面向中国洪涝灾害应急监测的无人机空港布局
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摘要
当前洪涝灾害对社会的经济发展和人民生命财产安全构成严重威胁。无人机机动、灵活,安全性高,可迅捷甚至实时获取灾区影像,对灾情的快速评估和应急救援决策意义重大。遥感无人机在洪涝灾害救援中能够发挥的重要作用已得到广泛共识,但是由于灾害的突发性,缺乏就近部署的资源制约了无人机遥感观测和救援作用的发挥。针对突发灾害,在区域和全国范围内建立起一定的无人机遥感应急体系成为国家面向未来正在考虑的选项。基于此,本研究提出了基于中国科学院的野外台站构建全国无人机遥感观测网的设想。本研究以中国防范洪涝灾害等级分布数据、行政区划数据、中国科学院野外台站分布数据和当前无人机性能数据库为数据源;以行政区划离散并提取的中心点作为需求点,台站作为设施点,不同洪涝等级区域内需要无人机进行应急观测的重要程度作为权重,利用最大覆盖选址模型进行空港选址布局;利用成本-效益曲线确定台站的最佳数量,最终从268个台站中选取出81个作为支撑全国洪涝灾害无人机遥感观测网络的无人机空港。无人机空港布局结果在理论上能够实现对中国绝大数突发洪涝灾害在2 h内初步完成洪涝观测,这对于构建中国空天地一体化的洪涝灾害监测体系具有重要意义。同时,本研究中的方法和成果对于进一步构建行业和综合性的全国无人机遥感观测网也具有一定借鉴和参照意义。
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 costeffectiveness 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.
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 costeffectiveness 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.
引文
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[3]李素菊,和海霞,刘明,等.中国对地观测卫星在缅甸洪涝灾害应急监测中的应用[J].航天器工程,2017,26(2):146-153.[Li S J, He H X, Liu M, et al. Application of China earth observation satellites for Myanmar flood emergency monitoring[J]. Spacecraft Engineering, 2017,26(2):146-153.]
[4] Kaku K, Aso N, Takiguchi F. Space-based response to the2011 Great East Japan Earthquake:Lessons learnt from JAXA's support using earth observation satellites[J]. International Journal of Disaster Risk Reduction, 2015,12:134-153.
[5] Colomina I, Molina P. Unmanned aerial systems for photogrammetry and remote sensing:A review[J]. ISPRS Journal of Photogrammetry&Remote Sensing, 2014,92(2):79-97.
[6]廖小罕,周成虎,苏奋振,等.无人机遥感众创时代[J].地球信息科学学报,2016,18(11):1439-1447.[Liao X H,Zhou C H, Su F Z, et al. The mass innovation era of UAV remote sensing[J]. Journal of Geo-information Science,2016,18(11):1439-1447.]
[7] Gortney W E. Department of defense dictionary of military and associated terms[M]. Washington:Joint Publication, 2016.
[8]李德仁,李明.无人机遥感系统的研究进展与应用前景[J].武汉大学学报·信息科学版,2014,39(5):505-513.[Li D R, Li M. Research advance and application prospect of unmanned aerial vehicle remote sensing system[J]. Geomatics and Information Science of Wuhan University,2014,39(5):505-513.]
[9]李奇.基于中继卫星的无人飞行器组网体制研究[J].无线电工程,2015,45(4):1-4.[Li Q. Research on networking system of unmanned aerial vehicles based on tracking and data relay satellite[J], Radio Engineering, 2015,45(4):1-4.]
[10]郭庆华,刘瑾,李玉美,等.生物多样性近地面遥感监测:应用现状与前景展望[J].生物多样性,2016,24(11):1249-1266.[Guo Q H, Liu J, Li Y M, et al. A near-surface remote sensing platform for biodiversity monitoring:Perspectives and prospects[J]. Biodiversity Science, 2016,24(11):1249-1266.]
[11]李德仁.论空天地一体化对地观测网络[J].地球信息科学学报,2012,14(4):419-425.[Li D R. On space-air-ground integrated Earth observation network[J]. Journal of Geoinformation Science, 2012,14(4):419-425.]
[12]宋晓阳,黄耀欢,董东林,等.融合数字表面模型的无人机遥感影像城市土地利用分类[J].地球信息科学学报,2018, 20(5):703-711.[Song X Y, Huang Y H, Dong D L,et al. Urban land use classification from UAV remote sensing images based on digital surface model[J]. Journal of Geo-information Science, 2018,20(5):703-711.]
[13]廖小罕,周成虎.轻小型无人机遥感发展报告[R].北京:科学出版社,2016.[Liao X H, Zhou C H. The report of light and small UAV remote sensing development[R].Beijing:Science Press, 2016.]
[14]牛栋.中国科学院野外台站网络建设与研究进展[J].林业科技管理,2003(2):27-28.[Niu D. The construction and research progress of the field network of Chinese Academy of Sciences[J]. Forestry technology management, 2003(2):27-28.]
