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Journal of Integrative Agriculture  2021, Vol. 20 Issue (7): 1958-1968    DOI: 10.1016/S2095-3119(20)63483-9
Special Issue: 农业生态环境-遥感合辑Agro-ecosystem & Environment—Romote sensing
Agro-ecosystem & Environment Advanced Online Publication | Current Issue | Archive | Adv Search |
Winter wheat yield estimation based on assimilated Sentinel-2 images with the CERES-Wheat model
LIU Zheng-chun1, 2, WANG Chao3, BI Ru-tian1, 2, ZHU Hong-fen1, 2, HE Peng1, 2, JING Yao-dong1, 2, YANG Wu-de3
1 College of Resource and Environment, Shanxi Agricultural University, Taigu 030801, P.R.China
2 National Experimental Teaching Demonstration Center for Agricultural Resources and Environment, Shanxi Agricultural University, Taigu 030801, P.R.China
3 College of Agriculture, Shanxi Agricultural University, Taigu 030801, P.R.China
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为有效验证Sentinel-2影像与CERES-Wheat模型同化进而提高区域作物估产的精度,本文以中国黄土高原东南部三个县(襄汾县、新绛县和闻喜县)为研究区,应用集合卡尔曼滤波算法同化Sentinel-2影像反演的LAI和CERES-Wheat模型模拟的LAI,得到冬小麦生长期逐日的LAI同化值。对比改进的层次分析法、熵值法和归一组合赋权法对不同生育期LAI赋权,并与冬小麦实测单产值进行模型构建,进而对作物进行准确估产。研究结果表明:(1)同化LAI遵循了模拟LAI在冬小麦生育期的生长变化趋势,且在Sentinel-2影像反演LAI的修正下,返青期至抽穗-灌浆期的LAI得到提高,乳熟期的LAI下降减缓,更符合冬小麦LAI的实际生长变化情况;(2)基于实测LAI数据的检验表明,同化LAI比模拟值和反演值的RMSE分别降低了0. 43 m2/m2、0.29 m2/m2,同化过程提高了时间序列LAI的估测精度;(3)归一组合赋权法计算的加权同化LAI与实测单产构建的回归模型决定系数最高R2为0.8627,RMSE最小472.92kg/ha,应用此模型对研究区冬小麦进行估产,县域估测平均单产与统计单产相对误差均小于1%,证明高时空分辨率的Sentinel-2数据融入作物模型能得到更高精度的区域估产结果。

Assimilating Sentinel-2 images with the CERES-Wheat model can improve the precision of winter wheat yield estimates at a regional scale.  To verify this method, we applied the ensemble Kalman filter (EnKF) to assimilate the leaf area index (LAI) derived from Sentinel-2 data and simulated by the CERES-Wheat model.  From this, we obtained the assimilated daily LAI during the growth stage of winter wheat across three counties located in the southeast of the Loess Plateau in China: Xiangfen, Xinjiang, and Wenxi.  We assigned LAI weights at different growth stages by comparing the improved analytic hierarchy method, the entropy method, and the normalized combination weighting method, and constructed a yield estimation model with the measurements to accurately estimate the yield of winter wheat.  We found that the changes of assimilated LAI during the growth stage of winter wheat strongly agreed with the simulated LAI.  With the correction of the derived LAI from the Sentinel-2 images, the LAI from the green-up stage to the heading–filling stage was enhanced, while the LAI decrease from the milking stage was slowed down, which was more in line with the actual changes of LAI for winter wheat.  We also compared the simulated and derived LAI and found the assimilated LAI had reduced the root mean square error (RMSE) by 0.43 and 0.29 m2 m–2, respectively, based on the measured LAI.  The assimilation improved the estimation accuracy of the LAI time series.  The highest determination coefficient (R2) was 0.8627 and the lowest RMSE was 472.92 kg ha–1 in the regression of the yields estimated by the normalized weighted assimilated LAI method and measurements.  The relative error of the estimated yield of winter wheat in the study counties was less than 1%, suggesting that Sentinel-2 data with
high spatial-temporal resolution can be assimilated with the CERES-Wheat model to obtain more accurate regional yield estimates.
Keywords:  data assimilation        CERES-Wheat model        Sentinel-2 images        combined weighting method        yield estimation  
Received: 08 April 2020   Accepted: 02 June 2021
Fund: This work was supported by the National Key Research and Development Program of China (2018YFD020040103) and the National Key Research and Development Program of Shanxi Province, China (201803D221005-2).
Corresponding Authors:  Correspondence BI Ru-tian, Tel: +86-354-6288322, E-mail:   
About author:  LIU Zheng-chun, E-mail:

Cite this article: 

LIU Zheng-chun, WANG Chao, BI Ru-tian, ZHU Hong-fen, HE Peng, JING Yao-dong, YANG Wu-de. 2021. Winter wheat yield estimation based on assimilated Sentinel-2 images with the CERES-Wheat model. Journal of Integrative Agriculture, 20(7): 1958-1968.

Becker-Reshef I, Vermote E, Lindeman M, Justice C. 2010. A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data. Remote Sensing of Environment, 114, 1312–1323.
