Wildland fire spread modelling using cellular automata: evolution in large-scale spatially heterogeneous environments under fire suppression tactics

2011 ◽  
Vol 20 (5) ◽  
pp. 633 ◽  
Author(s):  
A. Alexandridis ◽  
L. Russo ◽  
D. Vakalis ◽  
G. V. Bafas ◽  
C. I. Siettos
Keyword(s):  
Cellular Automata ◽  
Geographical Information Systems ◽  
Large Scale ◽  
Fire Suppression ◽  
Meteorological Data ◽  
Fire Spread ◽  
Geographical Information ◽  
Heterogeneous Environments ◽  
Detailed Model ◽  
Technical Specifications

We show how microscopic modelling techniques such as Cellular Automata linked with detailed geographical information systems (GIS) and meteorological data can be used to efficiently predict the evolution of fire fronts on mountainous and heterogeneous wild forest landscapes. In particular, we present a lattice-based dynamic model that includes various factors, ranging from landscape and earth statistics, attributes of vegetation and wind field data to the humidity of the fuel and the spotting transfer mechanism. We also attempt to model specific fire suppression tactics based on air tanker attacks utilising technical specifications as well as operational capabilities of the aircrafts. We use the detailed model to approximate the dynamics of a large-scale fire that broke out in a region on the west flank of the Greek National Park of Parnitha Mountain in June of 2007. The comparison between the simulation and the actual results showed that the proposed model predicts the fire-spread characteristics in an adequate manner. Finally, we discuss how such a detailed model can be exploited in order to design and develop, in a systematic way, fire risk management policies.

scholarly journals Multivariate clustering of reindeer herding districts in Sweden according to range prerequisites for reindeer husbandry

Rangifer ◽  
2009 ◽  
Vol 27 (2) ◽  
pp. 107-119
Author(s):  
Henrik Lundqvist ◽  
Öje Danell
Keyword(s):  
Geographical Information Systems ◽  
Large Scale ◽  
Global Climate ◽  
Meteorological Data ◽  
Principal Component ◽  
Geographical Information ◽  
Reindeer Herding ◽  
Factors Affecting ◽  
Decision Tools ◽  
Forage Value

The 51 reindeer herding districts in Sweden vary in productivity and prerequisites for reindeer herding. In this study we characterize and group reindeer herding districts based on relevant factors affecting reindeer productivity, i.e. topography, vegetation, forage value, habitat fragmentation and reachability, as well as season lengths, snow fall, ice-crust probability, and insect harassment, totally quantified in 15 variables. The herding districts were grouped into seven main groups and three single outliers through cluster analyses. The largest group, consisting of 14 herding districts, was further divided into four subgroups. The range properties of herding districts and groups of districts were characterized through principal component analyses. By comparisons of the suggested grouping of herding districts with existing administrative divisions, these appeared not to coincide. A new division of herding districts into six administrative sets of districts was suggested in order to improve administrative planning and management of the reindeer herding industry. The results also give possibilities for projections of alterations caused by an upcoming global climate change. Large scale investigations using geographical information systems (GIS) and meteorological data would be helpful for administrative purposes, both nationally and internationally, as science-based decision tools in legislative, economical, ecological and structural assessments. Abstract in Swedish / Sammanfattning: Multivariat gruppering av svenska samebyar baserat på renbetesmarkernas grundförutsettningar Svenska renskötselområdet består av 51 samebyar som varierar i produktivitet och förutsättningar för renskötsel. Vi analyserade variationen mellan samebyar med avseende på 15 variabler som beskriver topografi, vegetation, betesvärde, fragmentering av betesmarker, klimat, skareförekomst och aktivitet av parasiterande insekter och vi föreslår en indelning av samebyar i tio grupper. Den största gruppen, som bestod av 14 samebyar, delades vidare in i 4 undergrupper. Klusteranalyser med 4 olika linkage-varianter användes till att gruppera samebyarna. Principalkomponentsanalys användes för att kartlägga undersökta variabler och de resulterande samebygruppernas karaktär. Samebygrupperna följde inte länsgränser och tre samebyar föll ut som enskilda grupper. Denna undersökning ger underlag för jämförelser mellan samebyar med beaktande av likheter och olikheter i fråga om produktivitet och funktionella särdrag istället för länsgränser och historik. Vi föreslår en ny administrativ indelning i sex områden som skulle kunna fungera som ett alternativt underlag för planering och beslut som rör produktionsaspekter i rennäringen. Resultaten ger också underlag för förutsägelser av förändringar i samebyars produktionsförutsättningar till följd av klimatförändringar.

