A Multi-Objective Modeling Method of Multi-Satellite Imaging Task Planning for Large Regional Mapping

Regional remote sensing image products are playing an important role in an increasing number of application fields. Aiming at multi-satellite imaging task planning for large-area image acquisition, this paper proposes a multi-objective modeling method. First, we analyzed the core requirements of reg...

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Vydáno v:Remote sensing (Basel, Switzerland) Ročník 12; číslo 3; s. 344
Hlavní autoři: Chen, Yaxin, Xu, Miaozhong, Shen, Xin, Zhang, Guo, Lu, Zezhong, Xu, Junfei
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.02.2020
Témata:
Algorithms
China
Collaboration
Decomposition
Finland
Gene mapping
Genetic algorithms
Image acquisition
image analysis
Linear programming
Mapping
Mathematical models
Mission planning
Modelling
multi-objective optimization model
multi-satellite imaging mission planning
nsga-ii
Objective function
Optimization
planning
regional mapping
Regional planning
Regions
Remote sensing
Republic of the Congo
Resource allocation
Resource utilization
Satellite imagery
Satellites
Scheduling
Sensors
Sorting algorithms
China
Finland
Republic of the Congo
ISSN:2072-4292, 2072-4292
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Shrnutí:Regional remote sensing image products are playing an important role in an increasing number of application fields. Aiming at multi-satellite imaging task planning for large-area image acquisition, this paper proposes a multi-objective modeling method. First, we analyzed the core requirements of regional mapping for multi-satellite imaging mission planning: Full coverage of the target area and low consumption of satellite resources. Second, an optimization model with two objective functions, namely the maximum target area coverage and minimum satellite resource utilization, was established. Using the selection of imaging strips and their swing angles as two types of decision variables, the regional decomposition and satellite resource allocation were integrated into the planning model. Third, two efficient algorithms, Vatti and non-dominated sorting genetic algorithm (NSGA-II), were used for objective function calculation and model solving, respectively. Finally, the experiments used Hubei, Finland, and Congo as the target areas and GF1, GF6, ZY1-02C, and ZY3 as imaging satellites to verify the modeling method proposed in this paper. The experiments showed that the proposed multi-objective modeling method could complete the coverage of regional targets with fewer satellite resources and improve the satellite application efficiency significantly.
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ISSN:2072-4292
2072-4292
DOI:10.3390/rs12030344