scholarly journals Development of Google Earth Engine Fire Weather Index Calculator for Indonesian Fire Danger Rating System

2021 ◽  
Vol 936 (1) ◽  
pp. 012040
Author(s):  
J S Matondang ◽  
H Sanjaya ◽  
R Arifandri

Abstract Tropical peatlands make up almost ten percent of the land surface in Indonesia, making peat fires detrimental not only for global atmospheric carbon levels, but also to public health and socioeconomic activities in the region. Indonesian Fire Danger Rating System (FDRS) was developed based on the Canadian Forest Fire Weather Index System (CFFWIS), using three different fuel codes and three indices representing fire behaviour. Daily Fire Weather Index (FWI) calculation is done by the Meteorological Climatological and Geophysical Agency (BMKG) with data from its synoptic weather stations network. Distribution of such weather stations are sparse, therefore this paper reports on the development of Fire Weather Index calculator on Google Earth Engine, using high resolution weather data, provided by weather model and remote-sensing open datasets. The resulting application is capable of generating daily maps of FWI components to be used by the Indonesian Fire Danger Rating System.

2021 ◽  
Author(s):  
Andri Purwandani ◽  
Marina C. G. Frederik ◽  
Reni Sulistyowati ◽  
Lena Sumargana ◽  
Fanny Meliani ◽  
...  

2019 ◽  
Vol 3 (11) ◽  
pp. 25-40 ◽  
Author(s):  
Lourdes Villers-Ruiz ◽  
Emilio Chuvieco ◽  
Inmaculada Aguado

Entre los sistemas de alerta temprana de incendios forestales destaca el desarrollado por el Servicio Forestal de Canadá, denominado Fire Weather Index (FWI). Con el fin de contribuir a la creación de un sistema de alerta temprana, se utilizó este índice para determinar las condiciones de peligro a incendios en el Parque Nacional Malinche a partir de una serie de datos diarios de enero 2004 a octubre 2009 de cinco estaciones meteorológicas automáticas instaladas en el parque a una altitud de 3,000 m, se hicieron los cálculos de los elementos que contiene el índice; para ello, se empleó la versión automatizada del Canadian Forest Fire Danger Rating System. Se realizaron correlaciones y se crearon cuatro categorías con los valores de los componentes, según la frecuencia de incendios y el área siniestrada. También, se señalaron, los valores de temperatura máxima y mínima, humedad relativa y lluvia por categoría. Se constituyeron los umbrales mínimos de gran peligrosidad a incendios para cada uno de los elementos. En el caso del código de humedad de los combustibles finos, el umbral se estableció en 80 puntos; de superarse este valor, el número de incendios por día se incrementa sustancialmente. El código de sequía, el Índice de dispersión inicial del fuego; así como, el Índice acumulado fueron los más significativos en relación a la frecuencia de incendios, por lo que se calculó la probabilidad de estos eventos, para ciertos intervalos de los elementos considerados.


1998 ◽  
Vol 8 (4) ◽  
pp. 217 ◽  
Author(s):  
MD Flannigan ◽  
BM Wotton ◽  
S Ziga

In Canada, many fire management agencies interpolate indexes of the Fire Weather Index System to estimate the fire danger between weather stations. Difficulties with interpolation arise because summer precipitation can be highly variable over short distances. This variability hinders the usefulness of interpolating precipitation, which is one of the inputs for the Fire Weather Index System. Precipitation estimates from the Canadian Atmospheric Environment Service radar at Upsala, Ontario, were used to determine if this will enable a more accurate measure of the fire danger over the region. Three methods of interpolation of the fire danger between weather stations were compared: first, the standard practice of interpolating fire weather indexes from weather stations to any specified location; second, interpolating the weather variables, temperature, relative humidity, wind speed and precipitation from the weather station to any specified site and then calculating the fire weather indexes; third, interpolating weather variables as in Method 2 above except using the precipitation estimate from the radar and then calculating the fire weather indexes for any specified site. Overall, results indicate that the standard procedure of interpolating the fire weather indexes performs better than the other two methods. However, there are indexes where the other methods perform best (e.g., the fine fuel moisture code is best determined by using the radar precipitation estimation method). Fire management agencies should continue to use the standard practice of interpolating fire weather indexes to estimate fire danger between weather stations. Factors influencing the performance of the radar estimated precipitation method of estimating fire danger are discussed along with potential application of precipitation radar for fire management purposes.


2014 ◽  
Vol 23 (7) ◽  
pp. 945 ◽  
Author(s):  
Carlos C. DaCamara ◽  
Teresa J. Calado ◽  
Sofia L. Ermida ◽  
Isabel F. Trigo ◽  
Malik Amraoui ◽  
...  

