Burned Area Products Research Articles

Global burned area mapping from ENVISAT-MERIS and MODIS active fire data

We present the development of a global burned area (BA) algorithm based on MERIS imagery along with the assessment of the global BA results for three years (2006–2008). This work was developed within the Fire Disturbance project under the European Space Agency Climate Change Initiative programme, which aimed to generate long-term BA information for climate models. Our algorithm combined temporal series of MERIS reflectances with thermal information from MODIS HS (hotspot) product. The algorithm included two-steps. Firstly, cumulative distribution functions were computed to discriminate the most clearly burned pixels using regionally-oriented near infrared reflectance thresholds. Secondly, a contextual criterion improved the spatial detection of the burned patches from the seed pixels. BA estimates for the three target years range from 3.6 to 3.8million km2. Results were validated from a statistically designed sample of fire perimeters generated from Landsat multi-temporal imagery. Intercomparison with existing BA products was also carried out. Results from global validation datasets provided an average overall accuracy higher than 0.95. The accuracy of the BA category was lower than the accuracy of the unburned one. Within the former, average omission and commission errors were lower for areas where the proportion of burned area was higher (for pixel-based error matrices, commission error (CE) was 0.52 and omission error (OE) was 0.51), than for those areas with very low BA proportion (CE=0.60 and OE=0.74). In terms of total BA estimation, errors were generally well balanced, with a tendency towards underestimation (34%). Relevant impact of temporal reporting accuracy was found for these validation datasets. Intercomparison with other existing BA datasets pointed out similar spatial and temporal trends, with high correlation with GFED v4 BA estimations for the three years (r2>0.974).

Mediterranean cities under fire. A critical approach to the wildland–urban interface

Wildfires are widely reviewed as key inputs to Mediterranean ecosystems. However, research is often flawed by major biases. (1) The approach adopted by most planners focusing on forest fires dismisses the human dimension of fire as a component of agricultural production systems. (2) The Wildland–Urban Interface (WUI) concept postulates that cities and wildlands/wildfires are, and should remain, worlds apart, a statement whose truth is increasingly questioned by recent disastrous “urban wildfires”. (3) The Mediterranean Basin as a fire-prone area is all the more fantasized, as it is almost never studied as a whole.The present paper takes a critical view of city–wildland/wildfire interrelationships through a large-scale study of the Mediterranean Basin based on MODIS MCD12Q1 (Land Cover Type) and MCD45A1 (Burned Area Product) data collected between 2001 and 2013. The Mediterranean is an ideal place to investigate, as its human-dominated and urbanized landscapes are known to be extremely vulnerable to fire hazards. Data processing reveals that (wild)fires and cities maintain indissoluble ties, as if both elements could not be considered mutually exclusive on a geographical basis. Urban sprawl, reduced rural autonomies, changes in forest covers, old agricultural practices, and military conflicts provide the framework for an extended mitigation process challenging the WUI concept as a space divider.

Detection of burned areas from mega-fires using daily and historical MODIS surface reflectance

The detection and mapping of burned areas from wildland fires is one of the most important approaches for evaluating the impacts of fire events. In this study, a novel burned area detection algorithm for rapid response applications using Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m surface reflectance data was developed. Spectra from bands 5 and 6, the composite indices of the Normalized Burn Ratio, and the Normalized Difference Vegetation Index were employed as indicators to discover burned pixels. Historical statistical data were used to provide pre-fire baseline information. Differences in the current (post-fire) and historical (pre-fire) data were input into a support vector machine classifier, and the fire-affected pixels were detected and mapped by the support vector machine classification process. Compared with the existing MODIS level 3 monthly burned area product MCD45, the new algorithm is able to generate burned area maps on a daily basis when new data become available, which is more applicable to rapid response scenarios when major fire incidents occur. The algorithm was tested in three mega-fire cases that occurred in the continental USA. The experimental results were validated against the fire perimeter database generated by the Geospatial Multi-Agency Coordination Group and were compared with the MCD45 product. The validation results indicated that the algorithm was effective in detecting burned areas caused by mega-fires.

