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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Black Hills Wildfires: Mapping Post-Fire Conifer Regeneration using Snow-On Imagery

The 2000 Jasper Fire in the Black Hills of South Dakota was the largest wildfire to date in the region, burning over 83,000 acres of ponderosa pine forest. In collaboration with partners from the United States Forest Service (USFS) Black Hills Experimental Forest, USFS Rocky Mountain Research Station, and United States Geological Survey Geosciences and Environmental Change Science Center, we characterized post-fire forest regeneration within high-severity burn patches. We accomplished this by implementing novel conifer detection techniques using a snow index mask to create a winter, snow-on image composite from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data. We utilized 2015 USFS stem maps of field-observed regeneration plots and ocularly sampled additional reforestation sites planted in 2001–2013. In Google Earth Engine (GEE), the field data and imagery were used to train a Random Forest (RF) model. The RF model classified 2021 conifer regeneration density as low, medium, or high across the high-severity burn area with an overall accuracy of 81.3%. Approximately 45.9% of the high-severity burn had low or no regeneration (0-40 trees per acre) 20 years post-fire. Given our partners' desire to find easily accessible low conifer regeneration zones, we identified 4,079 acres of priority planting sites that were within 1,500 feet of roads, had not been planted previously, and were larger than 50 acres. This method supports the use of snow-on imagery as a successful technique to identify conifer regeneration.

Casey Menick↗
NASA NTRS1988

History of wildland fires on Vandenberg Air Force Base, California

The fire history of the past 50 years for Vandenberg AFB, California was determined using aerial photography, field investigation, and historical and current written records. This constitutes a record of the vegetation age classes for the entire base. The location, cause, and fuel type for sixty fires from this time period were determined. The fires were mapped and entered into a geographic infomation system (GIS) for Vandenberg. Fire history maps derived from this GIS were printed at 1:9600 scale and are on deposit at the Vandenberg Environmental Task Force Office. Although some ecologically significant plant communities on Vandenberg are adapted to fire, no natural fire frequency could be determined, since only one fire possibly caused by lightning occurred in the area now within the base since 1937. Observations made during this study suggest that burning may encourage the invasion of exotic species into chaparral, in particular Burton Mesa or sandhill chaparral, an unusual and geographically limited form of chaparral found on the base.

Hickson, Diana E.↗
NASA NTRS1974

Mapping a recent forest fire with ERTS-1 MSS data

Accurate fire boundary delineation provides essential information to forest managers in allocating suppression costs and planning regeneration efforts. The objective of this study was to test the capability of computer-aided analysis of ERTS-1 MSS data to accurately define the boundary of a recent forest fire and to discriminate spectral classes within the perimeter. Two frames of ERTS-1 MSS data were selected for analysis of the Moccasin Mesa Fire in Mesa Verde National Park. Data sets were collected one-half growing season and one full growing season after the fire. Results indicate that computer-aided analysis of ERTS-1 MSS data has the capability for accurately delineating fire boundaries and determining acreage of the burned area. Distinct spectral classes may also be defined within the fire perimeter.

Hitchcock, H. C.↗
NASA NTRS1990

The use of an airborne lidar for mapping cirrus clouds in FIRE, phase 2

The Univ. of Washington (UW) and Georgia Tech have recently built a dual wavelength airborne lidar for operation on the UW's Convair C-131A research aircraft. This lidar was used in studying aerosols and clouds. These studies demonstrated the utility of airborne lidar in a variety of atmospheric research and prompt the suggestion that this facility be included in the next FIRE cirrus experiment. The vertically pointing airborne lidar would be used as a complement to ground based lidars. The airborne lidar would ensure extended coverage of IFO cases that develop upwind of the surface lidars or which miss the ground based lidars while still being the focus of satellite and aircraft in situ studies. The airborne lidar would help assure that cirrus clouds were simultaneously viewed by satellite, sampled by aircraft, and structurally characterized by lidar. System specifications are listed and a schematic is shown of the lidar system aboard the C-131A.