Here we present a procedure that allows the operational generation of daily maps of fire danger over Mediterranean Europe. These are based on integrated use of vegetation cover maps, weather data and fire activity as detected by remote sensing from space. The study covers the period of July–August 2007 to 2009. It is demonstrated that statistical models based on two-parameter generalised Pareto (GP) distributions adequately fit the observed samples of fire duration and that these models are significantly improved when the Fire Weather Index (FWI), which rates fire danger, is integrated as a covariate of scale parameters of GP distributions. Probabilities of fire duration exceeding specified thresholds are then used to calibrate FWI leading to the definition of five classes of fire danger. Fire duration is estimated on the basis of 15-min data provided by Meteosat Second Generation (MSG) satellites and corresponds to the total number of hours in which fire activity is detected in a single MSG pixel during one day. Considering all observed fire events with duration above 1h, the relative number of events steeply increases with classes of increasing fire danger and no fire activity was recorded in the class of low danger. Defined classes of fire danger provide useful information for wildfire management and are based on the Fire Risk Mapping product that is being disseminated on a daily basis by the EUMETSAT Satellite Application Facility on Land Surface Analysis.


1999 ◽  
Vol 9 (4) ◽  
pp. 265 ◽  
Author(s):  
David L. Martell

A Markov chain is used to model day to day changes in the Fire Weather Index (FWI) component of the Canadian Forest Fire Weather Index System. The results of statistical analyses of 26 years (1963 through 1988) of fire weather data recorded at 15 fire weather stations located across the province of Ontario suggest that it is reasonable to partition the fire season into three subseasons and model day to day changes in the Fire Weather Index class within each subseason as a Markov chain of order 1.


2016 ◽  
Vol 16 (5) ◽  
pp. 1217-1237 ◽  
Author(s):  
Mark C. de Jong ◽  
Martin J. Wooster ◽  
Karl Kitchen ◽  
Cathy Manley ◽  
Rob Gazzard ◽  
...  

Abstract. Wildfires in the United Kingdom (UK) pose a threat to people, infrastructure and the natural environment. During periods of particularly fire-prone weather, wildfires can occur simultaneously across large areas, placing considerable stress upon the resources of fire and rescue services. Fire danger rating systems (FDRSs) attempt to anticipate periods of heightened fire risk, primarily for early-warning and preparedness purposes. The UK FDRS, termed the Met Office Fire Severity Index (MOFSI), is based on the Fire Weather Index (FWI) component of the Canadian Forest FWI System. The MOFSI currently provides daily operational mapping of landscape fire danger across England and Wales using a simple thresholding of the final FWI component of the Canadian FWI System. However, it is known that the system has scope for improvement. Here we explore a climatology of the six FWI System components across the UK (i.e. extending to Scotland and Northern Ireland), calculated from daily 2km × 2km gridded numerical weather prediction data and supplemented by long-term meteorological station observations. We used this climatology to develop a percentile-based calibration of the FWI System, optimised for UK conditions. We find this approach to be well justified, as the values of the "raw" uncalibrated FWI components corresponding to a very "extreme" (99th percentile) fire danger situation vary by more than an order of magnitude across the country. Therefore, a simple thresholding of the uncalibrated component values (as is currently applied in the MOFSI) may incur large errors of omission and commission with respect to the identification of periods of significantly elevated fire danger. We evaluate our approach to enhancing UK fire danger rating using records of wildfire occurrence and find that the Fine Fuel Moisture Code (FFMC), Initial Spread Index (ISI) and FWI components of the FWI System generally have the greatest predictive skill for landscape fire activity across Great Britain, with performance varying seasonally and by land cover type. At the height of the most recent severe wildfire period in the UK (2 May 2011), 50 % of all wildfires occurred in areas where the FWI component exceeded the 99th percentile. When all wildfire events during the 2010–2012 period are considered, the 75th, 90th and 99th percentiles of at least one FWI component were exceeded during 85, 61 and 18 % of all wildfires respectively. Overall, we demonstrate the significant advantages of using a percentile-based calibration approach for classifying UK fire danger, and believe that our findings provide useful insights for future development of the current operational MOFSI UK FDRS.


2011 ◽  
Vol 50 (8) ◽  
pp. 1617-1626 ◽  
Author(s):  
Paul Fox-Hughes

AbstractHalf-hourly airport weather observations have been used to construct high-temporal-resolution datasets of McArthur Mark V forest fire danger index (FFDI) values for three locations in Tasmania, Australia, enabling a more complete understanding of the range and diurnal variability of fire weather. Such an understanding is important for fire management and planning to account for the possibility of weather-related fire flare ups—in particular, early in a day and during rapidly changing situations. In addition, climate studies have hitherto generally been able to access only daily or at best 3-hourly weather data to generate fire-weather index values. Comparison of FFDI values calculated from frequent (subhourly) observations with those derived from 3-hourly synoptic observations suggests that large numbers of significant fire-weather events are missed, even by a synoptic observation schedule, and, in particular, by observations made at 1500 LT only, suggesting that many climate studies may underestimate the frequencies of occurrence of fire-weather events. At Hobart, in southeastern Tasmania, only one-half of diurnal FFDI peaks over a critical warning level occur at 1500 LT, with the remainder occurring across a broad range of times. The study reinforces a perception of pronounced differences in the character of fire weather across Tasmania, with differences in diurnal patterns of variability evident between locations, in addition to well-known differences in the ranges of peak values observed.


