Todd J. Hawbaker is a Research Ecologist with the Geosciences and Environmental Change Science Center in Denver, Colorado.
Todd received his B.S. degree in animal ecology in 1998 from Iowa State University. After receiving his B.S., he worked for a couple of years burning and restoring tallgrass prairie in southwestern Minnesota and then pursued graduate school. He received his M.S. degree in forestry in 2003 and Ph.D. degree in forestry in 2009 from the University of Wisconsin. He joined the U.S. Geological Survey as a research ecologist in 2008. His current research with the USGS combines remote sensing with statistical and process-based ecosystem simulation models to understand the drivers behind ecosystem disturbances and quantify the impacts of disturbances on human and natural systems.
Professional Experience
Research Ecologist (Oct. 2012 - present), U.S. Geological Survey, Geosciences and Environmental Change Science Center, Denver, CO
Research Ecologist (Aug. 2008 - Oct. 2012), U.S. Geological Survey, Rocky Mountain Geographic Science Center, Denver, CO
Graduate Research Assistant (Sep. 2004 - July 2008), University of Wisconsin, Department of Forest and Wildlife Ecology, Madison, WI
Research Intern (Sep. 2003 - Aug. 2004), University of Wisconsin, Department of Forest Ecology & Management, Madison, WI
Graduate Research Assistant (Jan. 2001 - Aug. 2003), University of Wisconsin, Department of Forest Ecology & Management, Madison, WI
Restoration Ecologist (May 1998 - Dec. 2000), Salix Ecological Resources, Windom, MN
Software Engineer & UNIX Systems Administrator (May 1993 - Oct. 1997), Engineering Animation Inc., Ames, IA
Education and Certifications
2009, PhD Forestry, University of Wisconsin – Madison. Dissertation title: Fire in the wildland-urban interface, a national comparison of patterns of fire occurrence and fire risk to homes.
2003, M.S. Forestry, University of Wisconsin – Madison. Thesis title: Road density and landscape pattern in Northern Wisconsin, USA; present and past perspectives on environmental constraints and...
1998, B.S. Animal Ecology, Iowa State University.
Science and Products
Landsat-derived fire history metrics to provide critical information for prioritizing prescribed fire across the Southeast
Developing a "fire-aware" stream gage network by integrating USGS enterprise databases
Drought and Disturbances as Drivers of Long-Term Ecological Transformation and Risk
Burned Area Essential Climate Variable
Mountain Pine Beetle Impacts on Carbon Cycling
Changes to Watershed Vulnerability under Future Climates, Fire Regimes, and Population Pressures
Restoration and Conservation Opportunity Maps for the conterminous U.S. (CONUS)
The Landsat Collection 2 Burned Area Products for the conterminous United States
The Wildfire Hazard and Risk Assessment Inventory
Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA (data release)
Building locations identified before and after the Camp, Tubbs, and Woolsey wildfires
Simulated annual area burned for eleven extensively forested ecoregions in the western United States for 1980 - 2099
Contemporary fire history metrics for the conterminous United States (1984 - 2022) (ver. 2.0, March 2023)
Wildland-urban interface maps for the conterminous U.S. based on 125 million building locations
Burn probability predictions for the state of California, USA using an optimal set of spatio-temporal features.
Wetland burned area extent derived from Sentinel-2 across the southeastern U.S. (2016-2019)
The Landsat Burned Area products for the conterminous United States (ver. 3.0, March 2022)
Data inputs and outputs for simulations of species distributions in response to future fire size and climate change in the boreal-temperate ecotone of northeastern China
Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA
Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)
Colorado River Basin Actionable and Strategic Integrated Science and Technology Project—Science strategy
Identifying building locations in the wildland–urban interface before and after fires with convolutional neural networks
An aridity threshold model of fire sizes and annual area burned in extensively forested ecoregions of the western USA
Contemporary (1984–2020) fire history metrics for the conterminous United States and ecoregional differences by land ownership
Determination of optimal set of spatio-temporal features for predicting burn probability in the state of California, USA
The wildland-urban interface in the United States based on 125 million building locations
Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?
Growth of the wildland-urban interface within and around U.S. National Forests and Grasslands, 1990-2010
Mapping wetland burned area from Sentinel-2 across the southeastern United States and its contributions relative to Landsat 8 (2016-2019)
Detecting subtle change from dense landsat time series: Case studies of mountain pine beetle and spruce beetle disturbance
USGS Wildfire Hazard and Risk Assessment Clearinghouse
This online tool was designed to help identify which wildfire hazard and risk assessments are available across the United States. It provides information about available risk assessments and links to assessment data when publicly available.
