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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

A Collaborative Decision Environment for UAV Operations

NASA is developing Intelligent Mission Management (IMM) technology for science missions employing long endurance unmanned aerial vehicles (UAV's). The IMM groundbased component is the Collaborative Decision Environment (CDE), a ground system that provides the Mission/Science team with situational awareness, collaboration, and decisionmaking tools. The CDE is used for pre-flight planning, mission monitoring, and visualization of acquired data. It integrates external data products used for planning and executing a mission, such as weather, satellite data products, and topographic maps by leveraging established and emerging Open Geospatial Consortium (OGC) standards to acquire external data products via the Internet, and an industry standard geographic information system (GIs) toolkit for visualization As a Science/Mission team may be geographically dispersed, the CDE is capable of providing access to remote users across wide area networks using Web Services technology. A prototype CDE is being developed for an instrument checkout flight on a manned aircraft in the fall of 2005, in preparation for a full deployment in support of the US Forest Service and NASA Ames Western States Fire Mission in 2006.

D'Ortenzio, Matthew V.↗
NASA NTRS2018

The Effects of Vegetative Type, Edges, Fire History, Rainfall and Management in Fire-Maintained Habitat

The combined effects of fire history, climate, and landscape features (e.g., edges) on habitat specialists need greater focus in fire ecology studies, which usually only emphasize characteristics of the most recent fire. Florida scrub-jays are an imperiled, territorial species that prefer medium (1.2-1.7 m) shrub heights, which are dynamic because of frequent fires. We measured short, medium, and tall habitat quality states annually within 10 ha grid cells (that represented potential territories) because fires and vegetative recovery cause annual variation in habitat quality. We used multistate models and model selection to test competing hypotheses about how transition probabilities vary between states as functions of environmental covariates. Covariates included vegetative type, edges (e.g., roads, forests), precipitation, openings (gaps between shrubs), mechanical cutting, and fire characteristics. Fire characteristics not only included an annual presence/absence of fire covariate, but also fire history covariates: time since the previous fire, the longest fire-free interval, and the number of repeated fires. Statistical models with support included many covariates for each transition probability, often including fire history, interactions and nonlinear relationships. Tall territories resulted from 28 years of fire suppression and habitat fragmentation that reduced the spread of fires across landscapes. Despite 35 years of habitat restoration and prescribed fires, half the territories remained tall suggesting a regime shift to a less desirable habitat condition. Edges reduced the effectiveness of fires in setting degraded scrub and flatwoods into earlier successional states making mechanical cutting an important tool to compliment frequent prescribed fires.

Breininger, David R.↗
NASA NTRS2015

Thirty Years of Change in Subalpine Forest Cover from Landsat Image Analysis in the Sierra Nevada Mountains of California

Landsat imagery was analyzed to understand changes in subalpine forest stands since the mid-1980s in the Sierra-Nevada region of California. At locations where long-term plot measurements have shown that stands are becoming denser in the number of small tree stems (compared to the early 1930s), the 30-year analysis of Landsat greenness index (NDVI) indicated that no consistent increases in canopy leaf cover have occurred at these same locations since the mid-1980s. Interannual variations in stand NDVI closely followed snow accumulation amounts recorded at nearby stations. In contrast, at eastern Sierra whitebark pine stand locations where it has been observed that widespread tree mortality has occurred, decreasing NDVI trends over the past 5-10 years were consistent with rapid loss of forest canopy cover. Landsat imagery was further analyzed to understand patterns of post-wildfire vegetation recovery, focusing on high burn severity (HBS) patches within burned areas dating from the late 1940s. Analysis of landscape metrics showed that the percentage of total HBS area comprised by the largest patch of recovered woody cover was relatively small in all fires that occurred since 1995, but increased rapidly with time since fire. Patch complexity of recovered woody cover decreased notably after more than 50 years of regrowth, but was not readily associated with time for fires that occurred since the mid 1990s. The aggregation level of patches with recovery of woody cover increased steadily with time since fire. The study approach using satellite remote sensing can be expanded to assess the consequences of stand-replacing wildfires in all forests of the region.

Fires↗
NASA NTRSDate not supplied

New Technologies From NASA's FireSense Technology Program

NASA Wildland Fire Initiative - NASA’s Wildland Fire Initiative, is a NASA-wide effort focused on delivering NASA’s unique science and technological capabilities to operational agencies, striving towards measurable improvements in US wildland fire management. - The initiative involves the Science Mission Directorate (SMD), Aeronautics Research Mission Directorate (ARMD), the Space Technology Mission Directorate (STMD), including the Small Business Innovative Research (SBIR) program. - NASA works with interagency partners such as the National Oceanic and Atmospheric Administration (NOAA), the U.S. Department of Agriculture Forest Service (USFS), the California Department of Forestry and Fire Protection, the National Interagency Fire Center, and commercial partners.