[15]王兮之,葛剑平.国家野外试验站现状分析及网络化体系构建[J].生态科学,2003,22(3):213-217.[Network system and status analysis of national long-term observation research in China[J]. Ecologic Science, 2003,22(3):213-217.]
[16] Roth R. Computer solutions to minimum-cover problems[J]. Operations Research, 1969,17(3):455-465.
[17] Toregas C, Swain R, Revelle C, et al. The location of emergency service facilities[J]. Operations Research,1971,19(6):1363-1373.
[18] Church R, Revelle C. The maximal covering location problem[J]. Papers of the Regional Science Association,1974,32(1):101-118.
[19] Hakimi S L. Optimum locations of switching centers and the absolute centers and medians of a Graph[J]. Operations Research, 1964,12(3):450-459.
[20] Kariv O, Hakimi S L. An algorithmic approach to network location problems. II:The p-Medians[J]. Siam Journal on Applied Mathematics, 1979,37(3):539-560.
[21]苏慧敏,葛炬.基于集合覆盖模型的物流配送中心选址问题研究——以新疆昌吉市社区菜市场物流配送中心选址分析为例[J].物流科技,2017,40(2):24-28.[Su H M, G J. Research on location of logistics distribution center based on set covering model-A study of logistics distribution center location of community food market in Xinjiang Changji[J]. Logistics Sci-Tech, 2017,40(2):24-28.]
[22]陆坚毅,杨超,揭婉晨.考虑绕行特征的电动汽车快速充电站选址问题及自适应遗传算法[J].运筹与管理,2017,26(1):8-17.[Lu J Y, Yang C, Jie W C. An adaptive-self genetic algorithm for solving electric vehicle fast recharging location problem with detour characteristic[J]. Operations Research and Management Science, 2017,26(1):8-17.]
[23]陈志宗,尤建新.重大突发事件应急救援设施选址的多目标决策模型[J].管理科学,2006,19(4):10-14.[Chen Z Z, You J X. A multi-objective decision model of emergency rescue facility location for large-scale emergency incidents[J], Management Sciences in China, 2006,19(4):10-14.]
[24]万金红,张葆蔚,刘建刚,等. 1950-2013年我国洪涝灾情时空特征分析[J].灾害学,2016,31(2):63-68.[Wan J H,Zhang B W, Liu J G, et al. The distribution of flood disaster loss during 1950-2013[J]. Journal of Catastrophology,2016,31(2):63-68.]
[25]国家遥感中心.无人机遥感系统信息库[EB/OL]. http://www.nrscc.gov.cn/wrj/, 2012.[National Remote Sensing Center of China. UAV remote sensing system information database[EB/OL]. http://www.nrscc.gov.cn/wrj/, 2012.]
[26]陈志宗.城市防灾减灾设施选址模型与战略决策方法研究[D].上海:同济大学,2006.[Chen Z Z. The location models and strategic decision method for urban disaster prevention and mitigation facilities[D]. Shanghai:Tongji University, 2006.]
[27]万波.公共服务设施选址问题研究[D].武汉:华中科技大学,2012.[Wan b. Study on the public service facility location problem[D]. Wuhan:Huazhong University of Science and Technology, 2012.]
[2]刘彤,闫天池.我国的主要气象灾害及其经济损失[J].自然灾害学报,2011,20(2):90-95.[Liu T, Yan T C. Main meteorological disasters in China and their economic losses[J]. Journal of Natural Disasters, 2011,20(2):90-95.]
[3]李素菊,和海霞,刘明,等.中国对地观测卫星在缅甸洪涝灾害应急监测中的应用[J].航天器工程,2017,26(2):146-153.[Li S J, He H X, Liu M, et al. Application of China earth observation satellites for Myanmar flood emergency monitoring[J]. Spacecraft Engineering, 2017,26(2):146-153.]
[4] Kaku K, Aso N, Takiguchi F. Space-based response to the2011 Great East Japan Earthquake:Lessons learnt from JAXA's support using earth observation satellites[J]. International Journal of Disaster Risk Reduction, 2015,12:134-153.
[5] Colomina I, Molina P. Unmanned aerial systems for photogrammetry and remote sensing:A review[J]. ISPRS Journal of Photogrammetry&Remote Sensing, 2014,92(2):79-97.
[6]廖小罕,周成虎,苏奋振,等.无人机遥感众创时代[J].地球信息科学学报,2016,18(11):1439-1447.[Liao X H,Zhou C H, Su F Z, et al. The mass innovation era of UAV remote sensing[J]. Journal of Geo-information Science,2016,18(11):1439-1447.]
[7] Gortney W E. Department of defense dictionary of military and associated terms[M]. Washington:Joint Publication, 2016.
[8]李德仁,李明.无人机遥感系统的研究进展与应用前景[J].武汉大学学报·信息科学版,2014,39(5):505-513.[Li D R, Li M. Research advance and application prospect of unmanned aerial vehicle remote sensing system[J]. Geomatics and Information Science of Wuhan University,2014,39(5):505-513.]
