Journal of Geo-information Science ›› 2019, Vol. 21 ›› Issue (6): 854-864.doi: 10.12082/dqxxkx.2019.180177

Previous Articles     Next Articles

Determining the Distribution of Unmanned Aerial Vehicles Airports for the Emergency Monitoring of Floods in China

Ming LU1,2(), Xiaohan LIAO1,*(), Huanyin YUE1,2, Shifeng HUANG3, Chenchen XU1,2, Haiying LU4, Yiqin BAI5   

  1. 1. State Key Laboratory of Resources and Environment Information System, Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2. Tianjin Institute of Application and Research on Unmanned Aerial Vehicles, Tianjin 301800, China
    3. Remote sensing technology application center, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
    4. Internet of things research center, China Electronics Standardization Institute, Beijing 100007, China
    5. China Academy of Civil Aviation Science and Technology, Beijing 100028, China
  • Received:2018-04-10 Revised:2019-04-18 Online:2019-06-15 Published:2019-06-15
  • Contact: Xiaohan LIAO;
  • Supported by:
    National Natural Science Foundation of China, No.41771388;National Key Research and Development;Program of China, No.2017YFB0503005;Postdoctoral Science Foundation of China, No.2018M640170


Frequent flood hazards affect large areas and cause great losses, which have posed a serious threat to economic development and people's lives and properties. Unmanned Aerial Vehicles (UAVs) have proven to be useful in monitoring disaster status and providing decision-making support for emergency rescue, because they are able to arrive at floods area timely, obtain flood images and videos quickly, low-risk to operate and flexible to carry out different sensors. The important roles of UAV in emergency rescue have been widely recognized. However, the lack of available UAV resources nearby at the sudden onset of floods seriously limits the capability of UAVs' rapid response to flood disasters. For addressing this challenge, a multi-UAVs remote sensing observation network is highly required, and now has been planned in China to enhance our ability of emergency response. Key problems include where and how to allocate UAVs resources such that the UAVs can reach destination timely when floods occur. To help close this gap, we proposed to build a number of UAV airports in China to establish a remote sensing observation network of UAVs. Field stations of Chinese Academy of Science (CAS) were considered as the potential locations of UAV airports because of their extensive geographical distribution and good cooperation with the UAV application and regulation research center of CAS. With the available flood risk prevention data, administrative division data, CAS field stations data and the UAV database as data sources, we created a fishnet of 0.5° multiply 0.5° to discretize administrative divisions and regarded the central points of these grids as potential demand points, and then calculated the importance of UAV to those demand points based on their flood risk prevention level. Based on this analysis, a Maximum Covering Location Problem (MCLP) model was adopted to determine the optimum stations for UAV airports and a cost-effectiveness curve was used to determine the optimum number of UAV airports. In the end, 81 field stations were selected from 268 field stations, thereby ensuring that UAV airports would be allocated near flood-prone areas and most floods in China could be monitored with UAVs within two hours, which is critical for saving lives and reducing losses. The construction of UAV airport networks will surely contribute to an integrated disaster emergency observation system combining satellite, airplane, UAV and ground observations in China. Additionally, the methods and results in this study can serve as a basis for building a more comprehensive national UAV remote sensing observation network.

Key words: UAV, airport distribution, remote sensing observation network, flood disaster, emergency rescue, China