scholarly journals Using 1D HEC-RAS Modeling and LiDAR Data to Improve Flood Hazard Maps Accuracy: A Case Study from Jijia Floodplain (NE Romania)

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1624 ◽  
Author(s):  
Elena Huţanu ◽  
Alin Mihu-Pintilie ◽  
Andrei Urzica ◽  
Larisa Elena Paveluc ◽  
Cristian Constantin Stoleriu ◽  
...  
Keyword(s):  
Geographical Information Systems ◽  
Large Scale ◽  
Flood Hazard ◽  
Hydraulic Modeling ◽  
Geographical Information ◽  
Computer Algorithms ◽  
Hazard Maps ◽  
Modeling Software ◽  
Recurrence Intervals ◽  
Flood Hazard Maps

The ability to extract flood hazard settings in highly vulnerable areas like populated floodplains by using new computer algorithms and hydraulic modeling software is an important aspect of any flood mitigation efforts. In this framework, the 1D/2D hydraulic models, which were generated based on a Light Detection and Ranging (LiDAR) derivate Digital Elevation Model (DEM) and processed within Geographical Information Systems (GIS), can improve large-scale flood hazard maps accuracy. In this study, we developed the first flood vulnerability assessment for 1% (100-year) and 0.1% (1000-year) recurrence intervals within the Jijia floodplain (north-eastern Romania), based on 1D HEC-RAS hydraulic modeling and LiDAR derivate DEM with 0.5 m spatial resolution. The results were compared with official flood hazards maps developed for the same recurrence intervals by the hydrologists of National Administration “Romanian Waters” (NARW) based on MIKE SHE modeling software and a DEM with 2 m spatial resolutions. It was revealed that the 1D HEC-RAS provides a more realistic perspective about the possible flood threats within Jijia floodplain and improves the accuracy of the official flood hazard maps obtained according to Flood Directive 2007/60/EC.

scholarly journals Assessment of Switchgrass-Based Bioenergy Supply Using GIS-Based Fuzzy Logic and Network Optimization in Missouri (U.S.A.)

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4516
Author(s):  
Huynh Truong Gia Nguyen ◽  
Erik Lyttek ◽  
Pankaj Lal ◽  
Taylor Wieczerak ◽  
Pralhad Burli
Keyword(s):  
Land Use ◽  
Fuzzy Logic ◽  
Network Optimization ◽  
Urban Areas ◽  
Geographical Information Systems ◽  
Large Scale ◽  
Spatial Information ◽  
Geographical Information ◽  
Negative Consequences ◽  
Analytical Approaches

Bioenergy has been globally recognized as one of the sustainable alternatives to fossil fuels. An assured supply of biomass feedstocks is a crucial bottleneck for the bioenergy industry emanating from uncertainties in land-use changes and future prices. Analytical approaches deriving from geographical information systems (GIS)-based analysis, mathematical modeling, optimization analyses, and empirical techniques have been widely used to evaluate the potential for bioenergy feedstock. In this study, we propose a three-phase methodology integrating fuzzy logic, network optimization, and ecosystem services assessment to estimate potential bioenergy supply. The fuzzy logic analysis uses multiple spatial criteria to identify suitable biomass cultivating regions. We extract spatial information based on favorable conditions and potential constraints, such as developed urban areas and croplands. Further, the network analysis uses the road network and existing biorefineries to evaluate feedstock production locations. Our analysis extends previous studies by incorporating biodiversity and ecologically sensitive areas into the analysis, as well as incorporating ecosystem service benefits as an additional driver for adoption, ensuring that biomass cultivation will minimize the negative consequences of large-scale land-use change. We apply the concept of assessing the potential for switchgrass-based bioenergy in Missouri to the proposed methodology.

Large-scale patterns in habitat structure on subtidal rocky reefs in New South Wales

2000 ◽  
Vol 51 (3) ◽  
pp. 255 ◽  
Author(s):  
N. L. Andrew ◽  
A. L. O'Neill
Keyword(s):  
Sea Urchin ◽  
Geographical Information Systems ◽  
Large Scale ◽  
Size Structure ◽  
New South ◽  
New South Wales ◽  
Geographical Information ◽  
South Wales ◽  
Subtidal Rocky Reefs ◽  
A Site

