Estimations of Winter Wheat Yields in Shandong Province Based on Remote Sensed Vegetation Indices Data and CASA Model
ZHANG Sha1, 2, BAI Yun2*, LIU Qi2, TONG De-ming2, XU Zhen-tian2, ZHAO Na2, WANG Zhao-xue2, WANG Xiao-peng2, LI Yong-sha1, 2, ZHANG Jia-hua3, 4
1. School of Automation, Qingdao University, Qingdao 266071, China
2. Remote Sensing Information and Digital Earth Center, College of Computer Science and Technology, Qingdao University, Qingdao 266071, China
3. College of Earth Planetary Science, University of Chinese Academy of Sciences, Beijing 100049, China
4. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
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.
Key words：Time series remote sensed vegetation indices data; Maximum light use efficiency; Extraction of winter wheat planted areas; Winter wheat yields estimation; Shandong Province
张 莎，白 雲，刘 琦，童德明，徐振田，赵 娜，王兆雪，王霄鹏，李咏沙，张佳华. 遥感植被指数和CASA模型估算山东省冬小麦单产[J]. 光谱学与光谱分析, 2021, 41(01): 257-264.
ZHANG Sha, BAI Yun, LIU Qi, TONG De-ming, XU Zhen-tian, ZHAO Na, WANG Zhao-xue, WANG Xiao-peng, LI Yong-sha, ZHANG Jia-hua. Estimations of Winter Wheat Yields in Shandong Province Based on Remote Sensed Vegetation Indices Data and CASA Model. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(01): 257-264.
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