Belgiu M, Csillik O. 2018. Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis. Remote Sensing of Environment, 204, 509–523.
Bellver J A, Mellado V C. 2005. An application of the analytic hierarchy process method in farmland appraisal. Spanish Journal of Agricultural Research, 3, 17–24.
Brisson N, Gary C, Justes E, Roche R, Mary B, Ripoche D, Zimmer D, Sierra J, Bertuzzi P, Burger P, Bussiere F, Cabidoche Y M, Cellier P, Debaeke P, Gaudillére J P, Hénault C, Maraux F, Seguin B, Sinoquet H. 2003. An overview of the crop model STICS. European Journal of Agronomy, 18, 309–332.
Casa R, Varella H, Buis S, Guérif M, Solan B D, Baret F. 2012. Forcing a wheat crop model with LAI data to access agronomic variables: Evaluation of the impact of model and LAI uncertainties and comparison with an empirical approach. European Journal of Agronomy, 37, 1–10.
Chen Y, Zhang Z, Tao F L. 2018. Improving regional winter wheat yield estimation through assimilation of phenology and leaf area index from remote sensing data. European Journal of Agronomy, 101,163–173.
Cheng Z Q, Meng J H, Qiao Y Y, Wang Y M, Dong W Q, Han Y X. 2018. Preliminary study of soil available nutrient simulation using a modified WOFOST model and time-series remote sensing observations. Remote Sensing, 10, 64–85.
Curnel Y, de Wit A J W, Duveiller G, Defourny P. 2011. Potential performances of remotely sensed LAI assimilation in WOFOST model based on an OSS experiment. Agricultural and Forest Meteorology, 151, 1843–1855.
Dente L, Satalino G, Mattia F, Rinaldi M. 2008. Assimilation of leaf area index derived from ASAR and MERIS data into CERES-Wheat model to map wheat yield. Remote Sensing of Environment, 112, 1395–1407.
Diepen C A, Wolf J, Keulen H. 2010. WOFOST: A simulation model of crop production. Soil Use & Management, 5, 16–24.
Dong T F, Liu J G, Qian B D, Zhao T, Jing Q, Geng X Y, Wang J F, Huffman T, Shang J L. 2016. Estimating winter wheat biomass by assimilating leaf area index derived from fusion of Landsat-8 and MODIS data. International Journal of Applied Earth Observation and Geoinformation, 49, 63–74.
Dorigo W A, Zurita-Milla R, de Wit A J W, Brazile J, Singh R, Schaepman M E. 2007. A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling. International Journal of Applied Earth Observation & Geoinformation, 9, 165–193.
Evensen G. 2003. The ensemble kalman filter: Theoretical formulation and practical implementation. Ocean Dynamics, 53, 343–367.
Fang H L, Liang S L, Hoogenboom G. 2011. Integration of MODIS LAI and vegetation index products with the CSM-CERES-Maize model for corn yield estimation. International Journal of Remote Sensing, 32, 1039–1065.
Haboudane D, Miller J R, Pattey E, Zarco-Tejada P, Strachan L B. 2004. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture. Remote Sensing of Environment, 90, 337–352.
Huang J X, Gomez-Dans J L, Huang H, Ma H Y, Wu Q L, Lewis P E, Liang S L, Chen Z X, Xue J H, Wu Y T, Zhao F, Wang J, Xie X H. 2019a. Assimilation of remote sensing into crop growth models: Current status and perspectives. Agricultural and Forest Meteorology, 2019, 276–277.
Huang J X, Ma H Y, Sedano F, Lewis P E, Liang S L, Wu Q L, Su W, Zhang X D, Zhu D H. 2019b. Evaluation of regional estimates of winter wheat yield by assimilating three remotely sensed reflectance datasets into the coupled WOFOST-PROSAIL model. European Journal of Agronomy, 102, 1–13.
Huang J X, Sedano F, Huang Y B, Ma H Y, Li X L, Liang S L, Tian L Y, Zhang X D, Fan J L, Wu W B. 2016. Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation. Agricultural and Forest Meteorology, 216, 188–202.
Jin H A, Li A N, Wang J D, Bo Y C. 2016. Improvement of spatially and temporally continuous crop leaf area index by integration of CERES-Maize model and MODIS data. European Journal of Agronomy, 78, 1–12.
Jones J W, Hoogenboom G, Porter C H, Boote K J, Batchelor W D, Hunt L A, Wilkens P W, Singh U, Gijsman A J, Ritchie J T. 2003. The DSSAT cropping system model. European Journal of Agronomy, 18, 235–265.
Keating B A, Carberry P S, Hammer G L, Probert M E, Robertson M J, Holzworth D, Huth N I, Hargreaves J N G, Meinke H, Hochman Z, McLean G, Verburg K, Snow V, Dimes J P, Silburn M, Wang E, Brown S, Bristow K L, Asseng S, Chapman S, et al. 2003. An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy, 18, 267–288.
Launay M, Guerif M. 2005. Assimilating remote sensing data into a crop model to improve predictive performance for spatial applications. Agriculture Ecosystems & Environment, 111, 321–339.
