scholarly journals Characterization of wildfire regimes in Canadian boreal terrestrial ecosystems

2009 ◽  
Vol 18 (8) ◽  
pp. 992 ◽  
Author(s):  
Yueyang Jiang ◽  
Qianlai Zhuang ◽  
Mike D. Flannigan ◽  
John M. Little
Keyword(s):  
Power Law ◽  
Terrestrial Ecosystems ◽  
Fire Regimes ◽  
Carbon Dynamics ◽  
Burned Area ◽  
Burned Areas ◽  
Fire Recurrence ◽  
Natural Fires ◽  
Recurrence Intervals ◽  
Frequency Area

Wildfire is a major disturbance in boreal terrestrial ecosystems. Characterizing fire regimes and projecting fire recurrence intervals for different biomes are important in managing those ecosystems and quantifying carbon dynamics of those ecosystems. This study used Canadian wildfire datasets, 1980–1999, to characterize relationships between number of fires and burned area for 13 ecozones and to calculate wildfire recurrence intervals in each ecozone. For the study period, wildfires were found to follow power–law relationships between frequency densities (number of fires normalized to unit bins) and burned areas in all ecozones. Power–law frequency–area relationships also held for both anthropogenic fires and natural fires in the 1980s and 1990s. For each Canadian ecozone using the parameters of the power–law frequency–area distributions, fire recurrence intervals were then calculated for wildfires equal to or larger than a given size of burned area. Fire recurrence intervals ranged from 1 to 32 years for burned areas >2 km2, and from 1 to 100 years for burned areas >10 km2 in every 10 000-km2 spatial area for each ecozone. The information obtained through characterizing the wildfires and the fire recurrence intervals calculated in this study will provide guidance to wildfire risk managers throughout Canada. The findings of this study will also be a benefit to future efforts in quantifying carbon dynamics in Canadian boreal terrestrial ecosystems.

Fire regime from 1973 to 2011 in north-western Patagonian grasslands

2016 ◽  
Vol 25 (9) ◽  
pp. 922 ◽  
Author(s):  
Facundo José Oddi ◽  
Luciana Ghermandi
Keyword(s):  
Fire Regime ◽  
Terrestrial Ecosystems ◽  
Fire Regimes ◽  
Burned Area ◽  
General Knowledge ◽  
Fire Size ◽  
Socioeconomic Impacts ◽  
Mean Size ◽  
Fire Size Distribution ◽  
North Western

Fire is one of the most important disturbances in terrestrial ecosystems and has major ecological and socioeconomic impacts. Fire regime describes the variation of individual fire events in time and space. Few studies have characterised the fire regime in grasslands in spite of the importance of these ecosystems. The aim of this study was to describe the recent fire regime (from 1973 to 2011) of north-western Patagonian grasslands in terms of seasonality, frequency and burned area. Our study area covered 560 000 ha and we used a remote sensing approach combined with statistics obtained from operational databases. Fires occur during the summer in 2 of every 3 years with a frequency of 2.7 fires per year and a mean size of 823 ha. Fire size distribution is characterised by many small fires and few large ones which would respond to a distribution from the power law family. Eighty per cent of the total area affected by fire was burned in the span of a few years, which were also widespread fire years in forests and woodlands of north-western Patagonia. This work contributes to general knowledge about fire regimes in grasslands and we expect that our results will serve as a reference to further fire regime research.

scholarly journals Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning

2021 ◽  
Vol 13 (11) ◽  
pp. 5353-5368
Author(s):  
David L. A. Gaveau ◽  
Adrià Descals ◽  
Mohammad A. Salim ◽  
Douglas Sheil ◽  
Sean Sloan
Keyword(s):  
Carbon Emission ◽  
Burned Area ◽  
International Crisis ◽  
Burned Areas ◽  
Area Distribution ◽  
Area Estimate ◽  
Frequency Area ◽  
Sentinel 2 ◽  
Official Estimate ◽  
Good Detection

