Scheduling Ocean Color Observations for a GEO-Stationary Satellite. Frank, J., Do, M., & Tran, T. In
Scheduling Ocean Color Observations for a GEO-Stationary Satellite [link]Paper  abstract   bibtex   
The GEO-Stationary Coastal and Air Pollution Events (GEO-CAPE) mission plans to put a visible spectrum imaging instrument on a satellite in geo-stationary orbit to perform ocean color remote sensing. Two different instrument designs, Filter Radiometer (FR) and COastal Ecosystems Dynamic Imager (COEDI), with different size and shape for the imaged area and image acquisition time are being evaluated. Scheduling observations for each of them requires optimizing science objectives in the presence of predicted cloud cover and available daylight. We model this scheduling problem as both Mixed Integer Linear Program (MILP) and Constraint Programming (CP) problems, and compare these two formulations for FR and COEDI using real cloudiness data collected at different times throughout the year. Our results show that MILP is the more suitable technique, and the schedule quality metric conclusively shows FR is preferred. We have reported our results to the GEO-CAPE mission team to assist them making an informed decision for the next step in formulating this mission.
@inproceedings {icaps16-184,
    track    = {​​​Applications Track},
    title    = {Scheduling Ocean Color Observations for a GEO-Stationary Satellite},
    url      = {http://www.aaai.org/ocs/index.php/ICAPS/ICAPS16/paper/view/13072},
    author   = {Jeremy Frank and  Minh Do and  Tony Tran},
    abstract = {The GEO-Stationary Coastal and Air Pollution Events (GEO-CAPE) mission plans to put a visible spectrum imaging instrument on a satellite in geo-stationary orbit to perform ocean color remote sensing. Two different instrument designs, Filter Radiometer (FR) and COastal Ecosystems Dynamic Imager (COEDI), with different size and shape for the imaged area and image acquisition time are being evaluated. Scheduling observations for each of them requires optimizing science objectives in the presence of predicted cloud cover and available daylight. We model this scheduling problem as both Mixed Integer Linear Program (MILP) and Constraint Programming (CP) problems, and compare these two formulations for FR and COEDI using real cloudiness data collected at different times throughout the year. Our results show that MILP is the more suitable technique, and the schedule quality metric conclusively shows FR is preferred. We have reported our results to the GEO-CAPE mission team to assist them making an informed decision for the next step in formulating this mission.},
    keywords = {Evaluation; testing; and validation of P&S applications,Description and modeling of novel application domains,Engineering issues in using P&S techniques}
}

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