scholarly journals Fire Activity and Their Relationship with the Global Fire Weather Index Database Components in Guinea

2019 ◽  
Vol 8 (2) ◽  
pp. 18
Author(s):  
Mamadou Baïlo Barry ◽  
Daouda Badiane ◽  
Saïdou Moustapha Sall ◽  
Moussa Diakhaté ◽  
Habib Senghor
Keyword(s):  
Statistical Analysis ◽  
Fire Behavior ◽  
Burned Area ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Burned Areas ◽  
Active Fire ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

The relationships between the Canadian Fire Weather Index (FWI) System components and the monthly burned area as well as the number of active fire which has taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua/TERRA were investigated in 32 Guinean stations between 2003 and 2013. A statistical analysis based on a multi-linear regression model was used to estimate the skills of FWI components on the predictability of burned area and active fire. This statistical analysis gave performances explaining between 16 to 79% of the variance for the burned areas and between 29 and 82% of the variance for the number of fires (P<0.0001) at lag 0. Respectively 16 to 79 % and 29 to 82 % of the variance of the burned areas and variance for the number of fires (P<0.0001) at lag0 can be explained based on the same statistical analysis. All the combinations used gave significant performances to predict the burned areas and active fire on the monthly timescale in all stations excepted Fria and Yomou where the predictability of the burned areas was not obvious. We obtained a significant correlation between the average over all of the stations of burned areas, active fires and FWI composites with percentage of variance between (75 to 84% and 29 to 77%) for active fires and burned areas at lag0 respectively. While for burned area peak (January), the skill of the predictability remains significant only one month in advance, for the active fires, the model remains skilful 1 to 3 months in advance. Results also showed that active fires are more related to fire behavior indices while the burned areas are related to the fine fuel moisture codes. These outcomes have implications for seasonal forecasting of active fire events and burned areas based on FWI components, as significant predictability is found from 1 to 3 months and one month before respectively.

Accuracy and spatiotemporal distribution of fire in the Brazilian biomes from the MODIS burned-area products

2020 ◽  
Vol 29 (10) ◽  
pp. 907 ◽  
Author(s):  
Nickolas Castro Santana ◽  
Osmar Abílio de Carvalho Júnior ◽  
Roberto Arnaldo Trancoso Gomes ◽  
Renato Fontes Guimarães
Keyword(s):  
Confusion Matrix ◽  
Burned Area ◽  
Accuracy Analysis ◽  
Visual Interpretation ◽  
Burned Areas ◽  
Active Fire ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Area Product ◽  
Area Monitoring

The Moderate Resolution Imaging Spectroradiometer (MODIS) products are the most used in burned-area monitoring, on regional and global scales. This research aims to evaluate the accuracy of the MODIS burned-area and active-fire products to describe fire patterns in Brazil in the period 2001–2015. The accuracy analysis, in the year 2015, compared the MODIS products (MCD45/MCD64) and the burned areas extracted by the visual interpretation of the LANDSAT/Operational Land Imager (OLI) images from the confusion matrix. The accuracy analysis of the active-fire products (MOD14/MYD14) in the year 2015 used linear regression. We used the most accurate burned-area product (MCD64), in conjunction with environmental variables of land use and climate. The MCD45 product presented a high error of commission (&gt;36.69%) and omission (&gt;77.04%) for the whole country. The MCD64 product had fewer errors of omission (64.05%) compared with the MCD45 product, but increased errors of commission (45.85%). MCD64 data in 2001–2015 showed three fire domains in Brazil determined by the climatic pattern. Savanna and grassy areas in semi-humid zones are the most prone areas to fire, burning an average of 25% of their total area annually, with a fire return interval of 5–6 years.

scholarly journals A high-resolution reanalysis of global fire weather from 1979 to 2018 – Overwintering the Drought Code

2020 ◽  
Author(s):  
Megan McElhinny ◽  
Justin F. Beckers ◽  
Chelene Hanes ◽  
Mike Flannigan ◽  
Piyush Jain
Keyword(s):  
High Resolution ◽  
Fire Behavior ◽  
Fire Season ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Start Up ◽  
System Calculation ◽  
Second Procedure ◽  
Temporal Coverage