Abstract. Many nations are challenged by landscape fires. A confident knowledge of the area and distribution of burning is crucial to monitor these fires and to assess how they might best be reduced. Given the differences that arise using different detection approaches, and the uncertainties surrounding burned-area estimates, their relative merits require evaluation. Here we propose, illustrate, and examine one promising approach for Indonesia where recurring forest and peatland fires have become an international crisis. Drawing on Sentinel-2 satellite time-series analysis, we present and validate new 2019 burned-area estimates for Indonesia. The corresponding burned-area map is available at https://doi.org/10.5281/zenodo.4551243 (Gaveau et al., 2021a). We show that >3.11 million hectares (Mha) burned in 2019. This burned-area extent is double the Landsat-derived official estimate of 1.64 Mha from the Indonesian Ministry of Environment and Forestry and 50 % more that the MODIS MCD64A1 burned-area estimate of 2.03 Mha. Though we observed proportionally less peatland burning (31 % vs. 39 % and 40 % for the official and MCD64A1 products, respectively), in absolute terms we still observed a greater area of peatland affected (0.96 Mha) than the official estimate (0.64 Mha). This new burned-area dataset has greater reliability than these alternatives, attaining a user accuracy of 97.9 % (CI: 97.1 %–98.8 %) compared to 95.1 % (CI: 93.5 %–96.7 %) and 76 % (CI: 73.3 %–78.7 %), respectively. It omits fewer burned areas, particularly smaller- (<100 ha) to intermediate-sized (100–1000 ha) burns, attaining a producer accuracy of 75.6 % (CI: 68.3 %–83.0 %) compared to 49.5 % (CI: 42.5 %–56.6 %) and 53.1 % (CI: 45.8 %–60.5 %), respectively. The frequency–area distribution of the Sentinel-2 burn scars follows the apparent fractal-like power law or Pareto pattern often reported in other fire studies, suggesting good detection over several magnitudes of scale. Our relatively accurate estimates have important implications for carbon-emission calculations from forest and peatland fires in Indonesia.

scholarly journals A Fire Hazard Assessment Using Sentinel Imagery; A Case Study Over Gippsland Australia

2020 ◽  
Vol 5 (7) ◽  
pp. 377-381
Author(s):  
Sanjeev Kumar Raut ◽  
David Nhemaphuki ◽  
Rebanta Aryal ◽  
Prakash Lakandri
Keyword(s):  
Fire Hazard ◽  
Fire Regimes ◽  
Burned Area ◽  
United States Geological Survey ◽  
Area Index ◽  
Burned Areas ◽  
Before And After ◽  
History Of ◽  
Sentinel 2

Accurate and the efficient rapid mapping of the fire-damaged areas are the most fundamental things for any places to retain from environmental loss. To support the fire management, make definite strategy and planning, and restore the vegetation, it is important to detect the area before and after the fire damages. Under climate change conditions, heat and drought may trigger tough fire regimes in terms of number and dimension of fires. To deliver the rapid information of the area damaged by the fires, Burned Area Index (BAI), Normalized Burned Ratio (NBR) and their versions are applied to map burned areas from high-resolution optical satellite data. The new MSI sensor aboard Sentinel-2 satellites records the more spectral information in the red edge spectral region making it more convenient to the development of new indices for the burned area mapping. Recently, Australia had confronted a devastating bushfire recorded in the history of the nation. In this project, NBR deployed to detect burned areas at around 10m-20m spatial resolution based on pre and post-fire Sentinel-2 images. A dNBR (differentiated Normalized Burned Ratio) was calculated while burn severity was mapped as purposed by United States Geological Survey (USGS). It observed that more than half of the East Gippsland region i.e. about 53% of the area affected by the wildfire while 38% remained unburned and 8.4% showed the regrowth.

scholarly journals Analysis of fire dynamics in the Brazilian savannas

2017 ◽  
Author(s):  
Guilherme Augusto Verola Mataveli ◽  
Maria Elisa Siqueira Silva ◽  
Gabriel Pereira ◽  
Francielle da Silva Cardozo ◽  
Fernando Shinji Kawakubo ◽  
...  
Keyword(s):  
Land Use ◽  
Condition Index ◽  
Burned Area ◽  
Spatial Correlations ◽  
Fire Dynamics ◽  
Burned Areas ◽  
Natural Fires ◽  
Active Fire ◽  
Vegetation Condition ◽  
Vegetation Condition Index

