Burn Severity Mapping

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Abstract

Wildland fire is a dominant ecological disturbance shaping terrestrial ecosystems across the United States, with profound implications for vegetation dynamics, biogeochemical cycling, hydrologic processes, wildlife habitat, and human communities. In recent decades, wildfire activity has intensified in many regions due to interacting influences of climate change, land-use legacies, fuel accumulation, and expanding wildland–urban interfaces. Understanding not only where fires occur, but also how they affect ecosystems, is essential for advancing fire science and informing adaptive management strategies. The Monitoring Trends in Burn Severity (MTBS) Fire Program was established to provide a consistent, long-term, and spatially explicit record of burn severity and fire extent for large wildland fires across the United States. Beginning in 1984 and continuing to the present, MTBS integrates Landsat satellite imagery, standardized spectral indices, and expert analyst interpretation to map burn severity across all land ownerships and major ecosystem types. This review synthesizes the scientific foundations, methodological framework, data products, applications, strengths, and limitations of the MTBS program. We examine its role in advancing understanding of fire regimes, climate–fire interactions, post-fire ecosystem responses, and land management decision-making, and we discuss future directions for national fire-effects monitoring under changing environmental conditions.

Keywords: burn severity, MTBS, wildland fire, Landsat, remote sensing, fire regimes, fire ecology

1. Introduction

Wildland fire is a fundamental ecological process that has shaped landscapes in North America for millennia. Fire influences species composition, successional pathways, ecosystem productivity, nutrient cycling, and landscape heterogeneity, while also interacting with other disturbances such as insects, drought, and storms (Agee, 1993; Pyne et al., 1996). In many ecosystems, fire is not merely a destructive force but an essential driver of ecological resilience and renewal.

At the same time, wildland fire poses substantial risks to human life, infrastructure, air quality, and water resources. Over the past several decades, the United States has experienced an increase in the frequency, size, and severity of wildfires, particularly in western forested ecosystems (Westerling et al., 2006; Abatzoglou & Williams, 2016). These changes are widely attributed to a combination of anthropogenic climate change, historical fire suppression, fuel accumulation, land-use change, and expanding development in fire-prone landscapes.

In response to these trends, there has been growing recognition that effective fire management and policy require comprehensive information not only about fire occurrence, but also about fire effects. Burn severity—broadly defined as the degree of ecological change caused by fire—has emerged as a critical metric linking fire behavior to ecological outcomes (Keeley, 2009). Burn severity influences post-fire erosion, vegetation recovery, wildlife habitat suitability, and long-term ecosystem trajectories, making it a key variable in both scientific research and applied management.

Despite its importance, burn severity information historically lacked consistency at national scales. Prior to the development of national remote sensing–based programs, burn severity mapping was often conducted on a fire-by-fire basis, using varying methods, definitions, and classification schemes. This fragmentation limited the ability to conduct cross-regional comparisons, assess long-term trends, or evaluate cumulative fire impacts at landscape to national scales.

The Monitoring Trends in Burn Severity (MTBS) Fire Program was established to address this gap. By producing a standardized, long-term dataset of fire perimeters and burn severity for large wildland fires across the United States, MTBS has fundamentally changed how fire effects are studied, managed, and incorporated into policy and planning. This review provides a comprehensive synthesis of the MTBS program, examining its origins, methodological framework, scientific contributions, and future relevance in an era of accelerating environmental change.

2. Conceptual Foundations: Fire Effects and Burn Severity

2.1 Defining Burn Severity

Burn severity is commonly defined as the degree of ecological change caused by fire, encompassing impacts to vegetation, soils, and organic matter (Keeley, 2009). While often used interchangeably with fire intensity or fire severity, burn severity is conceptually distinct. Fire intensity refers to the energy output of a fire, typically measured as heat release per unit length of fire front, whereas burn severity reflects the ecological consequences of that energy on the landscape.

Burn severity integrates multiple components, including:

• Consumption of live and dead vegetation
• Mortality of overstory and understory plants
• Alteration of soil organic layers
• Changes in soil structure, hydrophobicity, and nutrient availability

Because these effects can vary spatially within a single fire, burn severity is inherently heterogeneous, creating mosaics of ecological impact that influence post-fire recovery and landscape dynamics.

