A SATELLITE IMAGING MISSION PLANNING METHOD FOR FAST ANTARCTICA COVERAGE

Global warming has become one of the most prominent global issues, and Antarctic ice sheet is one of the indicator of global climate change. Satellite imagery has become an important means of monitoring the changes in Antarctic ice sheet. Due to the high overlap of satellite imaging swaths, the exis...

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Bibliographic Details
Published in:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Main Authors: Y. Chen, X. Shen, G. Zhang, T. Liu, Z. Lu, J. Xu, H. Wang
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2020
Subjects:
Technology
T
Engineering (General). Civil engineering (General)
TA1-2040
Applied optics. Photonics
TA1501-1820
Antarctic
Antarc*
Antarctica
Ice Sheet
Online Access:https://doi.org/10.5194/isprs-annals-V-4-2020-217-2020
https://doaj.org/article/6624df90034a4ff39615625029dac415
Description
Summary:Global warming has become one of the most prominent global issues, and Antarctic ice sheet is one of the indicator of global climate change. Satellite imagery has become an important means of monitoring the changes in Antarctic ice sheet. Due to the high overlap of satellite imaging swaths, the existing Antarctica images have the disadvantages of long period of imagery acquisition, large temporal difference among the mosaic images, and low utilization of satellite resource. This paper proposes a satellite imaging mission planning method for fast Antarctica coverage. First, the imaging time window is forecasted within the specified imaging time range to obtain all the visible time windows of the imaging satellite to Antarctica. Then, taking the selection of each time window and the satellite swing angle in each time window as decision variables, and the satellite attitude maneuver ability as constraint, an imaging mission model including two objective functions with minimum number of imaging time windows and the maximum coverage rate is established. To solving the proposed multi-objective optimization model, an improved real-binary hybrid LMOCSO (large-scale multi-objective optimization based on a competitive swarm optimizer) is proposed in this paper. Finally, a simulation experiment was performed using Gaofen-3 satellite to verify the effectiveness of the proposed method.

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