Abstract. Wildfires play a key role in the ecology of savannas. The Brazilian savannas (Cerrado biome), where the extension of burned areas and amount of fires can be more numerous than in the Amazon, is frequently burned due to natural fires or land-use and land-cover (LULC) changes. Thus, we aimed to understand the occurrence and the dynamics of fires in the Cerrado using active fire, burned area, precipitation, vegetation condition, estimated using the Vegetation Condition Index (VCI), and LULC data derived from orbital sensors. Results show that the Cerrado was, respectively, the second and first Brazilian biome for the occurrence of hotspots and burned area, which are concentrated during the dry season (May to September), especially in September, when the annual deficit in precipitation and extreme vegetation conditions reached maximum indices. Higher densities of hotspots concentrated in the Northern of the biome, while 75 % of the occurrences were found in the natural remnants of the Cerrado. Totals of hotspots and burned area were higher in years of lower precipitation, such as 2007 and 2010. Spatial correlations showed that hotspots and burned area are better correlated with precipitation than vegetation condition, especially in the Central North and Northeast of the Cerrado.

scholarly journals Effects of climate variability on savannah fire regimes in West Africa

2015 ◽  
Vol 6 (1) ◽  
pp. 161-174 ◽  
Author(s):  
E. T. N'Datchoh ◽  
A. Konaré ◽  
A. Diedhiou ◽  
A. Diawara ◽  
E. Quansah ◽  
...  
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Southern Oscillation ◽  
Regional Scale ◽  
Fire Regimes ◽  
Burned Area ◽  
Climate Conditions ◽  
Burned Areas ◽  
Seasonal Analysis ◽  
Biomass Availability

Abstract. The main objective of this work is to investigate at regional scale the variability in burned areas over the savannahs of West Africa and their links with the rainfall and the large-scale climatic indexes such as the Southern Oscillation Index (SOI), Multivariate ENSO Index (MEI), North Atlantic Oscillation (NAO) and sea surface temperature gradient (SSTG). Daily satellite products (L3JRC) of burned areas from the SPOT Vegetation sensor at a moderate spatial resolution of 1 km x 1 km between 2000 and 2007 were analyzed over the West African savannah in this paper. Results from seasonal analysis revealed a large increase in burned areas from November to February, with consistent peaks in December at the regional scale. In addition, about 30% of the pixels are burned at least four times within the 7-year period. Positive correlations were found between burned areas and rainfall values obtained from the TRMM satellite over savannahs located above 8° N, meaning that a wet rainfall season over these regions was favorable to biomass availability in the next dry season and therefore may induce an increase in burned areas in this region. Moreover, our results showed a nonlinear relationship between the large-scale climatic indexes SOI, MEI, NAO and SSTG and burned-area anomalies. Positive (negative) correlations between burned areas and SOI (MEI) were consistent over the Sahel and Sudano-Sahelian areas. Negative correlations with Atlantic SSTG were significant over the Guinea subregion. Correlations between burned areas over Sudano-Guinean subregion and all the large-scale indexes were weak and may be explained by the fact that this subregion had a mean rainfall greater than 800 mm yr−1 with permanent biomass availability and an optimal amount of soil moisture favorable to fire practice irrespective of the climate conditions. The teleconnection with NAO was not clear and needed to be investigated further.

scholarly journals High-severity wildfires in temperate Australian forests have increased in extent and aggregation in recent decades

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242484
Author(s):  
Bang Nguyen Tran ◽  
Mihai A. Tanase ◽  
Lauren T. Bennett ◽  
Cristina Aponte
Keyword(s):  
Fire Regime ◽  
Fire Severity ◽  
Fire Regimes ◽  
Ecosystem Dynamics ◽  
Burned Area ◽  
Burned Areas ◽  
South Eastern ◽  
High Severity ◽  
Eastern Australia ◽  
South Eastern Australia