2.2 Field-Based Measures of Burn Severity

Field-based approaches to measuring burn severity, such as the Composite Burn Index (CBI), have played a foundational role in linking ground observations to remote sensing metrics (Key & Benson, 2006). CBI integrates observations across multiple vertical strata—from soil surface to canopy—to produce a plot-level severity score. While highly informative, field-based methods are labor-intensive and impractical to apply across large spatial extents or long time periods.

The need to extrapolate field-based understanding of burn severity to regional and national scales has driven the development of remote sensing–based approaches, which can provide consistent, repeatable measurements across vast areas.

2.3 Remote Sensing of Burn Severity

Satellite remote sensing has become the primary means of mapping burn severity at landscape to national scales. Spectral indices derived from multispectral imagery are particularly effective at detecting fire-induced changes in vegetation structure and soil exposure. Among these, the Normalized Burn Ratio (NBR) has become the most widely used index for burn severity mapping (Key & Benson, 2006).

NBR exploits the contrasting responses of near-infrared and shortwave infrared reflectance to fire, capturing reductions in green vegetation and increases in char and exposed soil. By differencing pre-fire and post-fire NBR values, the differenced Normalized Burn Ratio (dNBR) provides a quantitative measure of spectral change attributable to fire.

These developments laid the conceptual and methodological groundwork for national-scale burn severity mapping efforts such as MTBS.

3. Historical Development of the MTBS Program

3.1 Pre-MTBS Fire Mapping Efforts

Prior to MTBS, fire mapping efforts in the United States were largely decentralized. Individual agencies and regions maintained fire perimeter datasets, often with inconsistent spatial accuracy and limited attribute information. Burn severity mapping, when conducted, was typically restricted to high-priority fires or specific management objectives, using methods that varied widely across jurisdictions.

This lack of standardization limited the ability to synthesize fire effects information across large spatial and temporal scales. As wildfire activity increased in the late 20th and early 21st centuries, the absence of a national fire-effects dataset became increasingly problematic for researchers and policymakers alike.

3.2 Establishment of the MTBS Program

The MTBS program was formally initiated in 2005 through a collaboration between the U.S. Geological Survey (USGS) and the U.S. Forest Service (USFS). The program was designed to retrospectively map burn severity for all large wildland fires in the United States beginning in 1984, the first year of continuous Landsat Thematic Mapper data availability (Eidenshink et al., 2007).

The selection of 1984 as the starting point was strategic. Landsat provides the longest continuous, moderate-resolution satellite record suitable for detecting fire effects, enabling MTBS to create a multi-decadal dataset using consistent sensor characteristics and processing approaches.

3.3 Program Rationale and Design Principles

The MTBS program was guided by several core principles:

1. National consistency: Methods and outputs needed to be comparable across regions, ecosystems, and land ownerships.
2. Scientific credibility: Burn severity products should be grounded in established remote sensing theory and field-based validation.
3. Operational feasibility: Methods needed to be efficient enough to process thousands of fires across decades.
4. Public accessibility: Data products should be openly available to support broad scientific and management use.

These principles shaped the methodological framework that continues to define MTBS today.

4. Spatial and Temporal Scope of the MTBS Program

4.1 Geographic Coverage

The Monitoring Trends in Burn Severity (MTBS) Fire Program encompasses the entire United States, including the conterminous United States (CONUS), Alaska, and Hawaii. A defining feature of MTBS is its inclusion of fires across all land ownerships, including federal, state, tribal, and private lands. This comprehensive geographic coverage distinguishes MTBS from many other fire datasets that are limited to specific agencies or jurisdictions.

By transcending administrative boundaries, MTBS enables consistent comparisons of fire effects across diverse ecological regions, management regimes, and ownership patterns. This national perspective has been particularly valuable for assessing regional variability in fire regimes and identifying broad-scale trends in burn severity (Miller et al., 2009; Dillon et al., 2011).

