摘要
为提高冬小麦遥感估产的精确性与适用性,在河南省的孟州市和沁阳市利用GPS定位布设田间试验,利用P-6卫星数据进行了冬小麦遥感估产研究。通过对遥感植被指数和冬小麦长势与产量GPS定位数据的综合分析,基于遥感影像信息获取的瞬时性和准确性,结合小麦灌浆期生态条件对小麦产量形成的影响,利用开花期遥感影像归一化植被指数(NDVI)和灌浆期生态因子(气温、日照、氮素营养、土壤水分)建立了冬小麦产量遥感估测模型,并检验了该模型的可靠性。结果表明,模型预测值与实测值较为一致,利用开花期遥感影像NDVI和灌浆期生态数据估测冬小麦产量的RMSE值为369.27 kg.ha-1,相对误差为6.45%。模型估测性能好,且具有一定的解释性。
To advance the accuracy and the applicability of estimating winter wheat yield by remote sensing technology, the field experiments were carried out in Mengzhou and Qinyang county of Henan province. The relationships between winter wheat yield and ecological factors including average temperature（T）, solar radiation（S）, nitrogen nutrition（N）, and soil water（W）during grain filling period were analyzed, then the ecological factor-driven equations with TF, SF, NF and WF were established. By correcting the impacts of ecological factors on winter wheat yield formation, a monitoring model for winter wheat yield was developed as WYW=（WBW X HI） ×m√TF × ST×WF × NF, where HI was cultivar harvest index, and WBW was the aboveground biomass which was calculated with NDVI in early anthesis. The model was validated using the data sets of NDVI with the root mean square error （RMSE） of 369.27 kg · ha^- 1 for winter wheat yield. The results indicated that the model was accurate and applicable for estimating winter wheat yield under different conditions with a relative error of 6.45%. Yet, more experiment data in different ecological condition are required for wide testing of the present model.
出处
《麦类作物学报》
CAS
CSCD
北大核心
2009年第5期906-909,共4页
Journal of Triticeae Crops
基金
国家863计划项目(2008AA10Z214)
农业部行业科技项目(200803037)
江苏省农业科学院人才基金项目(6510805)
江苏省农业科学院科研基金项目(6110824)
关键词
冬小麦
生态条件
遥感
产量预测
Winter wheat
Remote sensing
Yield estimating
Ecological condition