Wildfires have increased in size and frequency in recent decades in many biomes, but have they also become more severe? This question remains under-examined despite fire severity being a critical aspect of fire regimes that indicates fire impacts on ecosystem attributes and associated post-fire recovery. We conducted a retrospective analysis of wildfires larger than 1000 ha in south-eastern Australia to examine the extent and spatial pattern of high-severity burned areas between 1987 and 2017. High-severity maps were generated from Landsat remote sensing imagery. Total and proportional high-severity burned area increased through time. The number of high-severity patches per year remained unchanged but variability in patch size increased, and patches became more aggregated and more irregular in shape. Our results confirm that wildfires in southern Australia have become more severe. This shift in fire regime may have critical consequences for ecosystem dynamics, as fire-adapted temperate forests are more likely to be burned at high severities relative to historical ranges, a trend that seems set to continue under projections of a hotter, drier climate in south-eastern Australia.

Intensifying fire regimes in the arctic-boreal zone: recent changes, global implications, and possible solutions

2021 ◽  
Author(s):  
Brendan Rogers ◽  
Molly Elder ◽  
Peter Frumhoff ◽  
Thomas Gasser ◽  
Elena Kukavskaya ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
High Latitude ◽  
Boreal Forests ◽  
Global Climate ◽  
Fire Regimes ◽  
The Arctic ◽  
Burned Area ◽  
Climate Mitigation ◽  
Global Carbon ◽  
Frequency Area

&lt;p&gt;Across much of the high latitudes, wildfires have been increasing in frequency, area burned, and severity in response to longer fire seasons, more severe fire weather, and increased ignitions. These fires not only affect the tundra and boreal forests they burn, but also global climate due to the high levels of carbon emitted during combustion that take decades to re-aggrade. Carbon emissions from high latitude fires are generally not included in global models that inform policy nor emissions reductions commitments from relevant countries. In this presentation we describe recent progress and critical unknowns related to intensifying fire regimes in high latitude ecosystems, with a particular focus on (i) trends in burned area and large fire years; (ii) changing ignitions sources including lightning, human, and overwintering fires; (iii) patterns and drivers of carbon emissions, including interactions with permafrost; (iv) implications for global carbon budgets; and (v) potential climate mitigation through increased resources for carbon-focused fire management.&lt;/p&gt;

scholarly journals Power law distributions of wildfires across Europe: benchmarking a land surface model with observed data

2015 ◽  
Vol 2 (6) ◽  
pp. 1553-1586
Author(s):  
B. Di Mauro ◽  
F. Fava ◽  
P. Frattini ◽  
A. Camia ◽  
R. Colombo ◽  
...  
Keyword(s):  
Power Law ◽  
Land Surface ◽  
Land Surface Model ◽  
Burned Area ◽  
Surface Model ◽  
Scaling Exponent ◽  
Data Set ◽  
Size Frequency Distribution ◽  
Burned Areas ◽  
Community Land Model

Abstract. Monthly wildfire burned area frequency is here modeled with a power law distribution and scaling exponent across different European biomes are estimated. Data sets, spanning from 2000 to 2009, comprehend the inventory of monthly burned areas from the European Forest Fire Information System (EFFIS) and simulated monthly burned areas from a recent parameterization of a Land Surface Model (LSM), that is the Community Land Model (CLM). Power law exponents are estimated with a Maximum Likelihood Estimation (MLE) for different European biomes. The characteristic fire size (CFS), i.e. the area that most contributes to the total burned area, was also calculated both from EFFIS and CLM data set. We used the power law fitting and the CFS analysis to benchmark CLM model against the EFFIS observational wildfires data set available for Europe. Results for the EFFIS data showed that power law fittings holds for 2–3 orders of magnitude in the Boreal and Continental ecoregions, whereas the distribution of the Alpine, Atlantic are fitted only in the upper tail. Power law instead is not a suitable model for fitting CLM simulations. CLM benchmarking analysis showed that the model strongly overestimates burned areas and fails in reproducing size-frequency distribution of observed EFFIS wildfires. This benchmarking analysis showed that some refinements in CLM structure (in particular regarding the anthropogenic influence) are needed for predicting future wildfires scenarios, since the low spatial resolution of the model and differences in relative frequency of small and large fires can affect the reliability of the predictions.