4.2 Fire Size Thresholds

MTBS focuses on large wildland fires, defined using region-specific size thresholds:

• Fires ≥1,000 acres in the western United States
• Fires ≥500 acres in the eastern United States

These thresholds reflect fundamental differences in fire regimes, landscape patterns, and management contexts between eastern and western ecosystems. In the western United States, fire regimes are typically characterized by larger fire sizes and greater spatial variability in severity, whereas eastern fires tend to be smaller but more frequent (Guyette et al., 2012).

While this focus on large fires inevitably excludes many smaller events, it allows MTBS to efficiently capture the majority of burned area nationally, as large fires account for a disproportionate share of total area burned in most regions.

4.3 Temporal Coverage and Update Cycle

The MTBS dataset begins in 1984, coinciding with the availability of consistent Landsat Thematic Mapper imagery, and extends to the present with regular updates. This multi-decadal temporal coverage enables robust analyses of long-term trends in fire extent and burn severity under changing climatic and land-use conditions.

Annual updates ensure that MTBS remains relevant for contemporary fire management and research applications, while the retrospective component provides historical context critical for understanding baseline conditions and variability.

5. Remote Sensing Foundations of Burn Severity Mapping

5.1 The Landsat Satellite Program

The MTBS program relies primarily on data from the Landsat satellite series, including Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI. Landsat imagery offers several advantages for burn severity mapping:

• Moderate spatial resolution (30 m) suitable for landscape-scale analysis
• Long-term continuity, enabling multi-decadal comparisons
• Spectral bands sensitive to vegetation and soil properties
• Global coverage and open data access

The stability and longevity of the Landsat program have been critical to the success of MTBS, allowing the program to apply consistent methods across time and space (Wulder et al., 2012).

5.2 Spectral Response of Fire Effects

Fire alters land surface properties in ways that are readily detectable by multispectral sensors. Combustion of vegetation reduces near-infrared reflectance due to loss of leaf structure, while char and exposed mineral soils increase reflectance in the shortwave infrared portion of the spectrum. These spectral changes form the basis for remote sensing indices used to map burn severity.

Among the various indices developed for fire applications, the Normalized Burn Ratio (NBR) has proven particularly effective (Key & Benson, 2006). NBR is calculated as:

where NIR and SWIR represent near-infrared and shortwave infrared reflectance, respectively.

5.3 Differenced and Relativized Burn Ratios

MTBS primarily uses the differenced Normalized Burn Ratio (dNBR), calculated as the difference between pre-fire and post-fire NBR values:

Higher dNBR values generally correspond to greater spectral change and, by inference, higher burn severity.

In some analyses, particularly in heterogeneous landscapes, the relativized dNBR (RdNBR) is used to normalize burn severity relative to pre-fire vegetation conditions (Miller & Thode, 2007). While RdNBR can improve comparability across vegetation types, MTBS primarily relies on dNBR due to its operational simplicity and established field validation.

6. MTBS Image Selection and Preprocessing

6.1 Pre-Fire Image Selection

Selecting appropriate pre-fire imagery is critical for accurate burn severity mapping. MTBS analysts select images that best represent conditions immediately prior to the fire, while minimizing confounding factors such as:

• Cloud cover
• Smoke
• Snow or ice
• Seasonal phenological differences

In some cases, pre-fire images may be selected from the previous growing season if imagery immediately preceding the fire is unavailable or unsuitable.

6.2 Post-Fire Image Selection

Post-fire imagery is typically selected from the first growing season following the fire, allowing sufficient time for fire effects to be expressed while minimizing vegetation recovery that could obscure severity signals. The timing of post-fire imagery is particularly important in rapidly recovering ecosystems, where early post-fire green-up can reduce apparent severity (Keeley et al., 2009).

6.3 Radiometric and Geometric Processing

All Landsat imagery used in MTBS undergoes standard preprocessing, including:

• Radiometric calibration
• Atmospheric correction
• Geometric correction and co-registration

These steps ensure that pre- and post-fire images are directly comparable and that observed spectral differences are attributable to fire effects rather than sensor or atmospheric artifacts.

