Using an optimization algorithm to establish a network of video surveillance for the protection of Golden Camellia

The natural environment is facing increasing human disturbance. Many species of flora are extinct or endangered. To improve the efficiency of ecological management and monitoring, this study proposed to establish a video monitoring network to protect a world-famous rare flora: Golden Camellia, in Fangcheng nature reserve, Guangxi Province, China. Based on the model of LSCP (location set covering problem), we attempted to establish full monitoring coverage of camellias while minimizing the number of video cameras. The model was solved by integer programming. In case of multiple solutions, this study proposed two additional criterions, maximize monitoring area and maximize overlapping count, to eliminate suboptimal solutions. The two optimal solutions included 80 cameras covering a monitoring area of over 5500 ha. Together, these cameras are able to monitor 97.2% of golden camellia in the reserve. The study suggests that this location optimization model can be used to improve the conservation effectiveness of rare species. Citation: Kun Zhang, Zhi Huang, Songlin Zhang, Using an optimization algorithm to establish a network of video surveillance for the protection of Golden Camellia, Ecological Informatics, Volume 42, 2017, Pages 32-37, ISSN 1574-9541, https://doi.org/10.1016/j.ecoinf.2017.08.004.