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基于作物生物量估计的区域冬小麦单产预测

任建强1,2;刘杏认3;陈仲新1,2;周清波1,2;唐华俊1,2   

  1. 1农业部资源遥感与数字农业重点开放实验室, 北京 100081;2中国农业科学院农业资源与农业区划研究所, 北京 100081;3中国科学院地理科学与资源研究所, 北京 100101
  • 收稿日期:2008-09-05 修回日期:1900-01-01 出版日期:2009-04-20 发布日期:2009-04-20

Prediction of winter wheat yield based on crop biomass estimation at regional scale.

REN Jian-qiang1,2;LIU Xing-ren3;CHEN Zhong-xin1,2;ZHOU Qing-bo1,2;TANG Hua-jun1,2   

  1. 1Key Laboratory of Resources Remote Sensing & Digital Agriculture, Ministry of Agriculture, Beijing 100081, China;2Institute of Agricultural Resources & Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;3Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2008-09-05 Revised:1900-01-01 Online:2009-04-20 Published:2009-04-20

摘要: 基于2004年中国冬小麦主产区黄淮海平原典型区内石家庄、衡水和邢台3市45个县(市)83个地面典型样区冬小麦地面实测作物单产数据、光合有效辐射、光合有效辐射分量以及相应的气象和土壤湿度数据,建立了简化的冬小麦光能转化有机物效率系数模型,基于冬小麦关键生育期(3—5月)累积作物生物量并采用地面实测的冬小麦收获指数加以校正,建立了作物生物量与作物经济产量间的定量关系,预测了2004年河北和山东平原区235个县(市)的冬小麦单产,并依据国家公布的2004年各县冬小麦统计单产验证了估产的精度.结果表明:该模型预测的2004年研究区冬小麦单产的均方根误差(RMSE)为238.5 kg·hm-2,平均相对误差为4.28%,达到了大范围估产的精度要求,证明利用以遥感数据估算作物生物量进而预测冬小麦单产的方法是可行的.

关键词: 冬季水鸟, 东洞庭湖, 环境因子, 典范对应分析, t值双序图

Abstract: Based on the 2004 in situ data of crop yield, remote sensing inversed photosynt hetically active radiation (PAR), fraction of photosynthetically active radiatio n (fPAR), climate, and soil moisture in 83 typical winter wheat sampli ng field of 45 counties in Shijiazhuang, Hengshui, and Xingtai of Hebei Province , a simplified model for calculating the light use efficiency (ε) of winter wheat in Huanghuaihai Plain was established. According to the crop accumulated b iomass from March to May and corrected by harvest index, the quantitative relati onship between crop biomass and crop yield for winter wheat was set up, and appl ied in the 235 counties in Huanghuaihai Plain region of Hebei Province and Shand ong Province and validated by the official crop statistical data at county level in 2004. The results showed that the root mean square error (RMSE) of predicted winter wheat yield in study area was 2385 kg·hm-2, and the relative er ror was 428%, suggesting that it was feasible to predict winter wheat yield by crop biomass estimation based on remote sensing data.

Key words: wintering waterfowl, East Dongting Lake, environmental factor, canonical correspondence analysis (CCA), tvalue biplot.