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The applications of forest clearcut maps derived from LANDSAT data are dicussed. Such maps provide harvest location information useful in general management and indicate the stage of regrowth which helps determine timber stand improvement practices. The clearcut maps are also used in fire control planning and in determining wildlife habitats.
Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated into standard fuel models accessible to the FARSITE fire spread simulator. The FARSITE model and BEHAVE are considered industry standards for fire behavior analysis. Anderson level fuels map, generated using a binary decision tree classifier are available for multiple dates in the Santa Monica Mountains and at least one date for Santa Barbara. Fuel maps that will fill in the areas between Santa Barbara and the Santa Monica Mountains study sites are in progress, as part of a NASA Regional Earth Science Application Center, the Southern California Wildfire Hazard Center. Species-level maps, were supplied to fire managing agencies (Los Angeles County Fire, California Department of Forestry). Research results were published extensively in the refereed and non-refereed literature. Educational outreach included funding of several graduate students, undergraduate intern training and an article featured in the California Alliance for Minorities Program (CAMP) Quarterly Journal.
Airborne system rapidly delivers hard copy to firefighters. Sensors in airplane send data to ground station for image processing. Imagery immediately transferred to U.S. Geologic Survey (USGS) maps by photo interpreter. Maps transmitted by telecopies directly to fire-control camps. Receipt by fire camp less than 10 minutes. Information aids in decisions involving deployment of firefighters and equipment, flood control, monitoring oilspills, observing thermal currents, and pollutions monitoring.
ERTS-1 resolution capabilities and repetitive coverage have allowed the acquisition of several statewide inventories of natural resource features not previously completed or that could not be completed in any other way. Familiarity with landform, tone, pattern and other converging factors, along with multidate imagery, has been required. Nevada's vegetation has been mapped from ERTS-1. Dynamic characteristics of the landscape have been studied. Sequential ERTS-1 imagery has proved its usefulness for mapping vegetation, following vegetation phenology changes, monitoring changes in lakes and reservoirs (including water quality), determining changes in surface mining use, making fire fuel estimates and determining potential hazard, mapping the distribution of rain and snow events, making range readiness determinations, monitoring marshland management practices and other uses. Feasibility has been determined, but details of incorporating the data in management systems awaits further research and development. The need is to accurately define the steps necessary to extract required or usable information from ERTS imagery and fit it into on-going management programs.
Deforestation and forest fires are global land cover changes that can be caused by both natural and human factors. Although monitoring forest fires in near-real time is critical for operational wildfire management, mapping historical wildfires in a spatially explicit fashion is also important for a number of reasons, including climate change studies (e.g., examining the relationship between rising temperatures and frequency of fires), fuel load management (e.g., deciding when and where to conduct controlled burns), and carbon cycle studies (e.g., quantifying how much CO2 is emitted by fires and for emissions reduction efforts under the United Nations programs for Reducing Emissions from Deforestation and Degradation -- REDD).
The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB-5) team collected several data sets related to the effects of fire on the exchange of trace gases between the surface and the atmosphere. This raster format data set covers the province of Manitoba between 1980 and 1991. The data were gridded into the Albers Equal-Area Conic (AEAC) projection from the original vector data. The original vector data were produced by Forestry Canada from hand-drawn boundaries of fires on photocopies of 1:250,000-scale maps. The locational accuracy of the data is considered fair to poor. When the locations of some fire boundaries were compared to Landsat TM images, they were found to be off by as much as a few kilometers. This problem should be kept in mind when using these data. The data are stored in binary, image format files.
The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB-5) team collected several data sets related to the effects of fire on the exchange of trace gases between the surface and the atmosphere. This vector format data set covers the province of Manitoba between 1980 and 1991 and was produced by Forestry Canada from hand-drawn boundaries of fires on photocopies of 1:250,000 scale maps. The locational accuracy of the data is considered fair to poor. When the locations of some fire boundaries were compared to Landsat TM images, they were found to be off by as much as a few kilometers.
