In Earth science, information science, space science, and other disciplines, scientists use the land surface parameter inversion method in their work, applying this to the atmosphere, vegetation, soil, drought, and so on. Multidisciplinary experts sometimes collaborate on a particular application. However, these remote sensing models do not have a unified method of description and management and cannot effectively achieve the sharing of models and data resources. It is also hard to meet user demand for global data and models in the current state, especially in the face of global problems and long-term series problems. In this paper, we examine the scientific questions of the computability and scalability of remote sensing models. This paper adopts a data dependency approach to describe a remote sensing model and implements a hierarchical unified description and management method using modelling based on four layers: a data-processing view, an atomic model view, an on-demand resource package view, and a workflow view. We choose three typical remote sensing models for disaster monitoring as use cases and describe the practical application process of the proposed method. The results demonstrate the advantages and powerful capabilities of this efficient method.

中文翻译：

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基于分布式环境的一种高效的遥感应用建模层次表示方法

在地球科学，信息科学，空间科学和其他学科中，科学家在工作中使用地表参数反演方法，并将其应用于大气，植被，土壤，干旱等。多学科专家有时会在特定应用程序上进行协作。但是，这些遥感模型没有统一的描述和管理方法，无法有效实现模型和数据资源的共享。在当前状态下也很难满足用户对全局数据和模型的需求，尤其是面对全局问题和长期序列问题时。在本文中，我们研究了遥感模型的可计算性和可伸缩性的科学问题。本文采用数据依赖的方法来描述遥感模型，并通过基于四个层次的建模来实现分层的统一描述和管理方法：数据处理视图，原子模型视图，按需资源包视图和资源管理视图。工作流程视图。我们选择了三种典型的灾害监测遥感模型作为用例，并描述了该方法的实际应用过程。结果证明了这种有效方法的优点和强大的功能。我们选择了三种典型的灾害监测遥感模型作为用例，并描述了该方法的实际应用过程。结果证明了这种有效方法的优点和强大的功能。我们选择了三种典型的灾害监测遥感模型作为用例，并描述了该方法的实际应用过程。结果证明了这种有效方法的优点和强大的功能。