7. Burn Severity Classification Framework

7.1 Severity Classes

MTBS classifies burn severity into a standardized set of categories:

1. Unburned / Low Change
2. Low Severity
3. Moderate Severity
4. High Severity

These classes are designed to be broadly applicable across ecosystems while retaining ecological meaning. The boundaries between classes are based on dNBR thresholds informed by field-based Composite Burn Index (CBI) relationships and expert interpretation (Key & Benson, 2006).

7.2 Analyst Interpretation and Threshold Adjustment

A distinguishing feature of MTBS is the incorporation of expert analyst interpretation. Rather than applying fixed, fully automated thresholds, analysts evaluate each fire individually, adjusting thresholds as needed to account for ecosystem-specific responses, image quality, and contextual information.

This semi-automated approach balances efficiency with ecological realism, improving the accuracy and interpretability of burn severity maps compared to purely automated methods.

7.3 Fire Perimeter Delineation

In addition to burn severity classification, MTBS produces standardized fire perimeters. These perimeters are derived from a combination of existing fire records, satellite imagery, and analyst refinement. Accurate perimeters are essential for calculating burned area, summarizing severity statistics, and integrating MTBS data with other fire datasets.

8. Quality Assurance and Validation

8.1 Quality Control Procedures

MTBS employs multiple layers of quality control, including peer review of mapped fires, consistency checks, and documentation of processing decisions. Analyst notes accompanying each fire provide transparency regarding data limitations and interpretation choices.

8.2 Field Validation and Uncertainty

Burn severity classifications are supported by empirical relationships between dNBR and field-based CBI measurements. However, uncertainty remains due to factors such as image timing, vegetation type, and post-fire recovery dynamics. Recognizing these uncertainties is critical for appropriate application of MTBS data.

9. MTBS Data Products and Accessibility

9.1 Fire Perimeter Datasets

One of the core outputs of the MTBS program is a standardized set of fire perimeter polygons representing the spatial extent of each mapped fire. These perimeters are developed through a combination of existing fire occurrence records, satellite imagery interpretation, and analyst refinement. The resulting polygons provide a consistent spatial representation of burned areas across all regions and land ownerships.

Standardized perimeters enable reliable estimates of burned area, facilitate comparison across fires and regions, and support integration with other spatial datasets such as vegetation maps, climate surfaces, and land ownership layers. The MTBS perimeters are frequently used as a reference dataset in national and regional fire assessments.

9.2 Burn Severity Raster Products

The primary scientific contribution of MTBS lies in its burn severity raster maps, which depict the spatial distribution of severity classes within each fire perimeter. These rasters capture the inherent heterogeneity of fire effects, revealing mosaics of low-, moderate-, and high-severity patches that are critical for understanding ecological responses and recovery trajectories.

Burn severity rasters are typically provided at 30-m resolution, matching Landsat pixel size, and include both continuous dNBR values and classified severity categories. This dual representation allows users to select the level of detail appropriate for their application, whether quantitative modeling or categorical assessment.

• Data span: 1984 to 2024 (Fig 1) for mapped large wildland fires across the U.S. — this period represents the full temporal range currently released in MTBS datasets. 
• The dataset is continually updated as new fire seasons are processed. MTBS typically maps fires from the prior year and releases updates quarterly (e.g., February, May, August, November). 
• At present, 2022 fire season data are fully mapped and available, and the program is actively processing 2023 and 2024 fires with completion targeted by mid-2026.
• Currently, MTBS fire data/products are available for 30,730 fires national-wide (including Hawaii, Alaska, and Porto Rico).
• The program projects to make some of the 2025 rapid assessment products especially for larger fires available by early 2026.

9.4 Metadata and Documentation

Each MTBS fire is accompanied by detailed metadata describing:

• Image acquisition dates
• Sensors used
• Severity thresholds applied
• Analyst notes and confidence assessments

This documentation enhances transparency and reproducibility, allowing users to evaluate data suitability for specific applications and to interpret results in light of known limitations.

9.4 Data Accessibility and Distribution

MTBS data are publicly available through federal data portals such as www.mtbs.gov and burn severity portal- www.burnseverity.cr.usgs.gov and are widely used by researchers, land managers, and policymakers. Open access to MTBS products has been a key factor in their widespread adoption and citation in the scientific literature, supporting interdisciplinary research and cross-agency collaboration.

