The simulation model SCIARA: the 1991 and 2001 lava flows at Mount Etna

Crisci, Gino Mirocle; Rongo, Rocco; Gregorio, Salvatore Di; Spataro, William

doi:10.1016/s0377-0273(03)00349-4

Cited by 96 publications

(65 citation statements)

References 14 publications

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“…However, more sophisticated lava flow modelling efforts, including stochastic slope-controlled models (Harris and Rowland 2001;Favalli et al 2005), cellular automata models (Crisci et al 2004;Del Negro et al 2005;Vicari et al 2007), and other numerical simulations (Dietterich et al 2015), also rely on high quality DEMs input layers to produce successful results. UAS provide a means of effectively generating these needed DEMs, regardless of the modeling method.…”

Section: Applications For Other Lava Flow Modelsmentioning

confidence: 99%

“…Digital Elevation Models (DEMs) are the primary data layer used in models to estimate future lava flow paths and provide flow hazard assessments. The accuracy of the modeled results, either from the paths of steepest descent method (Kauahikaua 2007) or other physics-based lava flow models (e.g., FLOWGO, SCIARA, DOWNFLOW, MAGFLOW), depends strongly on how well the DEM represents the physical environment, which can be difficult to determine in heavily vegetated areas (Harris and Rowland 2001;Crisci et al 2004;Favalli et al 2005;Negro et al 2008). As lava flows change the landscape, subsequent flows will travel along new paths of steepest descent, requiring updated DEMs to reflect the dynamic environment.…”

Section: Introductionmentioning

confidence: 99%

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

2017

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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.

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Section: Applications For Other Lava Flow Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

2017

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“…Lava flow simulation model SCIARA [8] implements a cellular automata technique with applying a rule to introduce a movement of landslide lava path comparing to the real lava eruption at Etnean eruption in 1991-1993. The model aims to simulate the complexity of phenomenon by describing it in a local transformation of each lava cell using some local cell property such as height, temperature, inflow and outflow calculation.…”

Section: B Cellular Automatonmentioning

confidence: 99%

Scenario Generation with Cellular Automaton for Game-Based Crisis Simulation System

Praiwattana

Rhalibi

2016

2016 9th International Conference on Developments in eSystems Engineering (DeSE)

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Abstract-Crisis is infrequent and unpredictable event which is challenging to prepare and resolve. Scenario generation for modeling a crisis using computational approach is preferable due to its flexibility to produce automated variation of scenario based on different setup key factors. Combining crisis generation with game technology, serious-game game can be developed to provide potential support in training and simulation practice of realworld crisis situation to different stakeholders. Therefore, in this paper, we propose a computational framework to provide automated generation of a fire crisis scenario with firefighteragent simulation using cellular automaton with influence map for agent behavior optimization, and visualization using a 3D game engine. The framework is evaluated based on performance, convergence and realistic behavior of both crisis event (e.g. fire propagation or control) and crisis resolution (e.g. firefighter solving the crisis).

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“…Finally, several external influences can be considered in order to model features which are not easy to be described in terms of local interactions. Even though principally derived from the SCIARA-hex1 version [3], SCIARA-fv embeds a better management of several aspects with respect to the original one, some of which will be described later. Formally, the model is defined as:…”

Section: Model Specificationmentioning

confidence: 99%

“…A family of deterministic CA models specifically developed for simulating lava flows is SCIARA [1,2,3]. The model, which is optimized for a specific scenario through a parallel Genetic Algorithm (GA), accounts for the relevant physical processes involved in the macroscopic phenomenon and enables for the fast production of accurate forecasting of lava invasions.…”

Section: Introductionmentioning

confidence: 99%

Modelling Macroscopic Phenomena with Cellular Automata and Parallel Genetic Algorithms: An Application to Lava Flows

Avolio

D'Ambrosio

Gregorio

et al. 2007

Computational Science – ICCS 2007

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Abstract. Forecasting through simulations the shape of lava invasions in a real topography represents a challenging problem, especially considering that the phenomenon usually evolves for a long time (e.g. from a few to hundreds of days) and on very large areas. In the latest years, Cellular Automata (CA) have been well recognized as a valid computational approach in lava flow modelling. In this paper we present some significant developments of SCIARA, a family of deterministic CA models of lava flows which are optimized for a specific scenario through the use of a parallel genetic algorithm. Following a calibration-validation approach, the model outcomes are compared with three real events of lava effusion.

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The simulation model SCIARA: the 1991 and 2001 lava flows at Mount Etna

Cited by 96 publications

References 14 publications

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

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

Scenario Generation with Cellular Automaton for Game-Based Crisis Simulation System

Modelling Macroscopic Phenomena with Cellular Automata and Parallel Genetic Algorithms: An Application to Lava Flows

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