During recent summers, warm and dry conditions have increased the occurrence of wildfires and potentially peat-fires across Alaska. Limitations in resolving the fine-scale distribution of peatlands and climate observations have constrained our ability to accurately predict peat-fire dynamics. Using a new high-resolution peatland map of Alaska, we evaluated the climate and environmental controls of past and future peat-fire activity. Ensemble machine learning models identified reduced soil moisture, higher temperatures, and evapotranspiration as key predictors of annual total burned peatland area (tenfold CV R 2 = 0.62, RMSE = 221.1 km 2 ). By the end of the twenty-first century, models forced with climate datasets from representative concentration pathways (RCPs) 4.5, 6.0, and 8.5 emission scenarios project a statewide doubling of burned peatlands (increasing 61–121%), with regional increases ranging from 25–165% in polar, 61–95% in boreal, and 102–106% in maritime ecoregions. These projections indicate that wildfires will progressively encroach further into organic-rich moist and wet peaty soils, potentially amplifying soil carbon release across Alaska.
Aerial application of fire retardant is a critical tool for managing wildland fire spread. Retardant applications are carefully planned to maximize fire line effectiveness, improve firefighter safety, protect high-value resources and assets, and limit environmental impact. However, topography, wind, visibility, and aircraft orientation can lead to differences between planned drop locations and the actual placement of the retardant. Information on the precise placement and areal extent of the dropped retardant can provide wildland fire managers with key information to (1) adaptively manage event resources, (2) assess the effectiveness of retardant slowing or stopping fire spread, (3) document location in relation to ecologically sensitive areas; and perform or validate cost-accounting for drop services. This study uses Sentinel-2 satellite data and commonly used machine learning classifiers to test an automated approach for detecting and mapping retardant application. We show that a multiclass model (retardant, burned, unburned, and cloud artifact classes) outperforms a single-class retardant model and that image differencing (post-application minus pre-application) outperforms single-image models. Compared to the random forest and support vector machine, the gradient boosting model performed the best with an overall accuracy of 0.88 and an F1 Score of 0.76 for fire retardant, though results were comparable for all three models. Our approach maps the full areal extent of the dropped retardant within minutes of image availability, rather than linear representations currently mapped by aerial GPS surveys. The development of this capability allows for the rapid assessment of retardant effectiveness and documentation of placement in relation to sensitive environments.
This dataset contains recorded vegetation classifications from 16 transects within the Kougarok Fire Complex (KFC) area in Alaska. Each transect is 50 meters long, and vertical vegetation profiles were sampled every 50cm, resulting in 101 points recorded for each transect. At each point, a vertical rod was inserted in the ground and any living plant or substrate touching the rod was recorded from top to bottom. For each plant, the plant functional type (PFT) and species name was identified and recorded. The file "flmd.xlsx" provides file level meta data for all other included files. The file (transect_metadata.csv) contains descriptive information about each of the 16 transects (field observation year and date; latitude and longitude GPS measurements of the 0, 25, and 50 meter points; and whether that area burned during the 1971, 1997, 2002, 2015, and/or 2019 fires). The files (PFT_names.csv and species_names.csv) map the short hand labels for the plant function type (PFT) and species used in the transect surveys to their full names. The remaining files are named for each transect, and contain the results of the vegetation survey for each transect. These files contain the plant functional type and the species identified at each point. Points along the transect with more than one species at that point are listed vertically from top to bottom in these files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
The Worldview (https://worldview.earthdata.nasa.gov/) application from NASA's Earth Observing System Data and Information System (EOSDIS) provides a low friction solution for users of different scientific backgrounds to access near real-time satellite imagery and data products. Worldview credits its successful growth by displaying new imagery from the Global Imagery Browse Services (GIBS), which has an increasing archive of 700+ products serving full-resolution satellite imagery from NASA's Earth observing fleet. NASA promotes the open sharing of all data with researchers, private industry, academia, and the general public. Worldview encourages this open data policy. Numerous general news publications feature Worldview for its unique imagery. Worldview also helps scholarly research in identifying field research locations, mapping thermal hotspots of active burning fires, and visualizing theoretical models of weather storm systems.
