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基于遥感信息与作物生长模型的区域作物单产模拟 被引量:37

Regional crop yield simulation based on crop growth model and remote sensing data
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摘要 利用外部数据同化作物生长模型提高区域作物单产模拟精度是近年来的研究热点。该文以遥感反演的叶面积指数(LAI)作为结合点,以黄淮海粮食主产区典型县市夏玉米为研究对象,在区域尺度利用全局优化的复合形混合演化(SCE-UA)算法进行了遥感反演LAI信息同化EPIC(environmental policy integrated climate)模型的夏玉米作物单产模拟研究,最后进行区域作物单产模拟精度验证。结果表明,整合SCE-UA全局优化算法的EPIC模型通过同化遥感反演的LAI进行夏玉米单产模拟的平均相对误差为4.37%,RMSE为0.44t/hm2。同时,通过与实际调查数据对比可知,模型模拟的夏玉米播种日期、种植密度和纯氮施用量的均方根误差(RMSE)分别为4.16d、1.0株/m2和40.64kg/hm2,模拟的夏玉米播种日期的绝对误差为3d,模拟的夏玉米种植密度和纯氮施用量的平均相对误差分别为-7.78%和-10.60%。上述误差可满足大范围农作物单产模拟的要求,证明了利用SCE-UA全局优化算法的EPIC模型同化遥感反演LAI数据进行区域作物单产模拟的可行性。 Assimilating external data into crop growth model to improve accuracy of crop growth monitoring and yield estimation is a research hotspot in recent years. In this paper, the global optimization algorithm SCE-UA (Shuffled Complex Evolution method - University of Arizona) was used to integrate remote sensing leaf area index (LAI) with crop growth model EPIC to simulate regional yield, sowing date, plant density, and net nitrogen fertilizer application amount of summer maize in Huanghuaihai Plain. The results showed that the average relative error of estimated summer maize yield was 4.37%, and RMSE was 0.44 t/hm2. By comparison of the observation data, the root mean square error (RMSE) of simulated sowing date, plant density and net nitrogen fertilization application amount was 4.16 days, 1.0 plant/m2, 40.64 kg/hm2 respectively. The absolute error of simulated sowing date was 3 days, the average relative error of simulated plant density and net nitrogen fertilization application amount was -7.78% and -10.60% respectively. The accuracy of simulated results could meet the need of crop monitoring at regional scale, and it was proved that integrating remote sensing LAI with EPIC model based on global optimization algorithm SCE-UA for simulation of crop growth condition and crop yield was feasible.
出处 《农业工程学报》 EI CAS CSCD 北大核心 2011年第8期257-264,共8页 Transactions of the Chinese Society of Agricultural Engineering
基金 科技部国际科技合作项目(2010DFB10030) 农业部"948计划"项目(2009-Z31 2011-G6)农业部"全国农情遥感监测业务化运行"项目资助 欧盟FP7计划E-Agri项目(资助编号270351) 中国农业科学院农业资源与农业区划研究所中央级公益性科研院所基本科研业务费专项(IARRP-2009-27 IARRP-2011-42)
关键词 遥感 作物生长模型 估产 叶面积指数 数据同化 全局优化算法 remote sensing crop growth model yield estimation LAI data assimilation global optimization algorithm
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  • 1Chen Z, Li S, Ren J, et al. Monitoring and management of agriculture with remote sensing[M]. Liang S (Ed). Advances in Land Remote Sensing: system, modeling, inversion and application. Springer, 2008, ISBN 978-1-4020-6449-4, 397- 421.
  • 2Delecolle R, Mass S J, Guerif M, et al. Remote sensing and crop production models[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 1992, 47(2/3): 145- 161.
  • 3Reynolds C A, Yitayew M, Slack D C, et al. Estimating crop yields and production by integrating the FAO Crop Specific Water Balance model with real-time satellite data and ground-based ancillary data[J]. International Journal of Remote Sensing, 2000, 21(18), 3487-3508.
  • 4Ma Y, Wang S, Zhang L, et al. Monitoring winter wheat growth in North China by combining a crop model and remote sensing data[J]. International Journal of Applied Earth Observation and Geoinformation, 2008, 10(4): 426-437.
  • 5杨鹏,吴文斌,周清波,陈仲新,查燕,唐华俊,柴崎亮介.基于作物模型与叶面积指数遥感影像同化的区域单产估测研究[J].农业工程学报,2007,23(9):130-136. 被引量:44
  • 6申双和,杨沈斌,李秉柏,谭炳香,李增元,Le Toan Thuy.基于ENVISAT ASAR数据的水稻估产方案[J].中国科学(D辑),2009(6):763-773. 被引量:11
  • 7Dente L, Satalino G, Mattia F, et al. Assimilation of leaf area index derived from ASAR and MERIS data into CERES- Wheat model to map wheat yield[J]. Remote Sensing of Environment, 2008, 112(4): 1395- 1407.
  • 8Moulin S, Bondeau A, Delecolle R. Combining agricultural crop models and satellite observations: from field to regional scales[J]. International Journal of Remote Sensing, 1998, 19(6): 1021- 1036.
  • 9Launay M, Guerif M. Assimilating remote sensing data into a crop model to improve predictive performance for spatial applications[J]. Agriculture, Ecosystems and Environment, 2005, 111(1/4): 321 -339.
  • 10de Wit A J W, van Diepen C A. Crop model data assimilation with the Ensemble Kalman filter for improving regional crop yield forecasts[J]. Agricultural and Forest Meteorology, 2007, 146(1/2): 38-56.

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