Sensitivity of global terrestrial carbon cycle dynamics to variability in satellite‐observed burned area

AbstractFire plays an important role in terrestrial ecosystems by regulating biogeochemistry, biogeography, and energy budgets, yet despite the importance of fire as an integral ecosystem process, significant advances remain to improve its prognostic representation in carbon cycle models. To recommend and to help prioritize model improvements, this study investigates the sensitivity of a coupled global biogeography and biogeochemistry model, LPJ, to observed burned area measured by three independent satellite‐derived products, GFED v3.1, L3JRC, and GlobCarbon. Model variables are compared with benchmarks that include pantropical aboveground biomass, global tree cover, and CO2 and CO trace gas concentrations. Depending on prescribed burned area product, global aboveground carbon stocks varied by 300 Pg C, and woody cover ranged from 50 to 73 Mkm2. Tree cover and biomass were both reduced linearly with increasing burned area, i.e., at regional scales, a 10% reduction in tree cover per 1000 km2, and 0.04‐to‐0.40 Mg C reduction per 1000 km2. In boreal regions, satellite burned area improved simulated tree cover and biomass distributions, but in savanna regions, model‐data correlations decreased. Global net biome production was relatively insensitive to burned area, and the long‐term land carbon sink was robust, ~2.5 Pg C yr−1, suggesting that feedbacks from ecosystem respiration compensated for reductions in fuel consumption via fire. CO2 transport provided further evidence that heterotrophic respiration compensated any emission reductions in the absence of fire, with minor differences in modeled CO2 fluxes among burned area products. CO was a more sensitive indicator for evaluating fire emissions, with MODIS‐GFED burned area producing CO concentrations largely in agreement with independent observations in high latitudes. This study illustrates how ensembles of burned area data sets can be used to diagnose model structures and parameters for further improvement and also highlights the importance in considering uncertainties and variability in observed burned area data products for model applications.

Global analysis of radiative forcing from fire-induced shortwave albedo change

Abstract. Land surface albedo, a key parameter to derive Earth's surface energy balance, is used in the parameterization of numerical weather prediction, climate monitoring and climate change impact assessments. Changes in albedo due to fire have not been fully investigated on a continental and global scale. The main goal of this study, therefore, is to quantify the changes in instantaneous shortwave albedo produced by biomass burning activities and their associated radiative forcing. The study relies on the MODerate-resolution Imaging Spectroradiometer (MODIS) MCD64A1 burned-area product to create an annual composite of areas affected by fire and the MCD43C2 bidirectional reflectance distribution function (BRDF) albedo snow-free product to compute a bihemispherical reflectance time series. The approximate day of burning is used to calculate the instantaneous change in shortwave albedo. Using the corresponding National Centers for Environmental Prediction (NCEP) monthly mean downward solar radiation flux at the surface, the global radiative forcing associated with fire was computed. The analysis reveals a mean decrease in shortwave albedo of −0.014 (1σ = 0.017), causing a mean positive radiative forcing of 3.99 Wm−2 (1σ = 4.89) over the 2002–20012 time period in areas affected by fire. The greatest drop in mean shortwave albedo change occurs in 2002, which corresponds to the highest total area burned (378 Mha) observed in the same year and produces the highest mean radiative forcing (4.5 Wm−2). Africa is the main contributor in terms of burned area, but forests globally give the highest radiative forcing per unit area and thus give detectable changes in shortwave albedo. The global mean radiative forcing for the whole period studied (~0.0275 Wm−2) shows that the contribution of fires to the Earth system is not insignificant.