Radke, Lawrence F.↗
NASA NTRSDate not supplied

Exemplifying the Usability of NASA Earth Observations to Analyze Potential Risk Factors that Predispose Wildfires in the Rural-Urban Areas of Córdoba, Argentina

In recent years, Córdoba, Argentina has experienced intensified wildfire activity, with fires in 2020 alone scorching over 300,000 hectares within the province. Potential causes for the increased burn area include climate change, the expanding wildland-urban interface, and inadequate fire management practices. Previous studies have produced fire frequency maps for the region, but gaps remain in understanding the parameters influencing fire behavior and growth. This project partnered with the Instituto Nacional de Tecnología Agropecuaria to address these gaps by utilizing NASA’s remote sensing capabilities to analyze key wildfire risk factors. Using a combination of data inputs from Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), and Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), a ten-year baseline was created using environmental variables to determine anomalies that influenced the fires of 2020. Of these anomalies, the baseline data were used to calculate the statistical significance of the environmental factors to the wildfires. This study found that the normalized difference vegetation index (NDVI) and precipitation were the strongest indicators for the September 2020 wildfires. Using the environmental risk factors, this project created a wildfire risk map for the province of Córdoba, which can be used to enhance partner’s fire management strategies and decision-making processes.

Chassety Raines↗
NASA NTRS2024

Córdoba Wildland Fires: Assessing Fire Risk Factors in Córdoba, Argentina using Earth Observations

In recent years, Córdoba, Argentina has experienced intensified wildfire activity, with fires in 2020 alone scorching over 300,000 hectares within the province. Potential causes for the increased burn area include climate change, the expanding wildland-urban interface (WUI), and inadequate fire management practices. Previous studies have produced fire frequency maps for the region, but gaps remain in understanding the environmental parameters influencing fire behavior and growth. We partnered with the Instituto Nacional de Tecnología Agropecuaria (INTA) to address these gaps by utilizing NASA Earth observing data to analyze key wildfire risk factors. Using a combination of data inputs from Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), and Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), we created a ten-year baseline using environmental variables to determine anomalies that influenced the fires of 2020. Baseline data were used to calculate the statistical significance of the environmental factors as precursors to wildfires. We found that the normalized difference vegetation index (NDVI) and precipitation were the strongest indicators for the September 2020 wildfires. Using the environmental risk factors, we created a wildfire risk map for the province of Córdoba, which can be used to enhance our partner’s fire management strategies and decision-making processes.

wildland fires↗
NASA NTRS1982

Forestry timber typing. Tanana demonstration project, Alaska ASVT

The feasibility of using LANDSAT digital data in conjunction with topographic data to delineate commercial forests by stand size and crown closure in the Tanana River basin of Alaska was tested. A modified clustering approach using two LANDSAT dates to generate an initial forest type classification was then refined with topographic data. To further demonstrate the ability of remotely sensed data in a fire protection planning framework, the timber type data were subsequently integrated with terrain information to generate a fire hazard map of the study area. This map provides valuable assistance in initial attack planning, determining equipment accessibility, and fire growth modeling. The resulting data sets were incorporated into the Alaska Department of Natural Resources geographic information system for subsequent utilization.

Morrissey, L. A.↗
NASA NTRS1974

Vegetation mapping from ERTS imagery of the Okavango Delta

The Okavango is Botswana's major water resource. The present study has been specifically directed at mapping vegetation types within the delta and generally concerned with finding what information of value to plant and animal ecologists could be extracted from the imagery. To date it has been found that. (1) It is possible to map broad vegetation types from the imagery. (2) Imagery of the delta records the state of the system in a manner which will facilitate long-term studies of plant succession. (3) Phenological events can be detected. (4) The imagery can be used to detect and map wild fires. This will be useful in determining the role of fire in the ecology of the region. Using the imagery it is thus possible to map existing vegetation and monitor both short and long-term changes.

Willamson, D. T.↗
NASA NTRS2022

Arizona Water Resources: Utilizing Aerial Imagery and NASA Earth Observations to Assess Pinyon-Juniper Tree Mortality in Flagstaff, AZ

Pinyon-juniper woodlands (PJW) are a vital habitat and food source for several wildlife species and a source of both utility and cultural importance for Indigenous groups. In 2021, amidst a decades-long drought, an extensive juniper mortality event occurred at Wupatki National Monument (WNM) in Arizona. In response, the National Park Service (NPS) is evaluating which land management practices will be beneficial. In partnership with the NPS, the NASA DEVELOP team used remote sensing data to map PJW mortality and analyze the relation of tree mortality to stand density, climate, and topography in north-central Arizona from 2015 to 2021. To identify the extent of PJW, the team performed an unsupervised classification using National Agricultural Imagery Program (NAIP) data with validation sources including NPS-created land cover maps, Landscape Fire and Resource Management Planning Tools (LANDFIRE), NPS and United States Forest Service (USFS) vegetation maps, and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data. Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), and Landsat 8-derived Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI) were used to analyze factors contributing to pinyon-juniper mortality. Although no relationships were found in the broader study region, PJW mortality was weakly correlated to elevation, soil moisture, and land surface temperature within WNM. Results from this study can inform NPS vegetation management that best protects natural and cultural resources.