FireSense↗
NASA NTRS2013

Impacts of Disturbance History on Forest Carbon Stocks and Fluxes: Merging Satellite Disturbance Mapping with Forest Inventory Data in a Carbon Cycle Model Framework

Forest carbon stocks and fluxes are highly dynamic following stand-clearing disturbances from severe fire and harvest and this presents a significant challenge for continental carbon budget assessments. In this work we use forest inventory data to parameterize a carbon cycle model to represent post-disturbance carbon trajectories of carbon pools and fluxes for specific forest types growing in high and low site productivity class settings. We then apply these trajectories to landscapes and regions based on forest age distributions derived from either the FIA data or from Landsat time series stacks (1985-2006) for 54 representative scenes throughout most of the conterminous United States. We estimate the net carbon uptake in forests caused by post-disturbance growth and decomposition ("regrowth sink") for forested regions across the country. At the landscape scale, the prevailing condition of positive net ecosystem productivity (NEP) is in stark contrast to local patches with large sources, particularly in the west where fires and clear cuts create contiguous disturbed patches. At the continental scale, regional differences in disturbance rates reflect management patterns of high disturbance rates in the Southeastern and South Central states, and lower disturbance rates in the Northeast and Northern Lakes States. Despite low contemporary disturbance rates in the Northeast and Northern Lakes States (0.61 and 0.74% y(exp −1)), the regrowth sink there remains of moderate to large strength (88 and 57 g C m(exp −2) y(exp −1)) owing to the continued legacy from historical clearing. Large regrowth sinks are also found in the Southeast, South Central, and Pacific Southwest regions (85, 86, and 95 g C m(exp −2) y(exp −1)) where disturbance rates also tend to be higher (1.59, 1.38, and 0.93% y(exp −1)). Overall, the Landsat-derived disturbance rates are elevated relative to FIA-derived rates (1.19 versus 0.93% y(exp −1)) particularly for western regions. The differences only modestly adjust regional- and continental-scale carbon budgets, reducing NEP from forest regrowth by about 8%.

carbon↗
NASA NTRS2003

Synergic use of TOMS and Aeronet Observations for Characterization of Aerosol Absorption

The role of aerosol absorption on the radiative transfer balance of the earth-atmosphere system is one of the largest sources of uncertainty in the analysis of global climate change. Global measurements of aerosol single scattering albedo are, therefore, necessary to properly assess the radiative forcing effect of aerosols. Remote sensing of aerosol absorption is currently carried out using both ground (Aerosol Robotic Network) and space (Total Ozone Mapping Spectrometer) based observations. The satellite technique uses measurements of backscattered near ultraviolet radiation. Carbonaceous aerosols, resulting from the combustion of biomass, are one of the most predominant absorbing aerosol types in the atmosphere. In this presentation, TOMS and AERONET retrievals of single scattering albedo of carbonaceous aerosols, are compared for different environmental conditions: agriculture related biomass burning in South America and Africa and peat fires in Eastern Europe. The AERONET and TOMS derived aerosol absorption information are in good quantitative agreement. The most absorbing smoke is detected over the African Savanna. Aerosol absorption over the Brazilian rain forest is less absorbing. Absorption by aerosol particles resulting from peat fires in Eastern Europe is weaker than the absorption measured in Africa and South America. This analysis shows that the near UV satellite method of aerosol absorption characterization has the sensitivity to distinguish different levels of aerosol absorption. The analysis of the combined AERONET-TOMS observations shows a high degree of synergy between satellite and ground based observations.

Torres, O.↗
NASA NTRS2024

Autonomous Drone Integration in Prescribed Fire Operations

With the surge in wildfire frequency and severity, the risk to firefighters, communities, and forests has escalated dramatically. Climate change and increased amounts of fuel have intensified these challenges, making wildfire management more important than ever. Prescribed burns, a controlled manner of burning land, are a crucial strategy for wildfire prevention, ecosystem management, and forest health. Nonetheless, traditional methods of implementing prescribed burns are labor-intensive, slow, and risk-laden due to human involvement. Our innovative approach leverages autonomous drone swarms to revolutionize prescribed burning methods. These advanced drones collaborate to ignite fires strategically, gather real-time data, and suppress sections of the fire as needed. By minimizing human proximity to the flames, our solution has the potential to significantly enhance operational efficiency and safety.

UAV systems↗
NASA NTRS1989

Designing an infrared system to map and detect wildland fires

The 'Firefly' project is developing an infrared remote sensing system to provide near real-time wildland fire information for fire management and suppression. Recent technological advances in several areas now allow the design of an end-to-end, infrared system to map and detect wildland fires. The system components will include an airborne infrared sensor, automatic onboard signal and data processing, telecommunications link, and integration into a ground data terminal. The system will provide improved performance over current systems in terms of increased timeliness of data delivery, quantifiable accuracy, data consistency, reliability, and maintainability. The system will be the next generation of wildland fire mapping and detection system for the United States Forest Service.