Comparing the accuracies of remote sensing global burned area products using stratified random sampling and estimation

The accuracies of six global burned area (BA) products for year 2008 were compared using the same validation methods and reference data to quantify accuracy of each product. The selected products include MCD64, MCD45 and Geoland2, and three products developed within the Fire Disturbance project (fire_cci), which is part of the European Space Agency's (ESA) Climate Change Initiative (CCI) program. The latter three products were derived from MERIS and VEGETATION sensors (one product from each sensor separately, and a third one from the merging of MERIS and VGT products). The reference fire perimeters were mapped from two multi-temporal Landsat TM/ETM+ images at 103 non-overlapping Thiessen scene areas (TSA) selected with a stratified random sampling design. The validation results were based on cross tabulated error matrices from which six accuracy measures were computed following the requirements of end-users of burned area products. While overall accuracy (OA) exceeded 99% for all products, overall accuracy was lower for the burned class. Burned area commission error ratio was above 40% for all products and omission error ratio was above 65% for all products. The statistical significance of differences in accuracy between pairs of products was evaluated based on theory of the stratified combined ratio estimator. Statistical tests identified the MCD64 as the most accurate product, followed by MCD45 and the MERIS product.

Anthropogenic effects on global mean fire size

Wildland fires are an important agent in the earth’s system. Multiple efforts are currently in progress to better represent wildland fires in earth system models. Although wildland fires are a natural disturbance factor, humans have an important effect on fire occurrence by directly igniting and suppressing fires and indirectly influencing fire behaviour by changing land cover and landscape structure. Although these factors are recognised, their quantitative effect on fire growth and burned area are not well understood and therefore only partly taken into account in current process-based fire models. Here we analyse the influence of humans on mean fire size globally. The mean fire size was extracted from the global Moderate Resolution Imaging Spectroradiometer (MODIS) burned area product MCD45. We found a linear decreasing trend between population density and observed mean fire size over the globe, as well as a negative effect of cropland cover and net income. We implemented the effect of population density on fire growth in a global vegetation model including a process-based fire model (SPITFIRE–JSBACH). When including this demographic control, spatial trends in modelled fraction of burned area generally improved when compared with satellite-derived burned area data. More process-based solutions to limit fire spread are needed in the future, but the empirical relations described here serve as an intermediate step to improve current fire models.

Compositing MODIS time series for reconstructing burned areas in the taiga–steppe transition zone of northern Mongolia

Wildfire is the main natural disturbance in forest ecosystems; it controls and modifies vegetation compositions, landscape properties and global carbon cycle. Estimates of areas burned by wildfires vary greatly depending on the environmental conditions, data availability and methods used. This paper aims to develop a framework for reconstructing time series of burned areas in the taiga–steppe transition zone using MODIS composites. The estimated accuracy of the developed mapping algorithm and other statistical indications denote that the clear land surface composites of MODIS data in spring (Julian dates, JD 97–177), logistic regression and MODIS active fire product can be integrated successfully for reconstructing burned areas in the taiga–steppe transition zone. Time series of burned areas between 2000 and 2012 derived from the MODIS spring composite algorithm were validated using Landsat-based burned areas, showing average omission and commission errors of 18% and 31%. Compared with the MCD45A1 burned area product, the developed algorithm significantly improved the prediction of burned areas and successfully separated late-season from early-season burns. The derived long-term burned areas will assist in understanding the complex relationships among forest dynamics, forest recovery and fire in the vulnerable boreal forest ecosystem as well as its transition zone under climate change in northern Mongolia and Central Asia.

Satellite-based automated burned area detection: A performance assessment of the MODIS MCD45A1 in the Brazilian savanna

Burnings, which cause major changes to the environment, can be effectively monitored via satellite data, regarding both the identification of active fires and the estimation of burned areas. Among the many orbital sensors suitable for mapping burned areas on global and regional scales, the moderate resolution imaging spectroradiometer (MODIS), on board the Terra and Aqua platforms, has been the most widely utilized. In this study, the performance of the MODIS MCD45A1 burned area product was thoroughly evaluated in the Brazilian savanna, the second largest biome in South America and a global biodiversity hotspot, characterized by a conspicuous climatic seasonality and the systematic occurrence of natural and anthropogenic fires. Overall, September MCD45A1 polygons (2000–2012) compared well to the Landsat-based reference mapping (r2=0.92) and were closely accompanied, on a monthly basis, by MOD14 and MYD14 hotspots (r2=0.89), although large omissions errors, linked to landscape patterns, structures, and overall conditions depicted in each reference image, were observed. In spite of its spatial and temporal limitations, the MCD45A1 product proved instrumental for mapping and understanding fire behavior and impacts on the Cerrado landscapes.

