ESTIMATION OF MAIZE YIELD[J]. Chinese Geographical Science, 1998, 8(2): 161-167.

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