NASA’s Worldview (https://worldview.earthdata.nasa.gov/) web mapping application from the Earth Observing System Data and Information System (EOSDIS) provides a low friction solution for users of different scientific backgrounds to access satellite imagery and data products. Worldview uses imagery from the Global Imagery Browse Services (GIBS), which has an increasing catalog of 800+ products serving global, full-resolution satellite imagery from NASA’s Earth observing fleet. NASA promotes the open sharing of all data with researchers, private industry, academia, and the general public. Worldview encourages this open data policy. Numerous general news publications feature Worldview for its unique imagery. Worldview also helps scholarly research in identifying field research locations, mapping thermal hotspots of active burning fires, and visualizing theoretical models of weather storm systems amongst other uses. This presentation shares some recent uses of Worldview which highlight its capabilities.
NASA’s Worldview (https://worldview.earthdata.nasa.gov/) web mapping application from the Earth Observing System Data and Information System (EOSDIS) provides a low friction solution for users of different scientific backgrounds to access satellite imagery and data products. Worldview uses imagery from the Global Imagery Browse Services (GIBS), which has an increasing catalog of 800+ products serving global, full-resolution satellite imagery from NASA’s Earth observing fleet. NASA promotes the open sharing of all data with researchers, private industry, academia, and the general public. Worldview encourages this open data policy. Numerous general news publications feature Worldview for its unique imagery. Worldview also helps scholarly research in identifying field research locations, mapping thermal hotspots of active burning fires, and visualizing theoretical models of weather storm systems amongst other uses. This presentation shares some recent uses of Worldview which highlight its capabilities.
The Woolsey Fire began on November 8, 2018, and lasted for almost two weeks, during which it burned almost 100,000 acres of valuable landscape and habitat, including a vast area of woodland. The persistence of key woodland species provides aesthetic, monetary, and ecological value to the landscape through carbon sequestration, air temperature moderation, and erosion mitigation, among other ecosystem services. This study investigated the impact of the Woolsey Fire on native woodland species distributions and identified areas suitable for restoration within the Santa Monica Mountains National Recreation Area. The team partnered with the Resource Conservation District of the Santa Monica Mountains; National Park Service, Santa Monica Mountains National Recreation Area; California Department of Parks and Recreation, Los Angeles County Division; County of Los Angeles Fire Department, Prevention Services Bureau, Forestry Division; County of Los Angeles Department of Regional Planning; and the University of Montana. The Earth observations used include data from Landsat 8 Operational Land Imager, NASA ER-2 Jet Airborne Visible InfraRed Imaging Spectrometer, Shuttle Radar Topography Mission, and RapidEye. The team produced maps of burn severity from the Woolsey Fire, its impact on plant species distributions, and habitat suitability projections for 2050 and 2099 to assist partners in prioritizing areas for restoration. A plant community classification was successfully created using Multiple Endmember Spectral Mixture Analysis (MESMA). Overall accuracy was assessed at 90.54% by comparing the classification to validation pixels derived from ground truth information provided by our partners.
Wildfire frequency, intensity, and rate of spread are increasing across the Western U.S, resulting in more severe ecosystem impacts. Significant tree mortality can occur years after fire events, but this has received little attention compared to the immediate tree loss during a fire. We overlapped forest cover loss data with burn severity maps in the U.S. Pacific Northwest and quantified the total and delayed forest canopy loss after fires. We found that wildfires resulted in total canopy loss fraction (CLF) of 84%, 53%, and 22% within 3 years in areas burned at high, moderate, and low severity, respectively. The delayed canopy loss accounted for approximately 1/3, 1/2, and 2/3 of the total canopy loss for high, moderate, and low severity burns. Delayed canopy loss was greater in moist and cool areas than in dry and warm areas, likely because tree species in wetter environments were less adapted to survive when fires did occur. Across all forests, delayed CLF doubled as temperature increased from the climatological mean to a hot anomaly and tripled as vapor pressure deficit increased from a wet anomaly to a dry anomaly. Fire impacts on forest ecosystems are likely to intensify under future climate scenarios as wildfires expand into areas that historically experienced infrequent fires. The impacts can also be exacerbated by more frequent compound extreme events, such as droughts, heatwaves, and fires. These findings highlight the urgent need for targeted forest management strategies, particularly in mesic forests, to mitigate future fire impacts.
