scholarly journals Visualization of Fire Weather Index in Aek Godang Based on the Machine Learning Approach

2021 ◽  
Vol 1 (1) ◽  
pp. 22-28
Author(s):  
Kerista Tarigan ◽  
Edison Kurniawan ◽  
Sri Wahyuni
Keyword(s):  
Machine Learning ◽  
Forest Fires ◽  
Environmental Harm ◽  
Learning Approach ◽  
Fire Weather ◽  
Weather Index ◽  
Information Mining ◽  
Fire Weather Index ◽  
Machine Learning Approach

Forest fires are a major natural issue, making temperate and environmental harm whereas dangering human lives. The examined and study for timberland fire had been worn out Aek Godang, Northern Sumatera, Indonesia. There are 26 hotspots in 2017 near Aek Godang, North Sumatera, Indonesia. In this consider, we utilize an information mining approach to prepare and test the information of woodland fire and Fire Weather Index (FWI) from meteorological information. The point of this ponders to anticipate the burned range and distinguish the woodland fire in Aek Godang ranges, North Sumatera. The result of this considers shown the Fire battling and avoidance movement may be one reason for the watched need of relationship. The reality that this dataset exists demonstrates that there's as of now a few exertions going into fire avoidance.

scholarly journals Proposal of an Iot Solution to Fire Risk Assessment Problem

2020 ◽  
Author(s):  
Ana Bernardo ◽  
Pedro Silva ◽  
Paulo Fazendeiro
Keyword(s):  
Forest Fires ◽  
Fire Risk ◽  
Initial Response ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Keywords Internet ◽  
The Common ◽  
Civic Awareness ◽  
Municipal Level

Several of the fighting weaknesses evidenced by the forest fires tragedies of the last years are rooted in the disconnection between the current technical/scientific resources and the availability of the resulting information to operational agents on the ground. In order to be effective, a pre-emptive response to similar disasters must include the articulation between local authorities at municipal level - in prevention, preparedness and initial response - and the common citizen who is on the field, resides there, and has a deeper knowledge about the field of operation. This work intends to take a first step in the development of a tool that can serve to improve the civic awareness of all and to support the decision-making of the competent authorities. Keywords: Internet of things, Citizen science, Fire weather index

Fire activity in Portugal and its relationship to weather and the Canadian Fire Weather Index System

2008 ◽  
Vol 17 (3) ◽  
pp. 328 ◽  
Author(s):  
A. Carvalho ◽  
M. D. Flannigan ◽  
K. Logan ◽  
A. I. Miranda ◽  
C. Borrego
Keyword(s):  
Forest Fires ◽  
Daily Maximum ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Area Burned ◽  
System Components ◽  
Baseline Information ◽  
Forward Stepwise ◽  
Maximum Temperatures

The relationships among the weather, the Canadian Fire Weather Index (FWI) System components, the monthly area burned, and the number of fire occurrences from 1980 to 2004 were investigated in 11 Portuguese districts that represent respectively 66% and 61% of the total area burned and number of fires in Portugal. A statistical approach was used to estimate the monthly area burned and the monthly number of fires per district, using meteorological variables and FWI System components as predictors. The approach succeeded in explaining from 60.9 to 80.4% of the variance for area burned and between 47.9 and 77.0% of the variance for the number of fires; all regressions were highly significant (P < 0.0001). The monthly mean and the monthly maximum of daily maximum temperatures and the monthly mean and extremes (maximum and 90th percentile) of the daily FWI were selected for all districts, except for Bragança and Porto, in the forward stepwise regression for area burned. For all districts combined, the variance explained was 80.9 and 63.0% for area burned and number of fires, respectively. Our results point to highly significant relationships among forest fires in Portugal and the weather and the Canadian FWI System. The present analysis provides baseline information for predicting the area burned and number of fires under future climate scenarios and the subsequent impacts on air quality.