Desarrollo de una metodología para la detección de cambios de la cubierta vegetal en series temporales de imágenes de satélite diarias. Aplicación a la detección de áreas quemadas

We have developed a methodology for detection of observable phenomena at pixel level over time series of daily satellite images, based on using a Bayesian classifier. This methodology has been applied successfully to detect burned areas in the North American boreal forests using the LTDR dataset. The LTDR dataset represents the longest time series of global daily satellite images with 0.05° (~5 km) of spatial resolution. The proposed methodology has several stages: 1) pre-processing daily images to obtain composite images of n days; 2) building of space of statistical variables or attributes to consider; 3) designing an algorithm, by selecting and filtering the training cases; 4) obtaining probability maps related to the considered thematic classes; 5) post-processing to improve the results obtained by applying multiple techniques (filters, ranges, spatial coherence, etc.). The generated results are analyzed using accuracy metrics derived from the error matrix (commission and omission errors, percentage of estimation) and using scattering plots against reference data (correlation coefficient and slope of the regression line). The quality of the results obtained improves, in terms of spatial and timing accuracy, to other burned area products that use images of higher spatial resolution (500 m and 1 km), but they are only available after year 2000 as MCD45A1 and BA GEOLAND-2: the total burned area estimation for the study region for the years 2001-2011 was 28.56 millions of ha according to reference data and 12.41, 138.43 and 19.41 millions of ha for the MCD45A1, BA GEOLAND-2 and BA-LTDR burned area products, respectively.

Comparison of forest burned areas in mainland China derived from MCD45A1 and data recorded in yearbooks from 2001 to 2011

Forest burning, which emits large amounts of trace gases and particulate matter into the atmosphere, produces great impacts on air quality and climate change. In this study, the MODIS (Moderate-Resolution Imaging Spectroradiometer) burned area product (MCD45A1) and GlobCover land-cover product were integrated to estimate the forest burned areas in mainland China from 2001 to 2011. The results were compared with the official data from China Forestry Yearbooks and China Forestry Statistical Yearbooks. On the national scale, the MCD45A1 data were comparable with the official data. However, great gaps exist between the MCD45A1-derived provincial and regional forest burned areas and the corresponding values from the Forestry Statistical Yearbooks. In particular, the MCD45A1-derived areas were higher than the Forestry Statistical Yearbooks in north-east China and significantly lower in south-west China. Moreover, it was indicated that the MCD45A1 algorithm was unsuitable for retrieving the burned areas of small forest fires. Nevertheless, the MCD45A1 exhibited excellent performance in retrieving seasonal patterns of forest fire, with high fire occurrence in spring and autumn. On balance, more studies are required to assess and improve the MCD45A1 product and more precise data on forest burned areas in China are urgently needed.

An accuracy assessment of the MTBS burned area product for shrub–steppe fires in the northern Great Basin, United States

Although fire is a common disturbance in shrub–steppe, few studies have specifically tested burned area mapping accuracy in these semiarid to arid environments. We conducted a preliminary assessment of the accuracy of the Monitoring Trends in Burn Severity (MTBS) burned area product on four shrub–steppe fires that exhibited varying degrees of within-fire patch heterogeneity. Independent burned area perimeters were derived through visual interpretation and were used to cross-compare the MTBS burned area perimeters with classifications produced using set thresholds on the Relativised differenced Normalised Burn Index (RdNBR), Mid-infrared Burn Index (MIRBI) and Char Soil Index (CSI). Overall, CSI provided the most consistent accuracies (96.3–98.6%), with only small commission errors (1.5–4.4%). MIRBI also had relatively high accuracies (92.2–97.9%) and small commission errors (2.1–10.8%). The MTBS burned area product had higher commission errors (4.3–15.5%), primarily due to inclusion of unburned islands and fingers within the fire perimeter. The RdNBR burned area maps exhibited lower accuracies (92.9–96.0%). However, the different indices when constrained by the MTBS perimeter provided variable results, with CSI providing the highest and least variable accuracies (97.4–99.1%). Studies seeking to use MTBS perimeters to analyse trends in burned area should apply spectral indices to constrain the final burned area maps. The present paper replaces a former paper of the same title (http://dx.doi.org/10.1071/WF13206), which was withdrawn owing to errors discovered in data analysis after the paper was accepted for publication.