Margaret Jaenicke↗
NASA NTRS2003

The Economical Microbolometer-Based Environmental Radiometer Satellite (EMBERSAT) Designed for Forest Fire Detection and Monitoring

Thermal infrared imagery from several satellite instruments, such as the NOAA AVHRR and the NASA MODIS, is presently used to detect and map forest fires. But while these radiometers can identify fires they are designed and optimized for cloud detection, providing relatively low spatial resolution and quickly saturating even for small fires. Efforts to detect and monitor forest fires from space would benefit from the development of single-sensor satellites designed specifically for this purpose. With the advent of uncooled thermal detectors, and thus the absence of aggressive cooling, the possibility of developing small satellites for the purpose of fire detection and monitoring becomes practical and cost-effective. Thus is the case with the Economical Microbolometer Based Environmental Radiometer Satellite (EMBERSat) program. The objective of this program is to develop a single, prototype satellite that will provide multiband thermal imagery with a spatial resolution of 250m and a dynamic range of 300-1000K. The thermal imaging payload has flight heritage in the Infrared Spectral Imaging Radiometer that flew aboard mission STS-85 and the spacecraft is a variant of the SimpleSat bus launched from the shuttle Columbia as part of STS-109. The EMBERSat program is a technology demonstration initiative with the eventual goal of providing high-resolution thermal imagery to both the scientific community and the public.

Lancaster, Redgie S.↗
NASA NTRS2004

The Economical Microbolometer-Based Environmental Radiometer Satellite (EMBERSat) Designed for Forest Fire Detection and Monitoring

Thermal infrared imagery from several satellite instruments, such as the NOAA AVHRR and the NASA MODIS, is presently used to detect and map forest fires. But while these radiometers can identify fires they are designed and optimized for cloud detection, providing relatively low spatial resolution and quickly saturating even for small fires. Efforts to detect and monitor forest fires from space would benefit from the development of single-sensor satellites designed specifically for this purpose. With the advent of uncooled thermal detectors, and thus the absence of aggressive cooling, the possibility of developing small satellites for the purpose of fire detection and monitoring becomes practical and cost-effective. Thus is the case with the Economical Microbolometer Based Environmental Radiometer Satellite (EMBERSat) program. The objective of this program is to develop a single, prototype satellite that will provide multiband thermal imagery with a spatial resolution of 250m and a dynamic range of 300-1000K. The thermal imaging payload has flight heritage in the Infrared Spectral Imaging Radiometer that flew aboard mission STS-85 and the spacecraft is a variant of the SimpleSat bus launched from the shuttle Columbia as part of STS-105. The EMBERSat program is a technology demonstration initiative with the eventual goal of providing high-resolution thermal imagery to both the scientific community and the public.

Lancaster, Redgie S.↗
NASA NTRS1993

Mapping Wildfires In Nearly Real Time

Airborne infrared-sensing system flies over wildfire as infrared detector in system and navigation subsystem generate data transmitted to firefighters' camp. There, data plotted in form of map of fire, including approximate variations of temperature. System, called Firefly, reveals position of fires and approximate thermal intensities of regions within fires. Firefighters use information to manage and suppress fires. Used for other purposes with minor modifications, such as to spot losses of heat in urban areas and to map disease and pest infestation in vegetation.

Nichols, Joseph D.↗
NASA NTRS2011

Mapping Canopy Damage from Understory Fires in Amazon Forests Using Annual Time Series of Landsat and MODIS Data

Understory fires in Amazon forests alter forest structure, species composition, and the likelihood of future disturbance. The annual extent of fire-damaged forest in Amazonia remains uncertain due to difficulties in separating burning from other types of forest damage in satellite data. We developed a new approach, the Burn Damage and Recovery (BDR) algorithm, to identify fire-related canopy damages using spatial and spectral information from multi-year time series of satellite data. The BDR approach identifies understory fires in intact and logged Amazon forests based on the reduction and recovery of live canopy cover in the years following fire damages and the size and shape of individual understory burn scars. The BDR algorithm was applied to time series of Landsat (1997-2004) and MODIS (2000-2005) data covering one Landsat scene (path/row 226/068) in southern Amazonia and the results were compared to field observations, image-derived burn scars, and independent data on selective logging and deforestation. Landsat resolution was essential for detection of burn scars less than 50 ha, yet these small burns contributed only 12% of all burned forest detected during 1997-2002. MODIS data were suitable for mapping medium (50-500 ha) and large (greater than 500 ha) burn scars that accounted for the majority of all fire-damaged forest in this study. Therefore, moderate resolution satellite data may be suitable to provide estimates of the extent of fire-damaged Amazon forest at a regional scale. In the study region, Landsat-based understory fire damages in 1999 (1508 square kilometers) were an order of magnitude higher than during the 1997-1998 El Nino event (124 square kilometers and 39 square kilometers, respectively), suggesting a different link between climate and understory fires than previously reported for other Amazon regions. The results in this study illustrate the potential to address critical questions concerning climate and fire risk in Amazon forests by applying the BDR algorithm over larger areas and longer image time series.

