Remote Sensing (Apr 2023)

An Earth Observation Task Representation Model Supporting Dynamic Demand for Flood Disaster Monitoring and Management

  • Zhongguo Zhao,
  • Chuli Hu,
  • Ke Wang,
  • Yixiao Zhang,
  • Zhangyan Xu,
  • Xuan Ding

DOI
https://doi.org/10.3390/rs15082193
Journal volume & issue
Vol. 15, no. 8
p. 2193

Abstract

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A comprehensive, accurate, and timely expression of earth observation (EO) tasks is the primary prerequisite for the response to and the emergency monitoring of disasters, especially floods. However, the existing information model does not fully satisfy the demand for a fine-grain observation expression of EO task, which results in the absence of task process management. The current study proposed an EO task representation model based on meta-object facility to address this problem. The model not only describes the static information of a task, but it also defines the dynamics of an observation task by introducing a functional metamodel. This metamodel describes the full life cycle of a task; it comprises five process methods: birth, separation, combination, updating, and extinction. An earth observation task modeling and management prototype system (EO-TMMS) for conducting a remote sensing satellite sensor observation task representation experiment on flooding was developed. In accordance with the results, the proposed model can describe various EO tasks demands and the full life cycle process of an EO task. Compared with other typical observation task information models, the proposed model satisfies the dynamic and fine-grain process representation of EO tasks, which can improve the efficiency of EO sensor utilization.

Keywords