scholarly journals Assessing Wildfire Regimes in Indigenous Lands of the Brazilian Savannah-Like Cerrado

Fire ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 34
Author(s):  
Pedro Melo ◽  
Javier Sparacino ◽  
Daihana Argibay ◽  
Vicente Sousa Júnior ◽  
Roseli Barros ◽  
...  
Keyword(s):  
Forest Fires ◽  
Fire Regime ◽  
Management Strategies ◽  
Fire Regimes ◽  
Google Earth ◽  
Dry Season ◽  
Burned Area ◽  
Burned Areas ◽  
Brazilian Savannah ◽  
Indigenous Lands

The Brazilian savannah-like Cerrado is classified as a fire-dependent biome. Human activities have altered the fire regimes in the region, and as a result, not all fires have ecological benefits. The indigenous lands (ILs) of the Brazilian Cerrado have registered the recurrence of forest fires. Thus, the diagnosis of these events is fundamental to understanding the burning regimes and their consequences. The main objective of this paper is to evaluate the fire regimes in Cerrado’s indigenous lands from 2008 to 2017. We used the Landsat time series, at 30 m spatial resolution, available in the Google Earth Engine platform to delineate the burned areas. We used precipitation data from a meteorological station to define the rainy season (RS), early dry season (EDS), middle dry season (MDS), and late dry season (LDS) periods. During 2008–2017, our results show that the total burned area in the indigenous lands and surrounding area was 2,289,562 hectares, distributed in 14,653 scars. Most fires took place between June and November, and the annual burned area was quite different in the years studied. It was also possible to identify areas with high fire recurrence. The fire regime patterns described here are the first step towards understanding the fire regimes in the region and establishing directions to improve management strategies and guide public policies.

scholarly journals Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep Learning

2021 ◽  
Vol 13 (8) ◽  
pp. 1509
Author(s):  
Xikun Hu ◽  
Yifang Ban ◽  
Andrea Nascetti
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Multiple Scales ◽  
Detection Methods ◽  
Burned Area ◽  
Landsat 8 ◽  
Multispectral Imagery ◽  
Burned Areas ◽  
Local Climate Zones ◽  
Sentinel 2

Accurate burned area information is needed to assess the impacts of wildfires on people, communities, and natural ecosystems. Various burned area detection methods have been developed using satellite remote sensing measurements with wide coverage and frequent revisits. Our study aims to expound on the capability of deep learning (DL) models for automatically mapping burned areas from uni-temporal multispectral imagery. Specifically, several semantic segmentation network architectures, i.e., U-Net, HRNet, Fast-SCNN, and DeepLabv3+, and machine learning (ML) algorithms were applied to Sentinel-2 imagery and Landsat-8 imagery in three wildfire sites in two different local climate zones. The validation results show that the DL algorithms outperform the ML methods in two of the three cases with the compact burned scars, while ML methods seem to be more suitable for mapping dispersed burn in boreal forests. Using Sentinel-2 images, U-Net and HRNet exhibit comparatively identical performance with higher kappa (around 0.9) in one heterogeneous Mediterranean fire site in Greece; Fast-SCNN performs better than others with kappa over 0.79 in one compact boreal forest fire with various burn severity in Sweden. Furthermore, directly transferring the trained models to corresponding Landsat-8 data, HRNet dominates in the three test sites among DL models and can preserve the high accuracy. The results demonstrated that DL models can make full use of contextual information and capture spatial details in multiple scales from fire-sensitive spectral bands to map burned areas. Using only a post-fire image, the DL methods not only provide automatic, accurate, and bias-free large-scale mapping option with cross-sensor applicability, but also have potential to be used for onboard processing in the next Earth observation satellites.

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