Author ' s personal copy A simple algorithm for yield estimates : Evaluation for semi-arid irrigated winter wheat monitored with green leaf area index

Author ' s personal copy A simple algorithm for yield estimates : Evaluation for semi-arid irrigated winter wheat monitored with green leaf area index
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发表时间:
2007
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通讯作者:
B. Duchemin;P. Maisongrande;G. Boulet;I. Benhadj
B. Duchemin;P. Maisongrande;G. Boulet;I. Benhadj
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作者:
B. Duchemin;P. Maisongrande;G. Boulet;I. Benhadj

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在这项研究中,我们研究了耦合一个简单的植被生长模型和地面遥感数据的小麦生产监测提供的前景。建立了绿色叶面积指数(GLAI)、地上部干生物量(DAM)和籽粒产量(戈伊)的时间过程模型。一个全面的敏感性分析,可以解决模型校准的问题,区分三类参数:(1)那些,众所周知,来自目前或以前的小麦实验;(2)那些,物候,已确定的小麦品种研究;(3)那些,与农民的做法,已调整字段。该方法进行了测试,对灌溉冬小麦在半干旱马拉喀什平原上收集的实地数据。该数据集包括GLAI的估计值以及额外的DAM和戈伊测量值。该模型提供了良好的模拟GLAI和DAM的时间过程。正确预测了戈伊空间变化,但对验证场的估计普遍偏低。尽管有这种限制,但这种方法的优点是相当简单,不需要任何关于农业做法(播种、灌溉和施肥)的数据。这使得它在区域范围内的业务应用非常有吸引力。这一观点在结论中进行了讨论。2007爱思唯尔有限公司版权所有。
In this study we investigated the perspective offered by coupling a simple vegetation growth model and ground-based remotely-sensed data for the monitoring of wheat production. A simple model was developed to simulate the time courses of green leaf area index (GLAI), dry aboveground phytomass (DAM) and grain yield (GY). A comprehensive sensitivity analysis has allowed addressing the problem of model calibration, distinguishing three categories of parameters: (1) those, well known, derived from the present or previous wheat experiments; (2) those, phenological, which have been identified for the wheat variety under study; (3) those, related to farmer practices, which has been adjusted field by field. The approach was tested against field data collected on irrigated winter wheat in the semi-arid Marrakech plain. This data set includes estimates of GLAI with additional DAM and GY measurements. The model provides excellent simulations of both GLAI and DAM time courses. GY space variations are correctly predicted, but with a general underestimation on the validation fields. Despite this limitation, the approach offers the advantage of being quite simple, without requiring any data on agricultural practices (sowing, irrigation and fertilisation). This makes it very attractive for operational application at a regional scale. This perspective is discussed in the conclusion. 2007 Elsevier Ltd. All rights reserved.