Abstract. We present a global high-resolution calculation of the Canadian Fire Weather Index (FWI) System Indices using surface meteorology from the ERA5-HRS reanalysis for 1979–2018. ERA5-HRS represents an improved dataset compared to several other reanalyses in terms of accuracy, as well as spatial and temporal coverage. The FWI calculation is performed using two different procedures for setting the start-up value of the Drought Code (DC) at the beginning of the fire season. The first procedure, which accounts for the effects of inter-seasonal drought, overwinters the DC by adjusting the fall DC value with a fraction of accumulated overwinter precipitation. The second procedure sets the DC to its default start-up value (i.e. 15) at the start of each fire season. We validate the FWI values over Canada using station observations from Environment and Climate Change Canada and find generally good agreement (mean Spearman correlation of 0.77). We also show that significant differences in early season DC and FWI values can occur when the FWI System calculation is started using the overwintered versus default DC values, as is highlighted by an example from 2016 over North America. The FWI System moisture codes and fire behavior indices are made available for both versions of the calculation at https://doi.org/10.5281/zenodo.3626193 (McElhinny et al., 2020), although we recommend using codes and indices calculated with the overwintered DC, unless specific research requirements dictate otherwise.

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;

Global assessment of the temporal reporting accuracy and precision of the MODIS burned area product

2010 ◽  
Vol 19 (6) ◽  
pp. 705 ◽  
Author(s):  
Luigi Boschetti ◽  
David P. Roy ◽  
Christopher O. Justice ◽  
Louis Giglio
Keyword(s):  
Fire Detection ◽  
Time Difference ◽  
Systematic Evaluation ◽  
Burned Area ◽  
Reporting Accuracy ◽  
Active Fire ◽  
Accuracy And Precision ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Area Product

A method for the systematic evaluation of the temporal reporting accuracy and precision of burned area products conducted using active fire detections as the reference dataset is described. The method is applied globally to 6 years of Moderate Resolution Imaging Spectroradiometer (MODIS) burned area and active fire product data. The distribution of the time difference between active fire and burned area detections that occur within 90 days is analysed and summary statistics extracted globally. The median time difference in reporting between the MODIS burned area and the active fire product detections is 1 day and the majority of MODIS burned area product detections occur temporally close to an active fire detection: 50% within a single day and 75% within 4 days. Users of the MODIS burned area product with temporal reporting requirements should be aware of these findings if using the approximate day of burning information provided in the burned area product.

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.

scholarly journals UTILISATION OF NASA - GFWED AND FIRMS SATELLITE DATA IN DETERMINING THE PROBABILITY OF HOTSPOTS USING THE FIRE WEATHER INDEX (FWI) IN OGAN KOMERING ILIR REGENCY, SOUTH SUMATRA

2020 ◽  
Vol 17 (1) ◽  
pp. 85
Author(s):  
Hermanto Asima Nainggolan ◽  
Desak Putu Okta Veanti ◽  
Dzikrullah Akbar
Keyword(s):  
Conditional Probability ◽  
Forest Fire ◽  
Satellite Data ◽  
Burned Area ◽  
Fire Weather ◽  
Meteorological Observation ◽  
Weather Index ◽  
Fire Weather Index ◽  
Negative Impacts ◽  
Conditional Probability Analysis

Prevention and mitigation of forest and land fires have important roles considering its various negative impacts. Throughout 2018, in Ogan Komering Ilir District, 864 hectares of land burned. This data increased significantly compared to the burned area in the previous year. Lack of field meteorological observation is still a problem in solving the problem of forest fire in the region. Consequently, we utilize NASA - GFWED and FIRMS satellite data to analyze the hotspots probabilities in Ogan Komering Ilir District, South Sumatra. Conditional probability analysis will be used to find out the likelihood of hotspots based on FWI and FFMC from 2001 to 2016. More than 50 percent of hotspots appear during extreme FFMC class and high to extreme FWI class. The probability of hotspots for extreme FFMC class and extreme FWI class varied between 0.3 to 10.4 % and 0.1 to 3.8 % respectively. Meanwhile, fire-prone areas with the highest density of fires are in the sub-district of Tulung Selapan, and the safest region is the Cengal sub-district. 

scholarly journals Deciphering Active Wildfires in the Southwestern USA Using Topological Data Analysis

Climate ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 135
Author(s):  
Hannah Kim ◽  
Christian Vogel
Keyword(s):  
Data Analysis ◽  
American Southwest ◽  
Topological Data Analysis ◽  
Weather Data ◽  
Fire Weather ◽  
Weather Variables ◽  
Fire Weather Index ◽  
Active Fire ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Topological Data

