A multi-objective programming model that can monitor and feedback front line fires data based on UAV cruising

Jingxin Guo; Chaoqun Lv; Yu Cheng; Jikun Niu; Xiru Song; Zhonggeng Xie; Lijuan Fu; Zhe Zhang

doi:10.1117/12.3021033

23 January 2024 A multi-objective programming model that can monitor and feedback front line fires data based on UAV cruising

Jingxin Guo, Chaoqun Lv, Yu Cheng, Jikun Niu, Xiru Song, Zhonggeng Xie, Lijuan Fu, Zhe Zhang

Author Affiliations +

Proceedings Volume 12978, Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023); 1297814 (2024) https://doi.org/10.1117/12.3021033
Event: 2023 4th International Conference on Geology, Mapping and Remote Sensing (ICGMRS 2023), 2023, wuhan, China

Abstract

The wildfires that have raged across Australia for over three months have left an indelible impact on every state. In response, we have developed a multi-objective planning model and a fire monitoring model that are suitable for SSA (sub-Saharan Africa) unmanned aerial vehicles. These models provide assurance for fire prevention and timely understanding of fire front issues while also ensuring cost control.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jingxin Guo, Chaoqun Lv, Yu Cheng, Jikun Niu, Xiru Song, Zhonggeng Xie, Lijuan Fu, and Zhe Zhang "A multi-objective programming model that can monitor and feedback front line fires data based on UAV cruising", Proc. SPIE 12978, Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023), 1297814 (23 January 2024); https://doi.org/10.1117/12.3021033

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