Wildfires and the Canadian Forest Fire Weather Index system for the Daxing'anling region of China

2011 ◽  
Vol 20 (8) ◽  
pp. 963 ◽  
Author(s):  
Xiaorui Tian ◽  
Douglas J. McRae ◽  
Jizhong Jin ◽  
Lifu Shu ◽  
Fengjun Zhao ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Coniferous Forest ◽  
Northern China ◽  
Fire Danger ◽  
Fire Season ◽  
Fire Weather ◽  
Burnt Area ◽  
Weather Index ◽  
Fire Weather Index

The Canadian Forest Fire Weather Index (FWI) system was evaluated for the Daxing'anling region of northern China for the 1987–2006 fire seasons. The FWI system reflected the regional fire danger and could be effectively used there in wildfire management. The various FWI system components were classified into classes (i.e. low to extreme) for fire conditions found in the region. A total of 81.1% of the fires occurred in the high, very high and extreme fire danger classes, in which 73.9% of the fires occurred in the spring (0.1, 9.5, 33.3 and 33.1% in March, April, May and June). Large wildfires greater than 200 ha in area (16.7% of the total) burnt 99.2% of the total burnt area. Lightning was the main ignition source for 57.1% of the total fires. Result show that forest fires mainly occurred in deciduous coniferous forest (61.3%), grass (23.9%) and deciduous broad leaved forest (8.0%). A bimodal fire season was detected, with peaks in May and October. The components of FWI system were good indicators of fire danger in the Daxing'anling region of China and could be used to build a working fire danger rating system for the region.

Sensitivity of the CFFDRS Fire Weather Index parameters for Indian weather conditions

2021 ◽  
Author(s):  
Anasuya Barik ◽  
Somnath Baidya Roy
Keyword(s):  
Forest Fires ◽  
Fire Hazard ◽  
Fire Behavior ◽  
Fire Danger ◽  
Model Parameters ◽  
Fire Weather ◽  
Weather Index ◽  
Climatic Zones ◽  
Fire Weather Index ◽  
Fire Model

&lt;p&gt;The Canadian Forest Fire Danger Rating System (CFFDRS) is used to assess and predict the fire behavior in various forest ecosystems all over the world. The Fire Weather Index (FWI) module of the CFFDRS models the relationship between meteorology and forest fires. It was observed in our earlier study that the values of the FWI and its related parameters were considerably different from the other countries that use the model for their operational fire weather simulation. In this study we evaluate the model performance over Indian climate for a period of 10 years 1996-2005 under various weather scenarios. The daily meteorological data from ECMWF&amp;#8217;s ERA5 reanalysis has been used as inputs to the fire model and the active fire data from MODIS Terra and Aqua satellites over the study period has been used to evaluate the capability of model to simulate fire danger. As India has many different climatic zones, we evaluated the behavior fire model parameters over 5 forest zones namely Himalayan, Deciduous, Western Ghats, Thorn forests and North Eastern forests based on the Roy et al. 2016 Land Use Land Cover data and Koppen climatic zones.&amp;#160; The analysis was narrowed down over only the forest areas of the zones so as to remove any chances of including the non-forest fires detected by the satellite. Results show that the FWI shows a strong correlation with forest fires if the model is correctly spun up and appropriately calibrated. A spin up time of minimum 60 days was found to be appropriate for stabilization of FWI components like Duff Moisture Code (DMC) and Drought Code (DC). Sensitivity studies showed that temperature and relative humidity are the key controlling factors of forest fires over India and that the parameters depict high interannual seasonality due to relatively lower values during the Indian monsoon season.&lt;/p&gt;&lt;p&gt;This study is one of the first attempts to use fire models to simulate fire behavior over India. It can serve as a launchpad for further work on fire hazard prediction and effects of climate change on fire hazard in India.&lt;/p&gt;

Evaluation of the reliability of the high-resolution WRF fire danger forecasts in Poland

2021 ◽  
Author(s):  
Marta Gruszczynska ◽  
Alan Mandal ◽  
Grzegorz Nykiel ◽  
Tomasz Strzyzewski ◽  
Weronika Wronska ◽  
...  
Keyword(s):  
High Resolution ◽  
Forest Fires ◽  
Human Life ◽  
Meteorological Data ◽  
Fire Service ◽  
Fire Danger ◽  
Economic Losses ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index