Li Z H, He J Q, Xu X G, Jin X L, Huang W J, Clark B, Yang G J, Li Z H. 2018. Estimating genetic parameters of DSSAT-CERES model with the GLUE method for winter wheat (Triticum aestivum L.) production. Computers and Electronics in Agriculture, 154, 213–221.
Lobell D B, Asner G P, Ortiz-Monasterio J I, Benning T L. 2003. Remote sensing of regional crop production in the Yaqui Valley, Mexico: Estimates and uncertainties. Agriculture Ecosystems & Environment, 94, 205–220.
Malczewski J. 2000. On the use of weighted linear combination method in GIS: Common and best practice approaches. Transactions in Global Information System, 4, 5–22.
Manna S, Raychaudhuri B. 2020. Retrieval of leaf area index and stress conditions for sundarban mangroves using Sentinel-2 data. International Journal of Remote Sensing, 41, 1019–1039.
Martre P, Wallach D, Asseng S, Ewert F, Jones J W, Rotter R P, Boote K, Ruane A C, Thorburn P J, Cammarano D, Hatfield J L, Rosenzweig C, Aggarwal P K, Angulo C, Basso B, Bertuzzi P, Biernath C, Brisson N, Challinor A, Doltra J, et al. 2015. Multimodel ensembles of wheat growth: many models are better than one. Global Change Biology, 21, 911–925.
Nearing G S, Crow W T, Thorp K R, Moran M S, Reichle R H, Gupta H V. 2012. Assimilating remote sensing observations of leaf area index and soil moisture for wheat yield estimates: An observing system simulation experiment. Water Resources Research, 48, 213–223.
Pohlert T. 2004. Use of empirical global radiation models for maize growth simulation. Agricultural and Forest Meteorology, 126, 47–58.
Rubinstein R. 1999. The cross-entropy method for combinatorial and continuous optimization. Methodology & Computing in Applied Probability, 2, 127–190.
Qu C H, Li X X, Ju H, Liu Q. 2019. The impacts of climate change on wheat yield in the Huang-Huai-Hai Plain of China using DSSAT-CERES-Wheat model under different climate scenarios. Journal of Integrative Agriculture, 18, 1379–1391.
Sun H Y, Wang S F, Hao X M. 2017. An improved analytic hierarchy process method for the evaluation of agricultural water management in irrigation districts of north China. Agricultural Water Management, 179, 324–337.
Tewes A, Hoffmann H, Nolte M, Krauss G, Schafer F, Kerkhoff C, Gaiser T. 2020. How do methods assimilating Sentinel-2-derived LAI combined with two different sources of soil input data affect the crop model-based estimation of wheat biomass at sub-field level? Remote Sensing, 12, 925.
Verrelst J, Rivera J P, Leonenko G, Alonso L, Moreno J. 2014. Optimizing LUT-Based RTM inversion for semiautomatic mapping of crop biophysical parameters from Sentinel-2 and-3 data: Role of cost functions. IEEE Transactions on Geoscience and Remote Sensing, 52, 257–269.
Wagner M P, Slawig T, Taravat A, Oppelt N. 2020. Remote sensing data assimilation in dynamic crop models using particle swarm optimization. ISPRS International Journal of Geo-Information, 9, 105–116.
Wang J, Li X, Lu L, Fang F. 2013. Estimating near future regional corn yields by integrating multi-source observations into a crop growth model. European Journal of Agronomy, 49, 126–140.
Wang L, Wang P X, Li L, Xun L, Kong Q, Liang S L. 2018a. Developing an integrated indicator for monitoring maize growth condition using remotely sensed vegetation temperature condition index and leaf area index. Computers and Electronics in Agriculture, 152, 340–349.
Wang L, Wang P X, Li L, Zhang S Y, Bai X J, Xie Y. 2018b. Wheat yield forecasting at county scale based on time series vegetation temperature condition index. Geomatics and Information Science of Wuhan University, 43, 1566–1573. (in Chinese)
De Wit A J W, Diepen C A. 2007. Crop model data assimilation with the ensemble kalman filter for improving regional crop yield forecasts. Agricultural & Forest Meteorology, 146, 38–56.
De Wit A J W, Duveiller G, Defourny P. 2012. Estimating regional winter wheat yield with WOFOST through the assimilation of green area index retrieved from MODIS observations. Agricultural and Forest Meteorology, 164, 39–52.
Xie Y, Wang P X, Bai X J, Khan J, Zhang S Y, Li L, Wang L.2017. Assimilation of the leaf area index and vegetation temperature condition index for winter wheat yield estimation using Landsat imagery and the CERES-Wheat model. Agricultural and Forest Meteorology, 246, 194–206.
Zhang G F, Cai Y X, Zheng Z, Zhen J W, Liu Y L, Huang K Y. 2016. Integration of the statistical index method and the analytic hierarchy process technique for the assessment of landslide susceptibility in Huizhou, China. Catena, 142, 233–244.
Zhang L, Zhou W D. 2011. Sparse ensembles using weighted combination methods based on linear programming. Pattern Recognition, 44, 97–106.
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