[9]李奇.基于中继卫星的无人飞行器组网体制研究[J].无线电工程,2015,45(4):1-4.[Li Q. Research on networking system of unmanned aerial vehicles based on tracking and data relay satellite[J], Radio Engineering, 2015,45(4):1-4.]
[10]郭庆华,刘瑾,李玉美,等.生物多样性近地面遥感监测:应用现状与前景展望[J].生物多样性,2016,24(11):1249-1266.[Guo Q H, Liu J, Li Y M, et al. A near-surface remote sensing platform for biodiversity monitoring:Perspectives and prospects[J]. Biodiversity Science, 2016,24(11):1249-1266.]
[11]李德仁.论空天地一体化对地观测网络[J].地球信息科学学报,2012,14(4):419-425.[Li D R. On space-air-ground integrated Earth observation network[J]. Journal of Geoinformation Science, 2012,14(4):419-425.]
[12]宋晓阳,黄耀欢,董东林,等.融合数字表面模型的无人机遥感影像城市土地利用分类[J].地球信息科学学报,2018, 20(5):703-711.[Song X Y, Huang Y H, Dong D L,et al. Urban land use classification from UAV remote sensing images based on digital surface model[J]. Journal of Geo-information Science, 2018,20(5):703-711.]
[13]廖小罕,周成虎.轻小型无人机遥感发展报告[R].北京:科学出版社,2016.[Liao X H, Zhou C H. The report of light and small UAV remote sensing development[R].Beijing:Science Press, 2016.]
[14]牛栋.中国科学院野外台站网络建设与研究进展[J].林业科技管理,2003(2):27-28.[Niu D. The construction and research progress of the field network of Chinese Academy of Sciences[J]. Forestry technology management, 2003(2):27-28.]
[15]王兮之,葛剑平.国家野外试验站现状分析及网络化体系构建[J].生态科学,2003,22(3):213-217.[Network system and status analysis of national long-term observation research in China[J]. Ecologic Science, 2003,22(3):213-217.]
[16] Roth R. Computer solutions to minimum-cover problems[J]. Operations Research, 1969,17(3):455-465.
[17] Toregas C, Swain R, Revelle C, et al. The location of emergency service facilities[J]. Operations Research,1971,19(6):1363-1373.
[18] Church R, Revelle C. The maximal covering location problem[J]. Papers of the Regional Science Association,1974,32(1):101-118.
[19] Hakimi S L. Optimum locations of switching centers and the absolute centers and medians of a Graph[J]. Operations Research, 1964,12(3):450-459.
[20] Kariv O, Hakimi S L. An algorithmic approach to network location problems. II:The p-Medians[J]. Siam Journal on Applied Mathematics, 1979,37(3):539-560.
[21]苏慧敏,葛炬.基于集合覆盖模型的物流配送中心选址问题研究——以新疆昌吉市社区菜市场物流配送中心选址分析为例[J].物流科技,2017,40(2):24-28.[Su H M, G J. Research on location of logistics distribution center based on set covering model-A study of logistics distribution center location of community food market in Xinjiang Changji[J]. Logistics Sci-Tech, 2017,40(2):24-28.]
[22]陆坚毅,杨超,揭婉晨.考虑绕行特征的电动汽车快速充电站选址问题及自适应遗传算法[J].运筹与管理,2017,26(1):8-17.[Lu J Y, Yang C, Jie W C. An adaptive-self genetic algorithm for solving electric vehicle fast recharging location problem with detour characteristic[J]. Operations Research and Management Science, 2017,26(1):8-17.]
[23]陈志宗,尤建新.重大突发事件应急救援设施选址的多目标决策模型[J].管理科学,2006,19(4):10-14.[Chen Z Z, You J X. A multi-objective decision model of emergency rescue facility location for large-scale emergency incidents[J], Management Sciences in China, 2006,19(4):10-14.]
[24]万金红,张葆蔚,刘建刚,等. 1950-2013年我国洪涝灾情时空特征分析[J].灾害学,2016,31(2):63-68.[Wan J H,Zhang B W, Liu J G, et al. The distribution of flood disaster loss during 1950-2013[J]. Journal of Catastrophology,2016,31(2):63-68.]
[25]国家遥感中心.无人机遥感系统信息库[EB/OL]. http://www.nrscc.gov.cn/wrj/, 2012.[National Remote Sensing Center of China. UAV remote sensing system information database[EB/OL]. http://www.nrscc.gov.cn/wrj/, 2012.]
[26]陈志宗.城市防灾减灾设施选址模型与战略决策方法研究[D].上海:同济大学,2006.[Chen Z Z. The location models and strategic decision method for urban disaster prevention and mitigation facilities[D]. Shanghai:Tongji University, 2006.]
[27]万波.公共服务设施选址问题研究[D].武汉:华中科技大学,2012.[Wan b. Study on the public service facility location problem[D]. Wuhan:Huazhong University of Science and Technology, 2012.]
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