Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1327-1331, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1327-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1327-1331, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1327-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

MULTI-SATELLITE OBSERVATION SCHEDULING FOR LARGE AREA DISASTER EMERGENCY RESPONSE

X. N. Niu1,2, H. Tang1,2, and L. X. Wu3 X. N. Niu et al.
  • 1Key Laboratory of Environment Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing, 100875, China
  • 2Beijing Key Laboratory of Environmental Remote Sensing and Digital Cities, Beijing Normal University, Beijing, 100875, China
  • 3School of Geosciences and Info-Physics, Central South University, Changsha, 410083, China

Keywords: Disaster Emergency Response, Area Tasks, Decomposition, Multi-satellite Scheduling, Multi-objective Genetic Algorithm

Abstract. an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.