地球科学进展 ›› 2009, Vol. 24 ›› Issue (4): 444 -451. doi: 10.11867/j.issn.1001-8166.2009.04.0444

生态学研究 上一篇    下一篇

遥感信息与作物生长模型的耦合应用研究进展
邢雅娟,刘东升,王鹏新   
  1. 中国农业大学信息与电气工程学院,北京 100083
  • 收稿日期:2008-09-11 修回日期:2009-02-20 出版日期:2009-04-10
  • 通讯作者: 邢雅娟 E-mail:xingyj222@163.com
  • 基金资助:

    国家高技术研究发展计划课题“作物水分胁迫信息的遥感定量反演与同化技术研究”(编号:2007AA12Z139);北京市自然科学基金面上项目“作物生长模型与遥感数据的同化及其应用研究”(编号:6062019)资助.

Advances of the Coupling Application of Remote Sensing Information and Crop Growth Model

Xing Yajuan, Liu Dongsheng, Wang Pengxin   

  1. College of Information and Electrical Engineering , China Agriculture University,Beijing 100083, China
  • Received:2008-09-11 Revised:2009-02-20 Online:2009-04-10 Published:2009-04-10

      卫星遥感技术具有快速、宏观、准确、客观、及时、动态等特点,在大范围作物长势监测和产量预测等方面具有得天独厚的优势。但遥感监测常常受卫星遥感数据空间分辨率、时间分辨率等因素的影响,且遥感信息大多反映的是瞬间物理状况。作物生长模型是对作物生长、发育、产量形成过程中的一系列生理生化过程进行数学描述,是一种面向过程、机理性的动态模型。但是,当作物模拟从单点研究发展到区域应用时,由于随空间尺度的增大导致模型中一些宏观资料的获取和参数的区域化方面存在很多困难。
      遥感信息与作物生长模型的耦合应用可以解决作物长势监测和产量预测等一系列农业问题,越来越受到相关研究人员的关注,已经逐渐成为一个重要的研究领域。因此,随着作物模型和遥感技术的迅速发展,如何将两者结合,进行互补性的研究是很有意义的。在查阅了相关资料的基础上,综述了遥感信息与作物生长模型的耦合应用以及发展历程,分别阐述了两种遥感数据与作物生长模型的结合方法——强迫法和同化法,总结了两类方法的应用情况。最后提出了该领域存在的问题,以及进一步解决的研究方向。

        Satellite remote sensing technology has the following characteristics: fast, macro, accurate, objective, timely, dynamic and so on, for large-scale crop monitoring and yield forecasting. It has a unique advantage. However, remote monitoring is often subject to spatial resolution, time resolution and other factors of remote sensing data, and most remote sensing information reflects the physical condition of the moment. Internal mechanism for crop growth is difficult to reveal by means of remote sensing. Crop growth model is a mechanism model that describes crop growth. It is a process-oriented, time highly dynamic model. It also has physical advantage. Crop model can simulate crop growth and development continuously, and give explanation of reasons and essence of environmental factor impacts on crop. Crop model used in the single-point can give the appropriate initial data and parameter values that model needs; it can accurately simulate the growth of crops and the final production process. However, when the application of crop simulation from a single point to the region, it generated some issues that some space change information can not be added to the model. In other words, it can not solve the accessing of the initially macro data and the adjusting of the parameter when the crop model is used on large-scale.   With the rapid development of crop model and remote sensing technology, their combination will be meaningful and applicable for crop monitoring and yield prediction. It is a new idea of remote sensing yield prediction put forward by international community in recent years. Accurate crop growth monitoring and yield prediction are significantly important to agricultural production. The coupling of remote sensing data and crop growth models has highly potential application to solving the above problems. It has gradually become an important field of study. Therefore, more and more research people concern it. On the basis of relevant information, this paper reviewed the coupled application of remote sensing information and crop growth model, the forcing method and the assimilation method. 
      In order to enhance crop growth simulation model of precision, the forcing method used remote sensing data to inverse the initial value of the model or used inverted value to update the output parameter values of crop growth model directly. The assimilation method adjusted the initial conditions or the value of the parameter which are closely related to crop growth and yield formation to narrow the disparity between a/some remote sensing “observation” data and the simulated value corresponding to the crop model for achieving the purpose of estimating the initial value or the parameter.
      This paper also reviewed their development process, and summed up the application of the two methods. It includes the application of these two methods at home and abroad, the situation and the effect. Satellite remote sensing and crop growth model have their own advantages in crop monitoring and yield estimation. Their combination can play their respective advantages, and have potential application value. At the end of the article,the existed problems and further research directions in the field were proposed, and the aspects that should be strengthened were summarized.

中图分类号: 

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