@techreport{petrasWildfireModelingGRASS2014,
  title = {Wildfire Modeling in {{GRASS GIS}}},
  author = {Petras, Vaclav},
  year = {2014},
  month = apr,
  abstract = {[Description] This paper introduces implementation of wildfire modeling tool for GRASS GIS named r.fire.spread based on existing r.ros and r.spread modules which were reviewed as part of this project. The new tools was tested in the Lewis Mountain study area in Shenandoah National Park in Virginia and compared to an actual fire which happened in the area in April 2006.

[Excerpt: Introduction] The core of wildre spread modeling in GRASS GIS [Neteler et al. 2012] consists of two modules r.ros and r.spread [Xu 1994]. The r.ros module computes rate of spread and the r.spread performs the re spread simulation including the computation of possible spotting. The additional processing can be done using r.spreadpath or other GRASS GIS modules as well as preparation of the input data for the simulation where for example, r.reclass can by used to convert input data from a certain fuel model to the fuel model used by r.ros and r.spread modules. Additionally, these modules can be used to simulate also other events, not only re spread, when proper inputs are specied [Indruszewski and Barton 2006].

[\textbackslash n] The re models are compared to real wildres or to controlled test res [Clements et al. 2007]. The GRASS GIS wildre modeling tools were developed in the US context but recently these tools were also successfully tested in Europe [Di Leo et al. 2013; de Rigo et al. 2013].

[\textbackslash n] However, the GRASS GIS r.ros and r.spread modules accept only one state of input parameters and changes in weather conditions are not supported. Moreover, the r.spread module produces only the resulting burned area and does not produce states of burned area during simulation. Thus, I implemented a higher level interface for r.ros and r.spread modules in the way that it accepts time series of input data and yields these intermediate states.

[\textbackslash n] In order to ensure quality of the wildre modeling tools the tools will be tested in the Lewis Mountain study area where an actual re happened.

[\textbackslash n] [...]

[Results] I implemented a first prototype of the r.re.spread module which accepts several moisture and wind states and corresponding times. The module performs the simulation of the re spread according to changing moisture and wind conditions. It is possible to specify interval in which intermediate states of the re spread should be exported. The r.re.spread module uses r.ros and r.spread modules in the background.

[\textbackslash n] Unfortunately, due to the fact that input parameters for the simulation were determined by running the simulation several times and changing the input parameters to t the simulation result to the real re data, it is was not possible to use this data for exact testing of the existing modules and newly developed module. Thus, the test of the tools should be seen as a rst step in a calibration of the wildre spread model. [...]

[Future work] Because the input and outputs of the r.re.spread modules are time series of data, the inputs and outputs should be temporal datasets. However, this may limit simple usages of this module and may require user to always use the temporal datasets3 or number of parameters would grow signicantly (if both classic series and temporal datasets would be supported). 

[\textbackslash n] Although some changes in documentation were done already, much more changes are still need due to the fact that the combining of general and re-related terminology is present in all parts of the documentation. Additionally, the module r.re.spread currently lacks documentation. In this case, the documentation will use only re-related terminology.

[\textbackslash n] [...]

[Conclusion] The new higher level interface for wildre modeling in GRASS GIS is in the stage of a rst prototype. The test in the study area showed that the implementation of the higher lever interface as well as the underlying modules are capable of simulating wildre spread at certain conditions. The new interface for wildre modeling, r.re.spread module, is not yet available in the ocial GRASS GIS Addons repository but it will hopefully be available in the future. Currently, r.re.spread module is available at NCSU GeoForAll Lab repository.

[\textbackslash n] [...]},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14133935,data-transformation-modelling,environmental-modelling,geospatial,grass-gis,wildfires},
  lccn = {INRMM-MiD:c-14133935}
}