Aerial photography was used to estimate the representation of shallow subtidal habitats in New South Wales. Sixty sites, each between 4 and 5 hectares, were mapped with Geographical Information Systems software using ortho-rectified images digitized from 1:8000-scale photographs and ‘ground truthed’ in the field by divers. Barrens habitat covered an estimated 50% (s.e. = 3.9) of nearshore reefs between Port Stephens and Disaster Bay. Coverage of barrens habitat was greatest in Disaster Bay (68%, s.e. = 6.7) and least south of Disaster Bay (1%, s.e. = 0.3). There were clear differences among localities in the area of reef within the mapped sites; those at Cape Howe, Nadgee, and Turingal were significantly smaller in area than all others. There was no clear latitudinal trend in these differences but there was evidence of sand inundation at a site at Nadgee, where the reef was small. Differences in the densities and size-structure of the sea urchin Centrostephanus rodgersiiat 27 of the mapped sites provide a basis for testing relationships between the demography of this species and the persistence of the barrens habitat. The extensive coverage of the barrens habitat in New South Wales is likely to limit the productivity of the abalone industry. The development of a sea urchin fishery may have large impacts on habitat representation on nearshore reefs.

scholarly journals Using building types and demographic data to improve our understanding and use of urban sprawl simulation

2019 ◽  
Vol 2 ◽  
pp. 1-8
Author(s):  
Mojtaba Eslahi ◽  
Rani El Meouche ◽  
Anne Ruas
Keyword(s):  
Cellular Automata ◽  
Urban Growth ◽  
Urban Areas ◽  
Geographical Information Systems ◽  
Dynamic Models ◽  
Urban Expansion ◽  
Demographic Data ◽  
Population Data ◽  
Geographical Information ◽  
Sleuth Model

<p><strong>Abstract.</strong> Many studies, using various modeling approaches and simulation tools have been made in the field of urban growth. A multitude of models, with common or specific features, has been developed to reconstruct the spatial occupation and changes in land use. However, today most of urban growth techniques just use the historical geographic data such as urban, road and excluded maps to simulate the prospective urban maps. In this paper, adding buildings and population data as urban fabric factors, we define different urban growth simulation scenarios. Each simulation corresponds to policies that are more or less restrictive of space considering what these territories can accommodate as a type of building and as a global population.</p><p>Among the urban growth modeling techniques, dynamic models, those based on Cellular Automata (CA) are the most common for their applications in urban areas. CA can be integrated with Geographical Information Systems (GIS) to have a high spatial resolution model with computational efficiency. The SLEUTH model is one of the cellular automata models, which match the dynamic simulation of urban expansion and could be adapted to morphological model of the urban configuration and fabric.</p><p>Using the SLEUTH model, this paper provides different simulations that correspond to different land priorities and constraints. We used common data (such as topographic, buildings and demography data) to improve the realism of each simulation and their adequacy with the real world. The findings allow having different images of the city of tomorrow to choose and reflect on urban policies.</p>

Field validation of a free-agent cellular automata model of fire spread with fire - atmosphere coupling

2013 ◽  
Vol 22 (2) ◽  
pp. 148 ◽  
Author(s):  
Gary L. Achtemeier
Keyword(s):  
Cellular Automata ◽  
Autonomous Agents ◽  
Meteorological Data ◽  
Fire Spread ◽  
Cellular Automata Model ◽  
Fire Model ◽  
Wind Speeds ◽  
Computational Speed ◽  
Measured Time ◽  
Heat Released

A cellular automata fire model represents ‘elements’ of fire by autonomous agents. A few simple algebraic expressions substituted for complex physical and meteorological processes and solved iteratively yield simulations for ‘super-diffusive’ fire spread and coupled surface-layer (2-m) fire–atmosphere processes. Pressure anomalies, which are integrals of the thermal properties of the overlying heated plume, drive the surface winds around and through the fire. Five simulations with differing fuel and wind conditions were compared with fire and meteorological data from an experimental grassfire (FireFlux). The fire model accurately simulated bulk patterns of measured time-series of 2-m winds at two towers and observed fire behaviour (spread rate, flaming depth and heat released). Fidelity to spatial windfields in the vicinity of the fire was similar to results from full-physics fire models for other grassfires. Accurate predictions of fire spread depend critically on accurate wind speeds and directions at the location of the fire. Simulated fire–atmosphere coupling using FireFlux data increased wind speeds across the fire line by up to a factor of three. With its computational speed relative to full-physics models, the fire model can inform full-physics modellers regarding problems of interest. Although the fire model is tested for homogeneous fuels on flat terrain, the model is designed for simulating complex distributions of fire within heterogeneous distributions of fuels over complex landscapes.

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