作物生长模型与定量遥感参数结合研究进展与展望
作物生长模型与定量遥感参数的结合,不仅满足前者实现区域应用的需求,也有助于提高后者的反演精度,在生态、农业、资源调查与全球气候变化等研究上意义重大。该文从作物生长模型空间应用拓展的角度,对国内外主流作物生长模型、定量遥感参数以及两者结合的参数与方法进行了概述,分析了典型作物生长模型的主要模拟过程及其驱动、初始化、输出等参数,总结了当前定量遥感正反演结果可为作物生长模型区域应用提供的参数数据;建立了作物生长模型模拟过程与定量遥感参数的对应关系,对比分析了作物生长模型与定量遥感参数的不同结合方式。基于以上内容,对作物生长模型面应用的限制因素及其与定量遥感参数的关系、作物生长模型面应用时参数尺度效应...
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| Published in | 农业工程学报 Vol. 33; no. 9; pp. 155 - 166 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国科学院遥感与数字地球研究所遥感科学国家重点实验室,北京 100101%石河子大学,石河子,832000
2017
石河子大学,石河子 832000%中国科学院遥感与数字地球研究所,北京 100101 中国科学院遥感与数字地球研究所,北京 100101 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-6819 |
| DOI | 10.11975/j.issn.1002-6819.2017.09.020 |
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| Abstract | 作物生长模型与定量遥感参数的结合,不仅满足前者实现区域应用的需求,也有助于提高后者的反演精度,在生态、农业、资源调查与全球气候变化等研究上意义重大。该文从作物生长模型空间应用拓展的角度,对国内外主流作物生长模型、定量遥感参数以及两者结合的参数与方法进行了概述,分析了典型作物生长模型的主要模拟过程及其驱动、初始化、输出等参数,总结了当前定量遥感正反演结果可为作物生长模型区域应用提供的参数数据;建立了作物生长模型模拟过程与定量遥感参数的对应关系,对比分析了作物生长模型与定量遥感参数的不同结合方式。基于以上内容,对作物生长模型面应用的限制因素及其与定量遥感参数的关系、作物生长模型面应用时参数尺度效应的影响、作物生长模型与定量遥感参数耦合方法的发展3个方面展开了讨论,以期为作物生长模型与定量遥感参数开展更好的结合研究提供参考。 |
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| AbstractList | TP79%S31; 作物生长模型与定量遥感参数的结合,不仅满足前者实现区域应用的需求,也有助于提高后者的反演精度,在生态、农业、资源调查与全球气候变化等研究上意义重大.该文从作物生长模型空间应用拓展的角度,对国内外主流作物生长模型、定量遥感参数以及两者结合的参数与方法进行了概述,分析了典型作物生长模型的主要模拟过程及其驱动、初始化、输出等参数,总结了当前定量遥感正反演结果可为作物生长模型区域应用提供的参数数据;建立了作物生长模型模拟过程与定量遥感参数的对应关系,对比分析了作物生长模型与定量遥感参数的不同结合方式.基于以上内容,对作物生长模型面应用的限制因素及其与定量遥感参数的关系、作物生长模型面应用时参数尺度效应的影响、作物生长模型与定量遥感参数耦合方法的发展3个方面展开了讨论,以期为作物生长模型与定量遥感参数开展更好的结合研究提供参考. 作物生长模型与定量遥感参数的结合,不仅满足前者实现区域应用的需求,也有助于提高后者的反演精度,在生态、农业、资源调查与全球气候变化等研究上意义重大。该文从作物生长模型空间应用拓展的角度,对国内外主流作物生长模型、定量遥感参数以及两者结合的参数与方法进行了概述,分析了典型作物生长模型的主要模拟过程及其驱动、初始化、输出等参数,总结了当前定量遥感正反演结果可为作物生长模型区域应用提供的参数数据;建立了作物生长模型模拟过程与定量遥感参数的对应关系,对比分析了作物生长模型与定量遥感参数的不同结合方式。基于以上内容,对作物生长模型面应用的限制因素及其与定量遥感参数的关系、作物生长模型面应用时参数尺度效应的影响、作物生长模型与定量遥感参数耦合方法的发展3个方面展开了讨论,以期为作物生长模型与定量遥感参数开展更好的结合研究提供参考。 |
| Abstract_FL | Combining the crop growth models with the remote sensing parameters, is important to realize the applications in the large spatial scale for the former, and also to improve the rationality and accuracy of inversion theory for the latter. Some research fields, such as the ecology, agriculture, resource investigation and global climate change, would use the data derived from the combination form. The overview includes 3 parts, i.e. the international crop growth model, the quantitative remote sensing parameters and the parametric methods. From the view of the spatial expansion for the application of the crop growth model, the development duration of crop growth models was divided into 3 stages: The construction of the mechanism models, the application in the point scale, and the application in the regional and global scale. In order to understand the situation and foundation of the inter-discipline combination from the crop growth simulation and the quantitative remote sensing, the paper describes 3 important contents. The first is overviewing the main simulation processes and the input and output parameters for the typical crop growth models. The second is summarizing the remote sensing inversion parameters which can be used as the initialization and driving data for the application of crop growth simulation models in the regional and global scale, establishing the corresponding relation between the simulation process of crop growth model and the parameters from the quantitative remote sensing. And the third is comparing 3 kinds of combination methods between the crop growth model and the parameters derived from the quantitative remote sensing, and emphasizing the differences, advantages and disadvantages