10. Scientific Applications of MTBS Data

10.1 Fire Regime Characterization and Trend Analysis

MTBS has played a central role in advancing understanding of fire regimes, defined by the frequency, size, intensity, and severity of fires over time. By providing consistent severity data across decades, MTBS enables quantitative assessments of changes in fire activity at regional to national scales.

Numerous studies have used MTBS data to document increases in burned area and burn severity in western U.S. forests since the mid-1980s (Miller et al., 2009; Dillon et al., 2011). These analyses have revealed spatially variable trends, with some regions experiencing pronounced increases in high-severity fire, while others show more modest changes.

Such findings have contributed to ongoing debates regarding the extent to which contemporary fire activity deviates from historical fire regimes and the implications for ecosystem resilience and management.

10.2 Climate–Fire Relationships

MTBS data have been widely integrated with climate datasets to explore linkages between fire activity and climatic drivers. Studies combining MTBS burn severity maps with temperature, precipitation, snowpack, and drought indices have demonstrated strong associations between warm, dry conditions and increased fire extent and severity (Westerling et al., 2006; Abatzoglou & Williams, 2016).

By enabling spatially explicit analyses of severity patterns, MTBS has helped move climate–fire research beyond simple metrics of area burned, revealing how climate influences not only the occurrence of fires but also their ecological impacts. This distinction is critical for projecting future fire effects under climate change scenarios.

10.3 Post-Fire Vegetation Recovery and Succession

Burn severity is a key determinant of post-fire vegetation recovery trajectories. MTBS data have been used to examine how severity influences rates of vegetation regrowth, species composition, and successional pathways across ecosystems.

Studies have shown that high-severity fire often leads to delayed or altered recovery, particularly in forests where seed sources are limited or climatic conditions are unfavorable (Turner et al., 2014). By contrast, low- and moderate-severity fire can promote heterogeneity and resilience in many fire-adapted systems.

MTBS burn severity maps provide essential spatial context for such studies, allowing researchers to link recovery patterns to severity gradients across landscapes.

10.4 Hydrology, Erosion, and Watershed Processes

Fire-induced changes to vegetation and soil properties can dramatically alter hydrologic responses, increasing runoff, erosion, and debris flow risk. Burn severity is one of the strongest predictors of these post-fire hazards (Moody et al., 2013).

MTBS data have been incorporated into watershed-scale models to assess erosion potential, sediment delivery, and flood risk following wildfire. High-severity burn areas, in particular, are often associated with elevated risks to downstream infrastructure and water quality.

The national consistency of MTBS severity data allows for comparative studies of post-fire hydrologic responses across climatic gradients and physiographic regions.

10.5 Wildlife Habitat and Biodiversity

Fire severity patterns strongly influence wildlife habitat availability and biodiversity. Many species respond to specific severity classes or mosaics, with some benefiting from high-severity patches and others dependent on unburned or low-severity refugia.

MTBS data have supported studies examining habitat suitability, population dynamics, and landscape connectivity in post-fire environments. By capturing the spatial configuration of severity classes, MTBS enables analyses of habitat heterogeneity that are critical for conservation planning.

11. Management and Policy Applications

11.1 Post-Fire Emergency Response and Rehabilitation

One of the most direct applications of MTBS data is in post-fire emergency response and rehabilitation planning. Burn severity maps are used to identify areas at high risk of erosion, flooding, and vegetation loss, informing prioritization of mitigation measures such as mulching, seeding, or infrastructure protection.

Although MTBS products are typically generated after initial emergency response periods, they provide valuable context for longer-term rehabilitation and monitoring efforts.

11.2 Fuel Management and Forest Planning

MTBS data contribute to fuel management and forest planning by providing historical context on fire effects and severity patterns. Land managers use MTBS maps to evaluate how past fires have altered fuel structures and to inform decisions regarding prescribed burning, mechanical treatments, and restoration strategies.

Understanding historical severity distributions can also help managers assess whether contemporary fires are producing ecological effects consistent with management objectives or historical conditions.

