Lava flow hazard prediction and monitoring with UAS: a case study from the 2014–2015 Pāhoa lava flow crisis, Hawai‘i

被引:6
作者
Turner N.R. [1 ,2 ]
Perroy R.L. [3 ]
Hon K. [4 ]
机构
[1] National Disaster Preparedness Training Center, University of Hawai‘i at Mānoa, 2500 Campus Rd, Honolulu, 96822, HI
[2] Department of Geology and Geophysics, University of Hawai‘i at Mānoa, 2500 Campus Rd, Honolulu, 96822, HI
[3] Department of Geography and Environmental Science, University of Hawai‘i at Hilo, 200 W Kawili St, Hilo, 96720, HI
[4] Department of Geology, University of Hawai‘i at Hilo, 200 W Kawili St, Hilo, 96720, HI
基金
美国国家航空航天局; 美国国家科学基金会;
关键词
Crisis response; Digital elevation model; Hazards; Mapping aid; Pāhoehoe lava flow; Unmanned aircraft system;
D O I
10.1186/s13617-017-0068-3
中图分类号
学科分类号
摘要
Accurately predicting lava flow path behavior is critical for active crisis management operations. The advance and emplacement of pāhoehoe flows modifies and inverts pre-existing topography, prompting the need for rapid and accurate updates to the topographic models used to forecast flow paths. The evolution and velocity of pāhoehoe flows are dependent on macro and micro topography, the slope of the descent path, effusion rate, and rheology. During the 2014–2015 Pāhoa crisis on the island of Hawai‘i, we used a low-altitude unmanned aerial system (UAS) to quickly and repeatedly image the active front of a slowly advancing pāhoehoe lava flow. This imagery was used to generate a series of 1 m resolution bare-earth digital elevation models (DEMs) and associated paths of steepest descent over the study area. The spatial resolution and timeliness of these UAS-derived models are an improvement over the existing topographic data used by managers during the crisis. Results from a stepwise resampling experiment suggest that the optimum DEM resolution for generating accurate pāhoehoe flow paths through lowland tropical forest environments is between 1 and 3 m. Our updated models show that future flows in this area will likely be deflected by these newly emplaced flows, possibly threatening communities not directly impacted by the original 2014–2015 lava flow. We demonstrate the value of deploying UAS during a dynamic volcanic crisis and suggest that this technology can fill critical monitoring gaps for Kīlauea and other active volcanoes worldwide. © 2017, The Author(s).
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共 43 条
[1]  
Anderson S.W., Smrekar S.E., Stofan E.R., Tumulus development on lava flows: insights from observations of active tumuli and analysis of formation models, Bull Volcanol, 74, pp. 931-946, (2012)
[2]  
Cashman K.V., Soule S.A., Mackey B.H., Et al., How lava flows: new insights from applications of lidar technologies to lava flow studies, Geosphere, 9, pp. 1664-1680, (2013)
[3]  
Crisci G.M., Rongo R., Di Gregorio S., Spataro W., The simulation model SCIARA: the 1991 and 2001 lava flows at Mount Etna, J Volcanol Geotherm Res, 132, pp. 253-267, (2004)
[4]  
Dandois J.P., Olano M., Ellis E.C., Optimal altitude, overlap, and weather conditions for computer vision uav estimates of forest structure, Remote Sens, 7, pp. 13895-13920, (2015)
[5]  
Del Negro C., Fortuna L., Vicari A., Modelling lava flows by Cellular Nonlinear Networks (CNN): preliminary results. 12:505–513–7946-12–505, Nonlinear Process Geophys v., (2005)
[6]  
Diaz J.A., Pieri D., Wright K., Et al., Unmanned aerial mass spectrometer Systems for in-Situ Volcanic Plume Analysis, J Am Soc Mass Spectrom, 26, 2, pp. 292-304, (2015)
[7]  
Dietterich H., Lev E., Chen J., Benchmarking computational fluid dynamics models for application to lava flow simulations and hazard assessment [abs.], Am Geophys Union, Fall Meet 2015 Abstr abstract no. V13D–07, (2015)
[8]  
Favalli M., Mazzarini F., Pareschi M.T., Boschi E., Topographie control on lava flow paths at Mount Etna. Italy: Implications for hazard assessment, J Geophys Res Earth Surf, (2009)
[9]  
Favalli M., Pareschi M.T., Neri A., Isola I., Forecasting lava flow paths by a stochastic approach, Geophys Res Lett, 32, pp. 1-4, (2005)
[10]  
Fraser R.H., Olthof I., Lantz T.C., Schmitt C., UAV photogrammetry for mapping vegetation in the low-Arctic, Arct Sci, 102, pp. 1-51, (2016)