A Decade Long, Multi-Scale Map Comparison of Fire Regime Parameters Derived from Three Publically Available Satellite-Based Fire Products: A Case Study in the Central African Republic

Although it is assumed that satellite-derived descriptions of fire activity will differ depending on the dataset selected for analysis, as of yet, the effects of failed and false detections at the pixel level and on an instantaneous basis have not been propagated through space and time to determine their cumulative impact on the characterization of individual fire regime parameters. Here we perform the first ever decade long, multi-scale map comparison of fire chronologies and fire seasonality derived from three publicly available satellite-based fire products: the MODIS active fire product (MCD14ML), the ATSR nighttime World Fire Atlas (WFA), and the MODIS burned area product (MCD45A1). Results indicate that: (i) the agreement between fire chronologies derived from two dissimilar satellite products improves as fire pixels are aggregated into coarser grid cells, but diminishes as the number of years included in the time series increases; and (ii) all three datasets provide distinctly different portraits of the onset, peak, and duration of the fire season regardless of the map resolution. Differences in regional, long-term fire regime parameters derived from the three datasets are attributed to the unique capability of each sensor and detection algorithm to recognize geographical gradients, seasonal oscillations, decadal trends, and interannual variability in active fire characteristics and burned area patterns. Since different satellite sensors and detection algorithm strategies are sensitive to different types of fires, we demonstrate that disagreements in fire regime maps derived from dissimilar satellite-based fire products can be used as an advantage to highlight spatial and temporal transitions in landscape fire activity. Given access to multiple, publically available datasets, we caution against describing fire regimes using a single satellite-based active fire or burned area product.

Fractal properties of forest fires in Amazonia as a basis for modelling pan-tropical burnt area

Abstract. Current methods for modelling burnt area in dynamic global vegetation models (DGVMs) involve complex fire spread calculations, which rely on many inputs, including fuel characteristics, wind speed and countless parameters. They are therefore susceptible to large uncertainties through error propagation, but undeniably useful for modelling specific, small-scale burns. Using observed fractal distributions of fire scars in Brazilian Amazonia in 2005, we propose an alternative burnt area model for tropical forests, with fire counts as sole input and few parameters. This model is intended for predicting large-scale burnt area rather than looking at individual fire events. A simple parameterization of a tapered fractal distribution is calibrated at multiple spatial resolutions using a satellite-derived burnt area map. The model is capable of accurately reproducing the total area burnt (16 387 km2) and its spatial distribution. When tested pan-tropically using the MODIS MCD14ML active fire product, the model accurately predicts temporal and spatial fire trends, but the magnitude of the differences between these estimates and the GFED3.1 burnt area products varies per continent.

Assessing the Temporal Stability of the Accuracy of a Time Series of Burned Area Products