for the 3 combination methods. Based on the contents mentioned above, 3 topics for discussion are proposed. The first topic is the application limitations of crop growth models in the large spatial scale and its relationship with quantitative remote sensing parameters. The second one is the influence of the scale effect from the input parameters when the crop growth model is used to simulate the crop growth in the larger region. And the third one is to discuss the development direction of combination methods. It is hopeful to provide a kind of thinking for combining the crop growth models with the parameters from the quantitative remote sensing through the overview, summary and discussion. And it is clearly concluded that the data from the quantitative remote sensing can provide initialization data for crop growth models to some extent in the regional and global scale, and the application in a large space scale is the direction of crop growth model. The conclusion shows further that it is important to pay attention to the scale problem of the model parameters, and that the data dis-matching for the same parameter from the crop growth and remote sensing can result in the huge error of estimation on the output data due to the difference of physical meaning from the 2 disciplines. Understanding that the data from the quantitative remote sensing could enhance the ability of simulating the crop conditions and yield at the large scale was also helpful to understand that the remote sensing had the ability of deriving the biochemical and biophysical information from the ground surface exactly. And furthermore, it is expected that the correct combination parameters should be chosen to deduce the propagation of error and uncertainty, the assimilation methods would still preserve the mainstream style for the combination, and following the increasing accuracy of data from the remote sensing and crop model, the fusion model for the model of crop growth and remote sensing can be constructed to play a greater application value in the environmental monitoring and agricultural production. |
| Author | 吴蕾 柏军华 肖青 杜永明 柳钦火 徐丽萍 |
| AuthorAffiliation | 中国科学院遥感与数字地球研究所,北京100101 石河子大学,石河子832000 中国科学院遥感与数字地球研究所遥感科学国家重点实验室,北京100101 |
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| Author_FL | Wu Lei Xu Liping Xiao Qing Bai Junhua Du Yongming Liu Qinhuo |
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| Keywords | models 作物生长 development 模型 remote sensing vegetation 遥感 quantitative remote sensing crop growth 发展 植被 定量遥感 结合 combination |
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| Notes | remote sensing; models; vegetation; crop growth; quantitative remote sensing; combination; development 11-2047/S Wu Lei1,2, Bai Junhua1,3, Xiao Qing1,3, Du Yongming1,3, Liu Qinhuo1,3, Xu Liping2 （1. Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences, Beijing 100101, China; 2. Shihezi University, Shihezi 832000, China; 3. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences, Beijing 100101, China） Combining the crop growth models with the remote sensing parameters, is important to realize the applications in the large spatial scale for the former, and also to improve the rationality and accuracy of inversion theory for the latter. Some research fields, such as the ecology, agriculture, resource investigation and global climate change, would use the data derived from the combination form. The overview includes 3 parts, i.e. the international crop growth model, the quantitative remote sensing parameters and the parametric me |
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| Title | 作物生长模型与定量遥感参数结合研究进展与展望 |
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