This talk will summarize our recent research in tropical tropospheric ozone studies in the field and from space. New tropospheric ozone and aerosol products from the TOMS (Total Ozone Mapping Spectrometer) satellite instrument will be highlighted (Hudson and Thompson, 1998; Thompson and Hudson, 1999). These are suitable for studying processes like ozone pollution resulting from biomass fires, seasonal and interannual variations and trends. Archived maps of tropospheric ozone over the tropics, from the Nimbus 7 observing period (1979-1992) are available in digital form at our website: http://metosrv2.umd.edu/-tropo. Real-time processing of TOMS data has produced images of tropical tropospheric ozone (TTO) since early 1997, using Earth-Probe TOMS; these maps are also available on the homepage. The need for validation data for TTO maps has led to establishment of the NASA/NOAA-sponsored SHADOZ (Southern Hemisphere Additional Ozonesondes) network, from which a 2-year record of high-quality ozonesonde data can be obtained: (http://hyperion.gsfc.nasa.gov/Data-services/Shadoz/shadoz-hmpg2.htrnl). Examples will be shown, along with ozonesondes from the January-February 1999 Aerosols-99 cruise of the R/V Ronald H Brown from Virginia to Cape Town, South Africa.
This talk will summarize our recent research in tropical tropospheric ozone studies in the field and from space. New tropospheric ozone and aerosol products from the TOMS (Total Ozone Mapping Spectrometer) satellite instrument will be highlighted (Hudson and Thompson, 1998; Thompson and Hudson, 1999). These are suitable for studying processes like ozone pollution resulting from biomass fires, seasonal and interannual variations and trends. Archived maps of tropospheric ozone over the tropics, from the Nimbus 7 observing period (1979-1992) are available in digital form at our website. Real-time processing of TOMS data has produced images of tropical tropospheric ozone (TTO) since early 1997, using Earth-Probe TOMS; these maps are also available on the homepage.
Forest composition and structure in the Colorado Front Range has been altered by changing wildfire regimes, particularly in response to increased fire severity. Subsequent reductions in post-fire tree regeneration can result in chronic impacts to ecological function and water quality. This project partnered with the U.S. Forest Service to estimate tree canopy recovery from 15 to 21 years after four Colorado Front Range fires that burned between 1996 and 2002— the Bobcat, Buffalo Creek, Hayman, and High Meadows fires—using Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI). First, we evaluated relationships between recovery metrics derived from spectral vegetation indices (i.e. post-fire vegetation, normalized burn ratio, percent unrecovered vegetation) and field-collected counts of post-fire tree seedling regeneration. Then, we used high-resolution imagery paired with Landsat timeseries spectral and geomorphometric data to map forest canopy cover 15-21 years post-fire. Finally, we assessed ecological drivers of recovery including topography, climate, soils, and fire severity using Random Forest. While we found that basic vegetation index metrics failed to distinguish field-measured tree regeneration, our data showed that both aspect and burn severity were important drivers of vegetation recovery. North-facing aspects tended to have higher pre-fire Normalized Difference Vegetation Index (NDVI) and thus higher burn severities. However, areas that burned at high severity experienced slower vegetation recovery, regardless of aspect suggesting that high severity fire can mute favorable site conditions on north-facing aspects (i.e. moister, more developed soils). While this work propels our understanding of variables that influence vegetative recovery, vegetation type, forest conversion, and watershed function, more work should focus on what vegetation indices identifying areas of recovery indicate across different forest types and burn severities.