Temporal stability, defined as the change of accuracy through time, is one of the validation aspects required by the Committee on Earth Observation Satellites’ Land Product Validation Subgroup. Temporal stability was evaluated for three burned area products: MCD64, Globcarbon, and fire_cci. Traditional accuracy measures, such as overall accuracy and omission and commission error ratios, were computed from reference data for seven years (2001–2007) in seven study sites, located in Angola, Australia, Brazil, Canada, Colombia, Portugal, and South Africa. These accuracy measures served as the basis for the evaluation of temporal stability of each product. Nonparametric tests were constructed to assess different departures from temporal stability, specifically a monotonic trend in accuracy over time (Wilcoxon test for trend), and differences in median accuracy among years (Friedman test). When applied to the three burned area products, these tests did not detect a statistically significant temporal trend or significant differences among years, thus, based on the small sample size of seven sites, there was insufficient evidence to claim these products had temporal instability. Pairwise Wilcoxon tests comparing yearly accuracies provided a measure of the proportion of year-pairs with significant differences and these proportions of significant pairwise differences were in turn used to compare temporal stability between BA products. The proportion of year-pairs with different accuracy (at the 0.05 significance level) ranged from 0% (MCD64) to 14% (fire_cci), computed from the 21 year-pairs available. In addition to the analysis of the three real burned area products, the analyses were applied to the accuracy measures computed for four hypothetical burned area products to illustrate the properties of the temporal stability analysis for different hypothetical scenarios of change in accuracy over time. The nonparametric tests were generally successful at detecting the different types of temporal instability designed into the hypothetical scenarios. The current work presents for the first time methods to quantify the temporal stability of BA product accuracies and to alert product end-users that statistically significant temporal instabilities exist. These methods represent diagnostic tools that allow product users to recognize the potential confounding effect of temporal instability on analysis of fire trends and allow map producers to identify anomalies in accuracy over time that may lead to insights for improving fire products. Additionally, we suggest temporal instabilities that could hypothetically appear, caused by for example by failures or changes in sensor data or classification algorithms.

Impact of human population density on fire frequency at the global scale

Abstract. Human impact on wildfires, a major earth system component, remains poorly understood. While local studies have found more fires close to settlements and roads, assimilated charcoal records and analyses of regional fire patterns from remote-sensing observations point to a decline in fire frequency with increasing human population. Here, we present a global analysis using three multi-year satellite-based burned-area products combined with a parameter estimation and uncertainty analysis with a non-linear model. We show that at the global scale, the impact of increasing population density is mainly to reduce fire frequency. Only for areas with up to 0.1 people per km2, we find that fire frequency increases by 10 to 20% relative to its value at no population. The results are robust against choice of burned-area data set, and indicate that at only very few places on earth, fire frequency is limited by human ignitions. Applying the results to historical population estimates results in a moderate but accelerating decline of global burned area by around 14% since 1800, with most of the decline since 1950.

Validation of the 2008 MODIS-MCD45 global burned area product using stratified random sampling

Abstract The 2008 global burned area product MODIS-MCD45 was validated and accuracy measures were estimated globally and for several terrestrial biomes. Stratified random sampling was used to select 102 non-overlapping Thiessen scene areas (TSA) and reference fire perimeters were determined from two multi-temporal Landsat TM/ETM + images for each sampled TSA. Error matrices and six accuracy measures were chosen to satisfy criteria specified by end-users of burned area products. Globally, MODIS-MCD45 had estimated commission and omission error rates of 46% and 72% respectively, and a Dice coefficient of 0.37. Burned area extent tended to be underestimated as the MODIS product detected an estimated 48% of the burned area as determined from the reference data. The two biomes with highest accuracy were Boreal Forest and Tropical & Subtropical savanna, two of the most fire-prone biomes. In general, accuracy slightly improved in those areas where burned area was more prevalent.

Validation of the Two Standard MODIS Satellite Burned-Area Products and an Empirically-Derived Merged Product in South Africa

The 500-m Moderate Resolution Imaging Spectroradiometer (MODIS) burned area products, MCD45A1, MCD64A1, and a merged product were validated across six study sites in South Africa using independently-derived Landsat burned-area reference data during the fire season of 2007. The objectives of this study were to: (i) investigate the likelihood of the improved detection of small burns through an empirically-derived merged product; (ii) quantify the probability of detection by each product using sub-pixel burned area measures; and, (iii) compare the mean percent concurrence of burned pixels between the standard products over a ten-year time series in each site. Results show that MCD45A1 presented higher detection probabilities (i.e., 3.0%–37.9%) for small fractions ≤50%, whereas MCD64A1 appeared more reliable (i.e., 12.0%–89.2%) in detecting large fractions >50% of a burned MODIS pixel, respectively. Overall, the merged product demonstrated improved detection of the burned area in all fractions. This paper also demonstrates that, on average, >50% of MODIS burned pixels temporally concur between the MCD45A1 and MCD64A1 products in each site. These findings have significant implications for fire monitoring in southern Africa and contribute toward the understanding of the range and of the sources of errors present in the MODIS burned area products.