&lt;p&gt;Fires negatively affect the composition and structure of fauna and flora, as well as the quality of air, soils and water. They cause economic losses and pose a risk to human life. Poland is at the forefront of European countries in terms of forest fires. Therefore, Institute of Meteorology and Water Management - National Research Institute (IMWM-NIR) implemented fire danger forecast system based on high-resolution (2.5 km) Weather Research and Forecast (WRF) model. Forecasted meteorological data are used to calculate parameters of Canadian Forest Fire Weather Index (FWI) System: Fire Weather Index (FWI), Initial Spread Index (ISI), Buildup Index (BUI), Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), and Drought Code (DC). Each parameter is presented in one of the classes corresponding to the fire danger &amp;#8211; from low to extreme. In this way, a daily 24- and 48-hour fire danger forecasts are generated for the whole area of Poland and presented on IMWM-NIR meteorological website (meteo.imgw.pl).&lt;/p&gt;&lt;p&gt;In this presentation we show analyses of reliability of implemented FWI system. For this purpose, data reprocessing from March to September 2019 were made. Also data on fires occurrence on forest lands: time of occurrence, characteristics and location, from the resources of the State Fire Service were collected. Finally, for the selected period, we obtained a dataset of about 8 thousand events for which we assigned values of FWI parameters. Generally, based on our analysis, correlation between number of fires and averaged value of FWI amounted over 0.8. We found out, the correlation coefficient calculated for regions differ. The correlation is higher in central and northern Poland compared to the eastern part of the country, which also correspond to the number of fires. This may be related to the different forest structure - there is a higher proportion of broadleaf forests in the east. The comparison of 24- and 48-hour forecasts showed that they have similar reliability.&lt;/p&gt;

Estimation of Forest Fire Risk by Using Fire Weather Index in the MENA Region

2020 ◽  
Author(s):  
Burcu Calda ◽  
Kamil Collu ◽  
Aytac Pacal ◽  
Mehmet Levent Kurnaz
Keyword(s):  
Observational Data ◽  
Forest Fire ◽  
Forest Fires ◽  
Control Period ◽  
Fire Risk ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
The Mediterranean ◽  
Forest Fire Risk

&lt;p&gt;Forest fires are naturals in the Mediterranean ecosystems. However, in the last decade, the number of wildfires has significantly increased in the Mediterranean basin along with climate change. Therefore, forecasts of this region by using fire indices are crucial to take necessary precautions. In the present study, the projected changes for the period 2070 - 2099 concerning the control period 1971 - 2000 were used to estimate forest fire risk by the Canadian Fire Weather Index (FWI). RCP4.5 and RCP8.5 emission scenarios (IPCC) outputs of MPI-ESM-MR and HadGEM2-ES dynamically downscaled to 50 km for the CORDEX-MENA domain with the use of the RegCM4 were utilized. ERA-Interim observational data from ECMWF covering the period 1980-2012 were also used to test the performances of models. The output of MPI-ESM-MR gave more similar fire risk prediction with the reforecast of observational data (ERA-Interim). Thus, the MPI-ESM-MR model could be more suitable to estimate fire risk by FWI. According to future projection, forest fire risk will significantly increase throughout the region for the last 30 years of this century.&lt;/p&gt;

scholarly journals Forest Fire Prediction in Northern Sumatera using Support Vector Machine Based on the Fire Weather Index

2020 ◽  
Author(s):  
Darwis Robinson Manalu ◽  
Muhammad Zarlis ◽  
Herman Mawengkang ◽  
Opim Salim Sitompul
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Meteorological Data ◽  
Burned Area ◽  
Support Vector ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Data Mining Approach ◽  
Prevention Activity

Forest fires are a major environmental issue, creating economical and ecological damage while dangering human lives. The investigation and survey for forest fire had been done in Aek Godang, Northern Sumatera, Indonesia. There is 26 hotspot in 2017 close to Aek Godang, North Sumatera, Indonesia. In this study, we use a data mining approach to train and test the data of forest fire and the Fire Weather Index (FWI) from meteorological data. The aim of this study to predict the burned area and identify the forest fire in Aek Godang areas, North Sumatera. The result of this study indicated that Fire fighting and prevention activity may be one reason for the observed lack of correlation. The fact that this dataset exists indicates that there is already some effort going into fire prevention.

Wildfire ignition from forestry machines in boreal Sweden

2019 ◽  
Vol 28 (9) ◽  
pp. 666 ◽  
Author(s):  
Johan Sjöström ◽  
Frida Vermina Plathner ◽  
Anders Granström
Keyword(s):  
Forest Fires ◽  
Spatial Relationship ◽  
Annual Number ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Burnt Soil ◽  
Soil Scarification ◽  
Underlying Mechanisms ◽  
Average Annual Number

