Estimating winter wheat yield by assimilation of remote sensing data with a four-dimensional variation algorithm considering anisotropic background error and time window
Estimating winter wheat yield by assimilation of remote sensing data with a four-dimensional variation algorithm considering anisotropic background error and time window
复制标题
考虑各向异性背景误差和时间窗的四维变分算法同化遥感数据估算冬小麦产量
DOI：
10.1016/j.agrformet.2021.108345
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发表时间：
2021-05
影响因子：
6.2
通讯作者：
Sun Liang
中科院分区：
文献类型：
--
作者：
Wu Shangrong;Yang Peng;Chen Zhongxin;Ren Jianqiang;Li He;Sun Liang
为进一步提高区域冬小麦估产精度，在En 4DVar算法的基础上，引入变异时间窗，构建了各向异性背景误差-时间窗四维变异（ABT-4DVar）算法。通过与单点尺度和典型试验区的非同化作物产量模拟结果的比较，验证了ABT-4DVar算法的有效性和可行性。在此基础上，以官方统计数据为验证数据，将ABT-4DVar算法应用于区域尺度的冬小麦估产系统中，将遥感叶面积指数同化到WOFOST（WOrld FOod STudies）作物生长模型中。衡水市冬小麦估产结果表明，平均估产与官方统计的误差为3.18%，11个县平均估产与官方统计的误差均在14.80%以内。衡水市冬小麦估产结果表明，ABT-4DVAR算法在区域估产中具有良好的性能，同化算法可为作物生长评价和产量模拟提供技术支持。
To further improve the yield estimation accuracy of regional winter wheat, based on En4DVar algorithm, an anisotropic background error and time window four-dimensional variation (ABT-4DVar) algorithm was constructed by introducing a variation time window. Based on a comparison with the simulated crop yield without data assimilation at a single point scale and in a typical test area, the effectiveness and feasibility of the constructed ABT-4DVar algorithm were effectively verified. On this basis, using the official statistics as verification data, the ABT-4DVar algorithm was applied to a winter wheat yield estimation system by assimilating remotely sensed LAI into the WOFOST (WOrld FOod STudies) crop growth model at a regional scale. The yield estimation results of winter wheat in Hengshui city showed that theREbetween the average estimated yield and official statistics was 3.18%, and theREs between the average estimated yields and the official statistics of the 11 counties were all within 14.80%. The yield estimation results of winter wheat in Hengshui city indicated that the ABT-4DVar algorithm had good performance in regional yield estimation and that the assimilation algorithm could provide technology for crop growth evaluation and yield simulation.
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DOI：
10.1109/jstars.2014.2315999
发表时间：
2014-09-01
影响因子：
5.5
作者：
Chakrabarti, Subit;Bongiovanni, Tara;Bayer, Cimelio
通讯作者：
Bayer, Cimelio
影响因子：
6.2
作者：
de Wit, Allard;Duveiller, Gregory;Defourny, Pierre
通讯作者：
Defourny, Pierre
影响因子：
6.2
作者：
Curnel, Yannick;de Wit, Allard J. W.;Defourny, Pierre
通讯作者：
Defourny, Pierre
将 Sentinel-1 和 Sentinel-2 数据获取的土壤水分同化到 WOFOST 模型中以改进冬小麦产量估算
影响因子：
5
作者：
Zhuo Wen;Huang Jianxi;Li Li;Zhang Xiaodong;Ma Hongyuan;Gao Xinran;Huang Hai;Xu Baodong;Xiao Xiangming
通讯作者：
Xiao Xiangming
DOI：
10.3390/rs11030268
发表时间：
2019-01
期刊：
Remote. Sens.
影响因子：
--
作者：
G. Zhou;Xiangnan Liu;Ming Liu
通讯作者：
G. Zhou;Xiangnan Liu;Ming Liu