Science and Products
- Science
Landsat-derived fire history metrics to provide critical information for prioritizing prescribed fire across the Southeast
Detailed information about past fire history is critical for understanding fire impacts and risk, as well as prioritizing conservation and fire management actions. Yet, fire history information is neither consistently nor routinely tracked by many agencies and states, especially on private lands in the Southeast. Remote sensing data products offer opportunities to do so but require additional prDeveloping a "fire-aware" stream gage network by integrating USGS enterprise databases
Wildfires affect streams and rivers when they burn vegetation and scorch the ground. This makes floods more likely to happen and reduces water quality. Public managers, first responders, fire scientists, and hydrologists need timely information before and after a fire to plan for floods and water treatment. This project will create a method to combine national fire databases with the StreamStats wDrought and Disturbances as Drivers of Long-Term Ecological Transformation and Risk
Forested areas in the Western U.S. that are impacted by disturbances such as fire and drought have increased in recent decades. This trend is likely to continue, with the increase in frequency and extent of wildfire activity being especially concerning. Resource managers need reliable scientific information to better understand wildfire occurrence, which can vary substantially across landscapes anBurned Area Essential Climate Variable
Essential Climate Variables (ECVs) track critical attributes of the atmosphere, oceanic, and terrestrial systems over time-scales appropriate for analyzing their relationships with climate change. As part of a larger Climate Data Record (CDR) and ECV project, scientists at GECSC are leading the development and validation of the Burned Area ECV algorithm. This algorithm automatically extracts...Mountain Pine Beetle Impacts on Carbon Cycling
In the Southern Rocky Mountains, an epidemic outbreak of mountain pine beetle (Dendroctonus ponderosae; MPB) has caused forest mortality on a scale unprecedented in recorded history. The impacts of insect-induced mortality have only recently received attention, although other disturbances such as fires and land-use change have a strong influence on carbon sequestration and can result in a net...Changes to Watershed Vulnerability under Future Climates, Fire Regimes, and Population Pressures
The project aimed to use existing models and data to understand how wildfires (number, size, and location) and land-use change will affect watersheds, and therefore water supply, under current conditions and future climates (through 2050) in the western U.S. The projected changes in temperature and precipitation are expected to affect water supply in two major ways: 1) decreased water availability - Data
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Restoration and Conservation Opportunity Maps for the conterminous U.S. (CONUS)
Nature-based solutions is a leading policy option for mitigating climate change. We mapped areas of potential restoration and conservation opportunities in the conterminous U.S. (CONUS). The potential for five scenarios were examined: increasing forest cover in urban centers, restoring historically forested areas that have been converted to grasslands, conserving pristine grasslands, rewetting peaThe Landsat Collection 2 Burned Area Products for the conterminous United States
The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions.The Wildfire Hazard and Risk Assessment Inventory
The Department of the Interior (DOI) Office of Wildland Fire and USGS created the The Wildfire Hazard and Risk Assessment Inventory to meet the Monitoring, Maintenance, and Treatment Plan requirements under the Bipartisan Infrastructure Law (BIL). It provides an inventory of key national, regional, and state wildfire risk and fire hazard assessments useful for understanding different characterizatChanges in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA (data release)
Wildfires and housing development have increased since the 1990s, presenting unique challenges for fire management. However, it is unclear how the relative influences of housing growth and changing wildfire occurrence have contributed to risk to homes. We fit a random forest using weather, land cover, topography, and past fire history to predict burn probabilities and uncertainty intervals. Then,Building locations identified before and after the Camp, Tubbs, and Woolsey wildfires
Wildland-urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated due to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown. Additionally, CNNs are computationally intensive and technically complex making it challenging for end-users, such as those who uSimulated annual area burned for eleven extensively forested ecoregions in the western United States for 1980 - 2099
This data release provides output produced by a statistical, aridity threshold fire model for 11 extensively forested ecoregions in the western United States. We identified thresholds in fire-season climate water deficit (FSCWD) that distinguish years with limited, moderate, and extensive area burned for each ecoregion. We developed a new area burned model using these relationships and used it toContemporary fire history metrics for the conterminous United States (1984 - 2022) (ver. 2.0, March 2023)
Fire history metrics enable rapidly increasing amounts of burned area data to be collapsed into a handful of data layers that can be used efficiently by diverse stakeholders. In this effort, the U.S. Geological Survey Landsat Burned Area product was used to identify burned area across CONUS over a 39-year period (1984-2022). The Landsat BA product was consolidated into a suite of annual BA productWildland-urban interface maps for the conterminous U.S. based on 125 million building locations
The wildland-urban interface (WUI) is the area where urban development occurs in close proximity to wildland vegetation. WUI maps for the conterminous U.S. were generated using building point locations, offering higher spatial resolution compared to previously developed WUI maps based on U.S. Census Bureau housing density data (Radeloff et al., 2017). Building point locations were obtained from aBurn probability predictions for the state of California, USA using an optimal set of spatio-temporal features.
