Exploring the capacity to grasp multi-annual seasonal variability of winter wheat in Continental Climates with MODIS

R. d’Andrimont, G. Duveiller, P. Defourny
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Abstract

This paper presents some exploratory results of the FP-7 MOCCCASIN project that aims to MOnitor Crops in Continental Climates through ASsimilation of Satellite Information. MOCCCASIN is a collaborative project which focuses on improving the monitoring of winter-wheat and forecasting of winter-wheat yield in Russia by combining modelling techniques with satellite data assimilation [1]. In continental climate, winter wheat is particularly affected by low temperatures during the winter which determine whether rapid regrowth is possible in spring. A pre-requisite to use satellite earth observation to characterize the effect of winter kill on wheat is to determine if the multi-annual seasonal variability over the entire growing season can be grasped by remote sensing indicators. The results over an exploratory study site in Tula region for 5 years (2005–2009) demonstrate that it was possible to retrieve crop status indicators using an approach combining radiative transfer modeling and neural networks which could inform on where winter kill has stricken.
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探索利用MODIS技术掌握大陆气候条件下冬小麦多年季节变化的能力
本文介绍了通过同化卫星信息监测大陆气候作物的FP-7 MOCCCASIN项目的一些探索性成果。MOCCCASIN是一个合作项目,其重点是通过将建模技术与卫星数据同化技术相结合,改善俄罗斯冬小麦监测和冬小麦产量预测。在大陆性气候中,冬小麦特别受冬季低温的影响,这决定了春季冬小麦能否快速再生。利用卫星地球观测来表征冬杀对小麦的影响的先决条件是确定遥感指标是否能够掌握整个生长季节的多年季节性变化。在图拉地区一个为期5年(2005-2009年)的探索性研究地点进行的研究结果表明,使用结合辐射传输建模和神经网络的方法检索作物状况指标是可能的,该方法可以告知冬季死亡发生的地点。
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