11.3 National Assessments and Policy Development

At national scales, MTBS has been instrumental in supporting assessments of wildfire trends and impacts. The dataset has been used in federal reports evaluating wildfire risk, ecosystem vulnerability, and climate change impacts, providing an empirical foundation for policy discussions.

By offering a transparent and scientifically credible record of fire effects, MTBS supports evidence-based decision-making and facilitates communication between scientists, managers, and policymakers.

12. Integration with Other Fire and Environmental Datasets

MTBS is frequently used in combination with other datasets, including:

• Fire occurrence and incident reporting systems
• Active fire detections
• Vegetation and fuel type maps
• Climate and weather datasets

Integration of MTBS with these complementary data sources enhances analytical power, enabling multi-dimensional assessments of fire drivers, effects, and outcomes.

Part IV

13. Strengths of the MTBS Program

The Monitoring Trends in Burn Severity (MTBS) Fire Program possesses several strengths that have established it as a cornerstone of wildfire science and management in the United States.

13.1 National Consistency and Standardization

Perhaps the most significant strength of MTBS is its national consistency. By applying standardized methods across all regions, ecosystems, and land ownerships, MTBS enables direct comparison of burn severity patterns across space and time. This consistency is essential for large-scale analyses of fire regimes, climate–fire relationships, and cumulative impacts that would be impossible using fragmented, region-specific datasets.

13.2 Long-Term Temporal Record

The MTBS dataset spans more than four decades, beginning in 1984. This long-term record is critical for detecting trends, understanding interannual variability, and placing recent wildfire activity in historical context. Few other fire-effects datasets offer comparable temporal depth combined with consistent methodology.

13.3 Integration of Expert Interpretation

Unlike fully automated global burn severity products, MTBS incorporates expert analyst interpretation, allowing for ecosystem-specific adjustments and contextual evaluation of imagery. This semi-automated approach improves ecological relevance and reduces misclassification caused by phenological variability, sensor artifacts, or non-fire disturbances.

13.4 Public Accessibility and Transparency

MTBS data are publicly available and accompanied by detailed metadata and documentation. This transparency promotes reproducibility, encourages widespread use, and fosters collaboration among scientists, land managers, and policymakers.

14. Limitations and Sources of Uncertainty

Despite its many strengths, MTBS has limitations that users must consider when applying the data.

14.1 Focus on Large Fires

MTBS includes only large fires (≥500 or ≥1,000 acres, depending on region), excluding many smaller fires that may nonetheless be ecologically significant, particularly in grasslands, shrublands, and frequently burned eastern ecosystems. As a result, MTBS does not capture the full spectrum of fire activity nationwide.

14.2 Spatial Resolution Constraints

The 30-m spatial resolution of Landsat imagery limits the ability of MTBS to detect fine-scale fire effects, such as small unburned refugia or subtle understory impacts. While appropriate for landscape-scale analysis, this resolution may be insufficient for site-specific management applications.

14.3 Spectral vs. Ecological Severity

MTBS burn severity metrics are based on spectral change, which serves as a proxy for ecological effects but does not capture all dimensions of fire impact. For example, soil heating, belowground effects, delayed tree mortality, and changes in microbial communities may not be fully reflected in spectral indices (Keeley, 2009).

14.4 Post-Fire Image Timing

The timing of post-fire imagery can influence severity estimates, particularly in ecosystems with rapid post-fire recovery. Early green-up may reduce apparent severity, while delayed imagery may obscure initial fire effects. Although MTBS analysts carefully select imagery, some uncertainty remains unavoidable.

15. Comparison with Other Fire and Burn Severity Datasets

MTBS occupies a unique niche among fire datasets, but it is increasingly used alongside other national and global products.

15.1 Fire Occurrence and Perimeter Datasets

Fire occurrence datasets, such as incident reporting systems and agency fire records, provide information on ignition points, causes, and suppression activities but often lack detailed severity information. MTBS complements these datasets by adding spatially explicit fire-effects data.

15.2 Active Fire and Burned Area Products

Global products derived from sensors such as MODIS provide near-real-time active fire detection and burned area mapping at coarser spatial resolution. While valuable for monitoring fire activity, these products are less suitable for detailed severity analysis and long-term ecological studies than MTBS.