Burn probability (BP) models the likelihood that a location could burn. However, predicting BP is extremely challenging, because fire behavior varies strongly among landscapes and with changing weather conditions and wildfire spread simulations are computationally intensive and require integration of data with large spatial and temporal variability. In this data release we include the monthly BP eWetland burned area extent derived from Sentinel-2 across the southeastern U.S. (2016-2019)
Wildfires and prescribed fires are frequent but under-mapped across wetlands of the southeastern United States . High annual precipitation supports rapid post-fire recovery of wetland vegetation, while associated cloud cover limits clear-sky observations. In addition, the low burn severity of prescribed fires and spectral confusion between fluctuating water levels and burned areas have resulted inThe Landsat Burned Area products for the conterminous United States (ver. 3.0, March 2022)
The U.S. Geological Survey (USGS) has developed and implemented an algorithm that identifies burned areas in temporally-dense time series of Landsat Analysis Ready Data (ARD) scenes to produce the Landsat Burned Area Products. The algorithm makes use of predictors derived from individual ARD Landsat scenes, lagged reference conditions, and change metrics between the scene and reference conditions.Data inputs and outputs for simulations of species distributions in response to future fire size and climate change in the boreal-temperate ecotone of northeastern China
This data release provides inputs needed to run the LANDIS PRO forest landscape model and the LINKAGES 3.0 ecosystem process model for the temperate-boreal ecotone Great Xing'n Mountains of northeastern China, and simulation results that underlie figures and analysis in the accompanying publication. The study compared the impacts of small and large fires on vegetation dynamics. The data release in - Publications
Filter Total Items: 57
Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA
Wildfires and housing development have increased since the 1990s, presenting unique challenges for wildfire management. However, it is unclear how the relative influences of housing growth and changing wildfire occurrence have altered risk to homes, or the potential for wildfire to threaten homes. We used a random forests model to predict burn probability in relation to weather variables at 1-km rAuthorsTodd Hawbaker, Paul D. Henne, Melanie K. Vanderhoof, Amanda R. Carlson, Miranda H. Mockrin, Volker C. RadeloffColorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)
IntroductionThe U.S. Geological Survey (USGS) is initiating a study approach focused on building cross-disciplinary connections to weave together the scientific knowledge related to drought conditions and effects in the Colorado River Basin. The basin is experiencing the worst drought in recorded history, posing unprecedented new challenges in the basin and in areas relying on water from the basinAuthorsKatharine Dahm, Daniel Jones, Patrick Anderson, Meghan C. Dick, Todd Hawbaker, Robert HortonColorado River Basin Actionable and Strategic Integrated Science and Technology Project—Science strategy
The U.S. Geological Survey (USGS) conducts a wide variety of science that improves understanding of droughts and their effects on ecosystems and society. This work includes data collection and monitoring of aquatic and terrestrial systems; assessment and analysis of patterns, trends, drivers, and impacts of drought; development and application of predictive models; and delivery of information andAuthorsKatharine Dahm, Todd Hawbaker, Rebecca J. Frus, Adrian P. Monroe, John B. Bradford, William Andrews, Alicia Torregrosa, Eric Anderson, David Dean, Sharon QiIdentifying building locations in the wildland–urban interface before and after fires with convolutional neural networks
Background: Wildland–urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated owing to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown. Additionally, CNNs are computationally intensive and technically complex, making them challenging for end-users, suAuthorsNeda K. Kasraee, Todd Hawbaker, Volker C. RadeloffAn aridity threshold model of fire sizes and annual area burned in extensively forested ecoregions of the western USA
Wildfire occurrence varies among regions and through time due to the long-term impacts of climate on fuel structure and short-term impacts on fuel flammability. Identifying the climatic conditions that trigger extensive fire years at regional scales can enable development of area burned models that are both spatially and temporally robust, which is crucial for understanding the impacts of past andAuthorsPaul D. Henne, Todd HawbakerContemporary (1984–2020) fire history metrics for the conterminous United States and ecoregional differences by land ownership