2002 ◽  
Vol 11 (4) ◽  
pp. 183 ◽  
Author(s):  
J. D. Carlson ◽  
Robert E. Burgan ◽  
David M. Engle ◽  
Justin R. Greenfield

This paper describes the Oklahoma Fire Danger Model, an operational fire danger rating system for the state of Oklahoma (USA) developed through joint efforts of Oklahoma State University, the University of Oklahoma, and the Fire Sciences Laboratory of the USDA Forest Service in Missoula, Montana. The model is an adaptation of the National Fire Danger Rating System (NFDRS) to Oklahoma, but more importantly, represents the first time anywhere that NFDRS has been implemented operationally using hourly weather data from a spatially dense automated weather station network (the Oklahoma Mesonet). Weekly AVHRR satellite imagery is also utilized for live fuel moisture and fuel load calculations. The result is a near-real-time mesoscale fire danger rating system to 1-km resolution whose output is readily available on the World Wide Web (http://agweather.mesonet.ou.edu/models/fire). Examples of output from 25 February 1998 are presented.The Oklahoma Fire Danger Model, in conjunction with other fire-related operational tools, has proven useful to the wildland fire management community in Oklahoma, for both wildfire anticipation and suppression and for prescribed fire activities. Instead of once-per-day NFDRS information at two to three sites, the fire manager now has statewide fire danger information available at 1-km resolution at up to hourly intervals, enabling a quicker response to changing fire weather conditions across the entire state.


2011 ◽  
Vol 20 (8) ◽  
pp. 963 ◽  
Author(s):  
Xiaorui Tian ◽  
Douglas J. McRae ◽  
Jizhong Jin ◽  
Lifu Shu ◽  
Fengjun Zhao ◽  
...  

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.


2021 ◽  
Author(s):  
Padraig Flattery ◽  
Klara Finkele ◽  
Paul Downes ◽  
Ferdia O'Leary ◽  
Ciaran Nugent

<p>Since 2006 the Canadian Forest Fire Weather Index System (FWI) has been used operationally at Met Éireann to predict the risk of forest fires in Ireland (Walsh, S, 2006). Although only around 11% or ca 770,000 ha of the total land area of Ireland is afforested, there are also large areas of open mountain and peatlands that are covered in grasses, dwarfshrub and larger woody shrub type vegetation which can provide ready fuel for spring wildfires, when suitable conditions arise. Following winter, much of this vegetation is either dead or has a very low live moisture content, and the flammability of this vegetation can be readily influenced by prevailing weather, most especially following prolonged dry periods. The Department of Agriculture, Food and Marine is the Forest Protection authority in Ireland and issues Fire Danger Notices as part of this work. These notices permit improved preparedness for fire responses and are based on information provided by Met Éireann on the current status of FWI and FWI components using observation data at synoptic stations and the predicted FWI for the next five days ahead based on numerical weather prediction input data.</p><p>The FWI is based on</p><ul><li>three different types of forest fuel, ie how quickly these dry out/get rewetted. These are the Fine Fuels Moisture Code (FFMC), the Duff Moisture Code (DMC) and the Drought Code (DC).</li> <li>components based on fire behaviour: the Initial Spread Index (ISI), the Build-up Index (BUI), and the Fire Weather Index (FWI) which represents fire intensity as energy output rate per unit length of fire front. It is then used to determine the Daily Severity Rating (DSR) of the fire danger. </li> </ul><p>Of these components, the FFMC and ISI components have been found to provide the most accurate indication of risk under Irish conditions, based on the fuels involved and ignition patterns observed to date.</p><p>The DSR was based on a climatology of 1971 to 2005 at the time of operational implantation of the FWI at Met Éireann. An updated climatology based on the new reference period of 1990 to 2020 will be shown as well as the change of the 98 percentiles of extreme rating using this new reference period.  </p><p><strong>Walsh, S.</strong> “Implementation in Ireland of the Canadian Forest Fire Weather Index System.” In <em>Making Science Work on the Farm. A Workshop on Decision Support Systems for Irish Agriculture</em>, 120–126. Dublin: AGMET, 2007. </p>


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