The recent droughts in the American Southwest have led to increasing risks of wildfires, which pose multiple threats to the regional and national economy and security. Wildfires cause serious air quality issues during dry seasons and can increase the number of mud and landslides in any subsequent rainy seasons. However, while wildfires are often correlated with warm and dry climates, this relationship is not linear, implying that there may be other factors influencing these fires. The objective of this study was to detect and classify any nonlinear patterns in weather data by applying Topological Data Analysis (TDA) to various weather variables, such as temperature, relative humidity, and precipitation, and the five most and least intense summer fire seasons as determined by the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire products. In addition to TDA, persistence diagrams and frequency plots were also used to compare fire seasons and regions in the American Southwest. Active fire seasons were more likely to have a significant correlation between the weather variables and wildfires, the Fire Weather Index (FWI) alone was not an accurate predictor for wildfires in California and Nevada, and fire weather is highly dependent upon the region and season.

scholarly journals The Hot-Dry-Windy Index: A New Fire Weather Index

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 279 ◽  
Author(s):  
Alan Srock ◽  
Joseph Charney ◽  
Brian Potter ◽  
Scott Goodrick
Keyword(s):  
Multiple Scales ◽  
Wildland Fire ◽  
Meteorological Data ◽  
Fire Behavior ◽  
Weather Conditions ◽  
Meteorological Variables ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
Complex Interactions

Fire weather indices are commonly used by fire weather forecasters to predict when weather conditions will make a wildland fire difficult to manage. Complex interactions at multiple scales between fire, fuels, topography, and weather make these predictions extremely difficult. We define a new fire weather index called the Hot-Dry-Windy Index (HDW). HDW uses the basic science of how the atmosphere can affect a fire to define the meteorological variables that can be predicted at synoptic-and meso-alpha-scales that govern the potential for the atmosphere to affect a fire. The new index is formulated to account for meteorological conditions both at the Earth’s surface and in a 500-m layer just above the surface. HDW is defined and then compared with the Haines Index (HI) for four historical fires. The Climate Forecast System Reanalysis (CFSR) is used to provide the meteorological data for calculating the indices. Our results indicate that HDW can identify days on which synoptic-and meso-alpha-scale weather processes can contribute to especially dangerous fire behavior. HDW is shown to perform better than the HI for each of the four historical fires. Additionally, since HDW is based on the meteorological variables that govern the potential for the atmosphere to affect a fire, it is possible to speculate on why HDW would be more or less effective based on the conditions that prevail in a given fire case. The HI, in contrast, does not have a physical basis, which makes speculation on why it works or does not work difficult because the mechanisms are not clear.

scholarly journals FIRE BEHAVIOR VARIABLES AND HAZARD INDICES OF FOREST FIRES

2018 ◽  
Vol 42 (3) ◽  
Author(s):  
Fillipe Tamiozzo Pereira Torres ◽  
Gumercindo Souza Lima ◽  
Bráulio Furtado Alvares
Keyword(s):  
Forest Fires ◽  
Fire Hazard ◽  
Fire Behavior ◽  
Meteorological Conditions ◽  
Fire Weather ◽  
Fuel Moisture ◽  
Combustible Material ◽  
Hazard Indices ◽  
Weather Index ◽  
Fire Weather Index

ABSTRACT The objective of this study was to evaluate the performance of different fire hazard indices (FWI, FMA, FMA+, Telicyn, Nesterov, P-EVAP and EVAP/P), taking into account the fire behavior variables and the susceptibility to fire expressed by the moisture of the combustible material. For this purpose, controlled burnings were performed at different times and information was recorded in relation to the meteorological conditions, characteristics of the combustible material and fire behavior variables. In general, all the indices presented significant correlations with both the moisture of the combustible material and the behavior of the fire. However, in general, a higher linear correlation of components of the Canadian Fire Weather Index (FWI) system was observed in predicting fire behavior and EVAP / P index in fuel moisture. The consistency of the correlations between the various indices and the analyzed variables makes the methodology possible to be used in any place, facilitating the decision making in regions where records of occurrences of forest fires are absent or unreliable.

Fire behavior in aspen slash fuels as related to the Canadian Fire Weather Index

1982 ◽  
Vol 12 (4) ◽  
pp. 1028-1029 ◽  
Author(s):  
Martin E. Alexander
Keyword(s):  
Forest Fire ◽  
Fire Behavior ◽  
Prescribed Fires ◽  
Fire Weather ◽  
Fuel Moisture ◽  
Trembling Aspen ◽  
Short Term ◽  
Weather Index ◽  
Fire Weather Index ◽  
Forest Fire Danger

The characteristics and short-term results of experimental prescribed fires in 2-year-old trembling aspen (Populustremuloides Michx.) logging slash in northern Minnesota have been described by D. A. Perala (1974. Can. J. For. Res. 4: 222–228). The associated burning conditions are expressed here in terms of the weather-dependent numerical fuel moisture codes and fire behavior indexes of the Canadian system of forest fire danger rating.

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