Background: Remotely sensed burned area products are critical to support fire modelling, policy, and management but often require further processing before use.Aim: We calculated fire history metrics from the Landsat Burned Area Product (1984–2020) across the conterminous U.S. (CONUS) including (1) fire frequency, (2) time since last burn (TSLB), (3) year of last burn, (4) longest fire-free intervAuthorsMelanie K. Vanderhoof, Todd Hawbaker, Casey Teske, Joe Noble, Jim SmithDetermination of optimal set of spatio-temporal features for predicting burn probability in the state of California, USA
Wildfires play a critical role in determining ecosystem structure and function and pose serious risks to human life, property and ecosystem services. Burn probability (BP) models the likelihood that a location could burn. Simulation models are typically used to predict BP but are computationally intensive. Machine learning (ML) pipelines can predict BP and reduce computational intensity. In this wAuthorsJavier Andres Pastorino Gonzalez, Joseph Willliams Director, Ashis K Biswas, Todd HawbakerThe wildland-urban interface in the United States based on 125 million building locations
The wildland-urban interface (WUI) is the focus of many important land management issues, such as wildfire, habitat fragmentation, invasive species, and human-wildlife conflicts. Wildfire is an especially critical issue, because housing growth in the WUI increases wildfire ignitions and the number of homes at risk. Identifying the WUI is important for assessing and mitigating impacts of developmenAuthorsAmanda R. Carlson, David P. Helmers, Todd Hawbaker, Miranda H. Mockrin, Volker C. RadeloffLarge fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?
Climate change is expected to increase fire activity, which has the potential to accelerate climate-induced shifts in species composition and distribution in the boreal-temperate ecotone. Wildfire can kill resident trees, and thus provide establishment opportunities for migrating tree species. However, the role of fire size and its interactions with tree species with varied life-history attributesAuthorsWenru Xu, Hong S. He, Chao Huang, Shengwu Duan, Todd Hawbaker, Paul D. Henne, Yu Liang, Zhiliang ZhuGrowth of the wildland-urban interface within and around U.S. National Forests and Grasslands, 1990-2010
The wildland-urban interface (WUI), where housing is in close proximity to or intermingled with wildland vegetation, is widespread throughout the United States, but it is unclear how this type of housing development affects public lands. We used a national dataset to examine WUI distribution and growth (1990–2010) in proximity to National Forests and created a typology to characterize each NationaAuthorsMiranda H. Mockrin, Dave Helmers, Sebastian Martinuzzi, Todd Hawbaker, Volker C. RadeloffMapping wetland burned area from Sentinel-2 across the southeastern United States and its contributions relative to Landsat 8 (2016-2019)
Prescribed fires and wildfires are common in wetland ecosystems across the Southeastern United States. However, the wetland burned area has been chronically underestimated across the region due to (1) spectral confusion between open water and burned area, (2) rapid post-fire vegetation regrowth, and (3) high annual precipitation limiting clear-sky satellite observations. We developed a machine leaAuthorsMelanie K. Vanderhoof, Todd Hawbaker, Casey Teske, Andrea Ku, Joe Noble, Joshua J. PicotteDetecting subtle change from dense landsat time series: Case studies of mountain pine beetle and spruce beetle disturbance
In contrast to abrupt changes caused by land cover conversion, subtle changes driven by a shift in the condition, structure, or other biological attributes of land often lead to minimal and slower alterations of the terrestrial surface. Accurate mapping and monitoring of subtle change are crucial for an early warning of long-term gradual change that may eventually result in land cover conversion.AuthorsSu Ye, John Rogan, Zhe Zhu, Todd Hawbaker, Sarah J. Hart, Robert A. Andrus, Arjan J.H. Meddens, Jeffery A. Hicke, J. Ronald Eastman, Dominik Kulakowski - Web Tools
USGS Wildfire Hazard and Risk Assessment Clearinghouse
This online tool was designed to help identify which wildfire hazard and risk assessments are available across the United States. It provides information about available risk assessments and links to assessment data when publicly available.