Several large Swedish wildfires during recent decades were caused by forestry machinery in operation, fires for which there is still no characterisation. We combined 18 years of data on dispatches, weather and fire danger and interviewed forestry workers to understand the spatial, temporal and weather distributions of these fires, and their underlying mechanisms. We estimate the average annual number of ignitions from forestry machinery in Sweden at 330–480 (2.0±0.4 ignitions per 1000ha clear-felling) of which 34.5 led to firefighter dispatches, constituting 2.2% of all forest fire dispatches and 40% of area burnt. Soil scarification causes the most ignitions and the main mechanism is likely high-inertia contact between discs and large stones, causing sparks igniting dry humus or moss, countering reports suggesting that such metal fragments cannot fulfil ignition requirements. We found a spatial relationship between forestry machine ignitions and abundance of large stones, represented by a Boulder Index generated from a nationwide dataset. Further, 75% of the dispatches occurred on days with relative humidity &lt;45%, Duff Moisture Code (Canadian system) &gt;26 and Fire Weather Index &gt;12. 75% of the area burned when Fire Weather Index was &gt;20. Results suggest machine-caused forest fires can be largely avoided by cancelling operations in stony terrain during high-risk weather.

Environmental determinants of lightning- v. human-induced forest fire ignitions differ in a temperate mountain region of Switzerland

2010 ◽  
Vol 19 (5) ◽  
pp. 541 ◽  
Author(s):  
Björn Reineking ◽  
Patrick Weibel ◽  
Marco Conedera ◽  
Harald Bugmann
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Weather Conditions ◽  
Forest Composition ◽  
Small Range ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Independent Variables ◽  
Fire Ignitions

Understanding the environmental and human determinants of forest fire ignitions is crucial for landscape management. In this study, we consider lightning- and human-induced fires separately and evaluate the relative importance of weather, forest composition and human activities on the occurrence of forest fire ignitions in the most fire-prone region of Switzerland, the Canton Ticino. Independent variables included 14 drought and fire weather indices, forest composition and human influences. Logistic regression models were used to relate these independent variables to records of forest fires over a 37-year period (1969–2005). We found large differences in the importance of environmental and human controls on forest fire ignitions between lightning- and human-induced events: lightning-induced fires occurred in a small range of weather conditions well captured by the Duff Moisture Code from the Canadian Forest Fire Weather Index System and the LandClim Drought Index, and with negligible influence of distance to human infrastructure, whereas human-induced fires occurred in a wider range of weather conditions well captured by the Angstroem and the Fosberg Fire Weather Index, mainly in deciduous forests, and strongly depending on proximity to human infrastructure. We conclude that the suitability of fire indices can vary dramatically between ignition sources, suggesting that some of these indices are useful within certain regions and fire types only. The ignition source is an important factor that needs to be taken into account by fire managers and when developing models of forest fire occurrence.

scholarly journals ANALYSIS OF EFFICIENCY OF FIRE DANGER INDICES IN FOREST FIRE PREDICTION

2017 ◽  
Vol 41 (2) ◽  
Author(s):  
Fillipe Tamiozzo Pereira Torres ◽  
Gumercindo Souza Lima ◽  
Sebastião Venâncio Martins ◽  
Sebastião Renato Valverde
Keyword(s):  
Forest Fires ◽  
Satellite Images ◽  
Skill Score ◽  
Fire Danger ◽  
Fire Weather ◽  
Allocation Of Resources ◽  
Weather Index ◽  
Fire Weather Index ◽  
The City ◽  
Fire Danger Indices

ABSTRACT Despite the existence of different fire danger indices, the use of an inefficient index can lead to making wrong decisions on the appropriate procedures for preventing and fighting forest fires, while a trusted prediction index can help the most quantification and allocation of resources for prevention. Thereat, the objective of this study is to analyze the efficiency of Fire Weather Index (FWI), Logarithmic of Telicyn Index, Nesterov Index, cumulative indexes of precipitation - evaporation (P-EVAP) and evaporation / precipitation (EVAP/P), Monte Alegre Index (FMA) and Monte Alegre Changed Index (FMA+) in the prediction of forest fires for the city of Viçosa (MG). The indices were compared using the method known as Skill Score (SS) taking into account the days that the indexes pointed to the risk of events with focus fire identified by satellite images on the 01/01/2005 to 31/12/2014 period. According to the results, the Logarithm of Telicyn Index (0.53257) as the most efficient for the study area, followed by the indices EVAP/P (0.46553), P-EVAP (0.43724), Nesterov (0.40445), FWI (0.39213), FMA+(0.34595) and FMA (0.28982).

Sign in / Sign up

Export Citation Format

Share Document