Fire and grazing modify grass community response to environmental determinants in savannas: Implications for sustainable use

Tropical dry forests and savannas are important repositories of plant diversity and ecosystem services in the tropics. These ecosystems are also used extensively for grazing by livestock, and represent a critical element of the rural economy of many tropical countries. Fire is considered as a part of co-evolution in these ecosystems across the globe. However, in recent decades, there has been a shift in historical fire regime. Fire has become more frequent in these landscapes, and could be further enhanced under climate change. This poses threats to existing biodiversity, ecosystem processes, and rural economy. We asked how variability in fire frequency has influenced diversity and heterogeneity in grass species composition, and richness and abundance of grass species preferred by large herbivores (referred to as grazing acceptability) in a South Indian tropical savanna forest. We assumed that an increase in fire frequency acts as the active constraint and limits an ecosystem from attaining the maximum heterogeneity, and the maximum grazing acceptability (maximum richness and abundance of grass species preferred by herbivores) in its native settings. We used MODIS active fire and burned area products to estimate fire frequency across the landscape. A nested sampling approach was used to collect information on vegetation and soil at different fire frequencies. Quantile regression analyses indicated that diversity and heterogeneity in grass species composition as well as grazing acceptability decreased with increasing fire frequencies. We found that livestock grazing intervened with the observed vegetation patterns; grass species diversity and heterogeneity, and grazing acceptability increased with grazing intensity at lower quantiles. Other measured covariates, rainfall, and soil-fertility, alone were not able to explain the observed vegetation patterns in the landscape. The results show a need to control annual fires but allow and manage intermittent fires in this landscape. A complete suppression of fire is not desirable as fire releases nutrients from burning of deeper-rooted vegetation and thus acts as a periodic nutrient pump. It also played an important role in maintaining the grass cover by reducing shrub cover. Hence, it is important to consider the complex interactions between fires–grazers–soil–vegetation to develop effective management practices. We conclude that fire frequency should be managed at low to intermediate levels (one fire in every 5–9 years, resembling the native settings), and grazing regulated, in order to sustain wild and domestic herbivores, biodiversity, and other key ecosystem processes and services over the long-term.

Burned Area Mapping in the North American Boreal Forest Using Terra-MODIS LTDR (2001–2011): A Comparison with the MCD45A1, MCD64A1 and BA GEOLAND-2 Products

An algorithm based on a Bayesian network classifier was adapted to produce 10-day burned area (BA) maps from the Long Term Data Record Version 3 (LTDR) at a spatial resolution of 0.05° (~5 km) for the North American boreal region from 2001 to 2011. The modified algorithm used the Brightness Temperature channel from the Moderate Resolution Imaging Spectroradiometer (MODIS) band 31 T31 (11.03 μm) instead of the Advanced Very High Resolution Radiometer (AVHRR) band T3 (3.75 μm). The accuracy of the BA-LTDR, the Collection 5.1 MODIS Burned Area (MCD45A1), the MODIS Collection 5.1 Direct Broadcast Monthly Burned Area (MCD64A1) and the Burned Area GEOLAND-2 (BA GEOLAND-2) products was assessed using reference data from the Alaska Fire Service (AFS) and the Canadian Forest Service National Fire Database (CFSNFD). The linear regression analysis of the burned area percentages of the MCD64A1 product using 40 km × 40 km grids versus the reference data for the years from 2001 to 2011 showed an agreement of R2 = 0.84 and a slope = 0.76, while the BA-LTDR showed an agreement of R2 = 0.75 and a slope = 0.69. These results represent an improvement over the MCD45A1 product, which showed an agreement of R2 = 0.67 and a slope = 0.42. The MCD64A1, BA-LTDR and MCD45A1 products underestimated the total burned area in the study region, whereas the BA GEOLAND-2 product overestimated it by approximately five-fold, with an agreement of R2 = 0.05. Despite MCD64A1 showing the best overall results, the BA-LTDR product proved to be an alternative for mapping burned areas in the North American boreal forest region compared with the other global BA products, even those with higher spatial/spectral resolution.