• Spectroscopy and Spectral Analysis
  • Vol. 41, Issue 1, 257 (2021)
Sha ZHANG1、1, Yun BAI1、1, Qi LIU1、1, De-ming TONG1、1, Zhen-tian XU1、1, Na ZHAO1、1, Zhao-xue WANG1、1, Xiao-peng WANG1、1, Yong-sha LI1、1, and Jia-hua ZHANG1、1
Author Affiliations
  • 1[in Chinese]
  • 11. School of Automation, Qingdao University, Qingdao 266071, China
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    DOI: 10.3964/j.issn.1000-0593(2021)01-0257-08 Cite this Article
    Sha ZHANG, Yun BAI, Qi LIU, De-ming TONG, Zhen-tian XU, Na ZHAO, Zhao-xue WANG, Xiao-peng WANG, Yong-sha LI, Jia-hua ZHANG. Estimations of Winter Wheat Yields in Shandong Province Based on Remote Sensed Vegetation Indices Data and CASA Model[J]. Spectroscopy and Spectral Analysis, 2021, 41(1): 257 Copy Citation Text show less

    Abstract

    Accurate estimation of regional winter wheat yields is of great significance for understanding the agricultural production status and ensuring national food security. Light use efficiency (LUE) model is one of the most used models for crop yield estimation, however an important parameter, maximum light use efficiency (ξmax), still remains large uncertainties, and whether the crop ξmax changes along with time is also to be explored. In this paper, Savitzky-Golay (S-G) method is used to filter the time-series moderate resolution imaging spectroradiometer (MODIS) vegetation indices data, and a quadratic difference method and a spectral mutation method are used to extract the winter wheat planted areas during 2000—2015 in Shandong Province. Then a fixed ξmax and a changed ξmax are used to drive the CASA (the Carnegie-Ames-Stanford approach) model for years from 2000 to 2016 respectively. Using harvest index (HI) and winter wheat planted areas, the winter wheat yield during 2000—2016 in Shandong Province are obtained, to explore the effect of ξmax on estimating winter wheat yield. The results show that the filtered time-series vegetation indices data capture the spectral features of winter wheat during the growth stages, and the extracted method used in this paper shows a good universal property. The extracted winter wheat planted areas agree well with the planted areas from statistical yearbooks at the city level, and the determination coefficient (R2) between those reaches 0.71, which indicates the extracted winter wheat planted areas are reliable in this paper. The R2 between statistical yields and yields estimated with a changed ξmax is 0.32, which is higher than that between statistical yields and yields estimated with a fixed ξmax. This indicates that the ξmax of winter wheat is changed along with time, and the varieties replacement of winter wheat may be responsible for this. Both the statistical and estimated yields of winter wheat during 2000—2016 show increasing trends with increasing rates of 93.12 and 149.79 kg·hm-2·a-1, respectively. The winter wheat yields in the western Shandong province are overall higher than those in the eastern study area.
    Sha ZHANG, Yun BAI, Qi LIU, De-ming TONG, Zhen-tian XU, Na ZHAO, Zhao-xue WANG, Xiao-peng WANG, Yong-sha LI, Jia-hua ZHANG. Estimations of Winter Wheat Yields in Shandong Province Based on Remote Sensed Vegetation Indices Data and CASA Model[J]. Spectroscopy and Spectral Analysis, 2021, 41(1): 257
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