Morton, Douglas C.↗
NASA NTRS1977

Monitoring the extent and occurrence of fire in the different veld types of South Africa with particular reference to its ecological role and role in range management

The author has identified the following significant results. Veld burning was recorded from LANDSAT imagery covering approximately 75 million ha or 62% of the surface of the eastern part of South Africa. All basic data on the location, areas, and numbers of burns for 10 biomes, composed of 67 veld types, are available on 1:250,000 and 1:500,000 map overlays, and are summarized on small scale maps showing fire distribution and amount burned in classes per 15 minute square of latitude and longitude. Veld burning is not randomly distributed, but is almost continuous over a broad belt, widest in the north and narrowing southeastwards, and then southwestwards between the eastern escarpment and the area. It is shown that over almost the whole sea, the overall pattern of veld burning is clearly marked out as early as July in midwinter, subsequent development being merely an intensification of the pattern.

Edwards, D.↗
NASA NTRS1982

Forest Fire Observation

Conditions on the perimeter of a forest fire can be obtained by use of airborne remote sensing techniques demonstrated by Ames Research Center. An Ames U-2 high-altitude survey aircraft served as an aerial fire observation system. Equipped with two types of sensors, the U-2 produces real-time infrared images of fireground scenes. Information acquired by the U-2's scanners defines the fire boundary and aids fire management decisions by showing the size, shape and direction of burn and the locations of hot spots in the fire zone. U-2 sends sensor date in digital form to an antenna at Ames Research Center. There the data is computer processed into images which are overlaid on U.S. Geological Survey topographical maps of the fire area. Maps are then transmitted by telecopy machine directly to fire control center. Whole process takes less than 10 minutes and the U-2 can provide information for up to five hours. Ames antenna can pick up signals from the U-2 anywhere within a 300 mile radius from Ames.

Source record↗
NASA NTRS2004

Forest Understory Fire in the Brazilian Amazon in ENSO and Non-ENSO Years: Area Burned and Committed Carbon Emissions

"Understory fires" that burn the floor of standing forests are one of the most important types of forest impoverishment in the Amazon, especially during the severe droughts of El Nino Southern Oscillation (ENSO) episodes. However, we are aware of no estimates of the areal extent of these fires for the Brazilian Amazon and, hence, of their contribution to Amazon carbon fluxes to the atmosphere. We calculated the area of forest understory fires for the Brazilian Amazon region during an El Nino (1998) and a non El Nino (1995) year based on forest fire scars mapped with satellite images for three locations in eastern and southern Amazon, where deforestation is concentrated. The three study sites represented a gradient of both forest types and dry season severity. The burning scar maps were used to determine how the percentage of forest that burned varied with distance from agricultural clearings. These spatial functions were then applied to similar forest/climate combinations outside of the study sites to derive an initial estimate for the Brazilian Amazon. Ninety-one percent of the forest area that burned in the study sites was within the first kilometer of a clearing for the non ENSO year and within the first four kilometers for the ENSO year. The area of forest burned by understory forest fire during the severe drought (ENSO) year (3.9 millions of hectares) was 13 times greater than the area burned during the average rainfall year (0.2 million hectares), and twice the area of annual deforestation rate. Dense forest was, proportionally, the forest area most affected by understory fires during the El Nino year, while understory fires were concentrated in transitional forests during the year of average rainfall. Our estimate of aboveground tree biomass killed by fire ranged from 0.06 Pg to 0.38 Pg during the ENSO and from 0,004 Pg to 0,024 Pg during the non ENSO.

Alencar, A.↗
NASA NTRS2013

Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data

High temporal resolution information on burned area is a prerequisite for incorporating bottom-up estimates of wildland fire emissions in regional air transport models and for improving models of fire behavior. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the evolution of nine large wildland fires. For each fire, local input parameters for the kriging model were defined using variogram analysis. The accuracy of the kriging model was assessed using high resolution daily fire perimeter data available from the U.S. Forest Service. We also assessed the temporal reporting accuracy of the MODIS burned area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared to 33% for MCD45A1 and 53% for MCD64A1.

Aqua↗