{"_id":"Hrd24DX6SMiipJp2M","bibbaseid":"petras-wildfiremodelingingrassgis-2014","downloads":0,"creationDate":"2017-06-22T15:25:08.006Z","title":"Wildfire Modeling in GRASS GIS","author_short":["Petras, V."],"year":2014,"bibtype":"techreport","biburl":"https://sharefast.me/php/download.php?id=zOUKvA&token=29","bibdata":{"bibtype":"techreport","type":"techreport","title":"Wildfire Modeling in GRASS GIS","author":[{"propositions":[],"lastnames":["Petras"],"firstnames":["Vaclav"],"suffixes":[]}],"year":"2014","month":"April","abstract":"[Description] This paper introduces implementation of wildfire modeling tool for GRASS GIS named r.fire.spread based on existing r.ros and r.spread modules which were reviewed as part of this project. The new tools was tested in the Lewis Mountain study area in Shenandoah National Park in Virginia and compared to an actual fire which happened in the area in April 2006. [Excerpt: Introduction] The core of wildre spread modeling in GRASS GIS [Neteler et al. 2012] consists of two modules r.ros and r.spread [Xu 1994]. The r.ros module computes rate of spread and the r.spread performs the re spread simulation including the computation of possible spotting. The additional processing can be done using r.spreadpath or other GRASS GIS modules as well as preparation of the input data for the simulation where for example, r.reclass can by used to convert input data from a certain fuel model to the fuel model used by r.ros and r.spread modules. Additionally, these modules can be used to simulate also other events, not only re spread, when proper inputs are specied [Indruszewski and Barton 2006]. [\\n] The re models are compared to real wildres or to controlled test res [Clements et al. 2007]. The GRASS GIS wildre modeling tools were developed in the US context but recently these tools were also successfully tested in Europe [Di Leo et al. 2013; de Rigo et al. 2013]. [\\n] However, the GRASS GIS r.ros and r.spread modules accept only one state of input parameters and changes in weather conditions are not supported. Moreover, the r.spread module produces only the resulting burned area and does not produce states of burned area during simulation. Thus, I implemented a higher level interface for r.ros and r.spread modules in the way that it accepts time series of input data and yields these intermediate states. [\\n] In order to ensure quality of the wildre modeling tools the tools will be tested in the Lewis Mountain study area where an actual re happened. [\\n] [...] [Results] I implemented a first prototype of the r.re.spread module which accepts several moisture and wind states and corresponding times. The module performs the simulation of the re spread according to changing moisture and wind conditions. It is possible to specify interval in which intermediate states of the re spread should be exported. The r.re.spread module uses r.ros and r.spread modules in the background. [\\n] Unfortunately, due to the fact that input parameters for the simulation were determined by running the simulation several times and changing the input parameters to t the simulation result to the real re data, it is was not possible to use this data for exact testing of the existing modules and newly developed module. Thus, the test of the tools should be seen as a rst step in a calibration of the wildre spread model. [...] [Future work] Because the input and outputs of the r.re.spread modules are time series of data, the inputs and outputs should be temporal datasets. However, this may limit simple usages of this module and may require user to always use the temporal datasets3 or number of parameters would grow signicantly (if both classic series and temporal datasets would be supported). [\\n] Although some changes in documentation were done already, much more changes are still need due to the fact that the combining of general and re-related terminology is present in all parts of the documentation. Additionally, the module r.re.spread currently lacks documentation. In this case, the documentation will use only re-related terminology. [\\n] [...] [Conclusion] The new higher level interface for wildre modeling in GRASS GIS is in the stage of a rst prototype. The test in the study area showed that the implementation of the higher lever interface as well as the underlying modules are capable of simulating wildre spread at certain conditions. The new interface for wildre modeling, r.re.spread module, is not yet available in the ocial GRASS GIS Addons repository but it will hopefully be available in the future. Currently, r.re.spread module is available at NCSU GeoForAll Lab repository. [\\n] [...]","keywords":"*imported-from-citeulike-INRMM,~INRMM-MiD:c-14133935,data-transformation-modelling,environmental-modelling,geospatial,grass-gis,wildfires","lccn":"INRMM-MiD:c-14133935","bibtex":"@techreport{petrasWildfireModelingGRASS2014,\n title = {Wildfire Modeling in {{GRASS GIS}}},\n author = {Petras, Vaclav},\n year = {2014},\n month = apr,\n abstract = {[Description] This paper introduces implementation of wildfire modeling tool for GRASS GIS named r.fire.spread based on existing r.ros and r.spread modules which were reviewed as part of this project. The new tools was tested in the Lewis Mountain study area in Shenandoah National Park in Virginia and compared to an actual fire which happened in the area in April 2006.\n\n[Excerpt: Introduction] The core of wildre spread modeling in GRASS GIS [Neteler et al. 2012] consists of two modules r.ros and r.spread [Xu 1994]. The r.ros module computes rate of spread and the r.spread performs the re spread simulation including the computation of possible spotting. The additional processing can be done using r.spreadpath or other GRASS GIS modules as well as preparation of the input data for the simulation where for example, r.reclass can by used to convert input data from a certain fuel model to the fuel model used by r.ros and r.spread modules. Additionally, these modules can be used to simulate also other events, not only re spread, when proper inputs are specied [Indruszewski and Barton 2006].\n\n[\\textbackslash n] The re models are compared to real wildres or to controlled test res [Clements et al. 2007]. The GRASS GIS wildre modeling tools were developed in the US context but recently these tools were also successfully tested in Europe [Di Leo et al. 2013; de Rigo et al. 2013].\n\n[\\textbackslash n] However, the GRASS GIS r.ros and r.spread modules accept only one state of input parameters and changes in weather conditions are not supported. Moreover, the r.spread module produces only the resulting burned area and does not produce states of burned area during simulation. Thus, I implemented a higher level interface for r.ros and r.spread modules in the way that it accepts time series of input data and yields these intermediate states.\n\n[\\textbackslash n] In order to ensure quality of the wildre modeling tools the tools will be tested in the Lewis Mountain study area where an actual re happened.\n\n[\\textbackslash n] [...]\n\n[Results] I implemented a first prototype of the r.re.spread module which accepts several moisture and wind states and corresponding times. The module performs the simulation of the re spread according to changing moisture and wind conditions. It is possible to specify interval in which intermediate states of the re spread should be exported. The r.re.spread module uses r.ros and r.spread modules in the background.\n\n[\\textbackslash n] Unfortunately, due to the fact that input parameters for the simulation were determined by running the simulation several times and changing the input parameters to t the simulation result to the real re data, it is was not possible to use this data for exact testing of the existing modules and newly developed module. Thus, the test of the tools should be seen as a rst step in a calibration of the wildre spread model. [...]\n\n[Future work] Because the input and outputs of the r.re.spread modules are time series of data, the inputs and outputs should be temporal datasets. However, this may limit simple usages of this module and may require user to always use the temporal datasets3 or number of parameters would grow signicantly (if both classic series and temporal datasets would be supported). \n\n[\\textbackslash n] Although some changes in documentation were done already, much more changes are still need due to the fact that the combining of general and re-related terminology is present in all parts of the documentation. Additionally, the module r.re.spread currently lacks documentation. In this case, the documentation will use only re-related terminology.\n\n[\\textbackslash n] [...]\n\n[Conclusion] The new higher level interface for wildre modeling in GRASS GIS is in the stage of a rst prototype. The test in the study area showed that the implementation of the higher lever interface as well as the underlying modules are capable of simulating wildre spread at certain conditions. 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