15.3 Emerging High-Resolution Datasets

Recent advances in high-resolution satellite imagery and cloud-based processing platforms offer opportunities for more detailed fire-effects mapping. However, these datasets often lack the long-term continuity and national consistency that define MTBS.

16. Future Directions and Emerging Opportunities

As wildfire regimes continue to evolve under climate change, the MTBS program faces both challenges and opportunities.

16.1 Integration of New Satellite Sensors

Incorporating data from newer satellite sensors, including those with higher temporal or spatial resolution, could enhance burn severity mapping while maintaining continuity with the Landsat record.

16.2 Improved Severity Metrics

Advances in remote sensing theory and field validation may enable development of improved severity metrics that better capture ecological impacts, including belowground effects and delayed mortality.

16.3 Expanded Analytical Tools

Providing user-friendly analytical tools and summary products could further increase the accessibility and utility of MTBS data for non-specialist users, including land managers and decision-makers.

16.4 Addressing Climate Change Impacts

As climate change alters fire regimes, MTBS will remain essential for documenting emerging patterns of fire extent and severity, informing adaptive management strategies, and supporting evidence-based policy development.

17. Conclusions

The Monitoring Trends in Burn Severity Fire Program represents a landmark achievement in national-scale wildfire monitoring. By providing a consistent, long-term, and spatially explicit record of burn severity across the United States, MTBS has transformed understanding of wildfire effects and supported a wide range of scientific, management, and policy applications.

MTBS data have advanced fire ecology by enabling robust analyses of fire regimes and severity trends, improved understanding of climate–fire interactions, and supported post-fire management and restoration efforts. While limitations exist, the strengths of the program far outweigh its constraints, and MTBS remains one of the most authoritative sources of burn severity information available.

As wildfire activity continues to intensify under changing environmental conditions, the importance of maintaining and enhancing national fire-effects monitoring programs such as MTBS cannot be overstated. Continued investment in MTBS will be critical for understanding the past, managing the present, and preparing for the future of wildfire in the United States.

References

Abatzoglou, J. T., & Williams, A. P. (2016). Impact of anthropogenic climate change on wildfire across western U.S. forests. Proceedings of the National Academy of Sciences, 113(42), 11770–11775.

Agee, J. K. (1993). Fire ecology of Pacific Northwest forests. Island Press.

Dillon, G. K., et al. (2011). Both topography and climate affected forest and woodland burn severity in two regions of the western U.S., 1984–2006. Ecosphere, 2(12), 1–33.

Eidenshink, J., et al. (2007). A project for monitoring trends in burn severity. Fire Ecology, 3(1), 3–21.

Guyette, R. P., et al. (2012). Fire history in the eastern United States. Fire Ecology, 8(2), 1–21.

Keeley, J. E. (2009). Fire intensity, fire severity and burn severity: a brief review and suggested usage. International Journal of Wildland Fire, 18(1), 116–126.

Key, C. H., & Benson, N. C. (2006). Landscape assessment: ground measure of severity, the Composite Burn Index. In FIREMON: Fire effects monitoring and inventory system. USDA Forest Service.

Miller, J. D., & Thode, A. E. (2007). Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment, 109(1), 66–80.

Miller, J. D., et al. (2009). Quantitative evidence for increasing forest fire severity in the Sierra Nevada and southern Cascade Mountains. Ecosystems, 12, 16–32.

Moody, J. A., et al. (2013). Post-wildfire erosion response. Earth-Science Reviews, 116, 1–29.

Pyne, S. J., Andrews, P. L., & Laven, R. D. (1996). Introduction to wildland fire. Wiley.

Turner, M. G., et al. (2014). Effects of fire severity on forest recovery in the western United States. Ecological Monographs, 84(4), 1–29.

Westerling, A. L., et al. (2006). Warming and earlier spring increase western U.S. forest wildfire activity. Science, 313(5789), 940–943.

Wulder, M. A., et al. (2012). Opening the archive: how free data has enabled the science and monitoring promise of Landsat. Remote Sensing of Environment, 122, 2–10.