Nichols, J. David↗
NASA NTRS2006

Making Robot Planes Useful for Scientific Investigation of Earth

This viewgraph slides presentation reviews the program to use unmanned aerial vehicles to gather information to study the Earth, the changes to the climate, and to protect the Earth. Several robot planes are shown, and cooperative programs with other agencies of the U.S. Government are highlighted. Including one with the United States Forest Service, that is planned to assist in locating fires

Jennison, Chris↗
NASA NTRS2013

Monitoring Regional Forest Disturbances across the US with near Real Time MODIS NDVI Products Resident to the ForWarn Forest Threat Early Warning System

Forest threats across the US have become increasingly evident in recent years. Sometimes these have resulted in regionally evident disturbance progressions (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and have resulted in extensive forest overstory mortality. In addition to stand replacement disturbances, other forests are subject to ephemeral, sometimes yearly defoliation from various insects and varying types and intensities of ephemeral damage from storms. Sometimes, after prolonged severe disturbance, signs of recovery in terms of Normalized Difference Vegetation Index (NDVI) can occur. The growing prominence and threat of forest disturbances in part have led to the formation and implementation of the 2003 Healthy Forest Restoration Act which mandated that national forest threat early warning system be developed and deployed. In response, the US Forest Service collaborated with NASA, DOE Oakridge National Laboratory, and the USGS Eros Data Center to build and roll-out the near real time ForWarn early warning system for monitoring regionally evident forest disturbances. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines that are used with current NDVI to derive a suite of six forest change products that are refreshed every 8 days. ForWarn employs daily quarter kilometer MODIS NDVI data from the Aqua and Terra satellites, including MOD13 data for deriving historical baseline NDVIs and eMODIS 7 NDVI for compiling current NDVI. In doing so, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally de-noise, fuse, and aggregate current and historical MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of products per year. The 24 day compositing interval enables disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. Forest change products are computed versus the previous 1, previous 3, and all previous years in the MODIS record for a given 24 day interval. Other "weekly" forest change products include one computed using an adaptive length compositing method for quicker detection of disturbances, two others that adjust for seasonal fluctuations in normal vegetation phenology (e.g., early versus late springs). This overall approach enables forest disturbance dynamics from a variety of regionally evident biotic and abiotic forest disturbances to be viewed and assessed through the calendar year. The change products are also being utilized for forest change trend analysis and for developing regional forest overstory mortality products. ForWarn's forest change products are used to alert forest health specialists about new forest disturbances. Such alerts are also typically based on available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances to multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn offers products that could be combined with other geospatial data on forest biomass to assess forest disturbance carbon impacts within the conterminous US.

Spruce, Joseph P.↗
NASA NTRS2024

Vermont Wildland Fires: Investigating the Role of Antecedent Conditions and Recent Environmental Trends in Exacerbating Fire Risk and Potential in Vermont

Under a changing climate, increases in dry conditions and extreme heat events are projected to exacerbate wildfire risk in the northeastern U.S. In recent years, Vermont has observed higher annual temperatures, more frequent heatwaves, increased annual precipitation, extreme flood events, and decreased snowfall. The mechanisms through which environmental factors contribute to increased fire risk in humid environments, such as Vermont, are poorly understood. The team partnered with the National Weather Service, the Vermont Division of Forests, and the University of Vermont to investigate phenological trends and antecedent conditions influencing wildland fire risk. For the phenological analysis, from 2001 to 2023, vegetation data, phenological dates, and snow water equivalent (SWE) values were accessed from Landsat 5Thematic Mapper (TM), Landsat 7Enhanced Thematic Mapper Plus (ETM+), Landsat 8Operational Land Imager (OLI), Landsat 9OLI-2, the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Snow Data Assimilation System (SNODAS), respectively. For the antecedent condition analysis, from 2008 to 2023, soil moisture, Environmental Stress Index, wind speed, minimum relative humidity, and daily precipitation data were obtained from the Global Land Data Assimilation System (GLDAS), SERVIR, gridMET Wind, gridMET Humidity, and NClimGrid, respectively. The study found that green-up dates over the study period remain relatively stable, while snowmelt dates appear increasingly variable. Minimum relative humidity was the most significant environmental variable correlated with wildfire risk in Vermont. Results from this study will inform the National Weather Service's preparation of fire forecasts before prescribed burns and support community outreach by the Vermont Agency of Natural Resources.

Wildland Fire↗
NASA NTRSDate not supplied

Oregon Wildfires: Integrating ECOSTRESS to Map & Analyze Vegetation Moisture for Wildfire Modeling

Wildfire season in the western USA is starting earlier and gaining in intensity. The Bootleg Fire in Southern Oregon began on July 6th, 2021, and burned over 1675 km2 before it was fully contained on August 15th, 2021. Evapotranspiration (ET) is one indicator of vegetation moisture and there is interest in using high-resolution ET products from ECOsystem and Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) in future wildfire modeling. In partnership with the Pacific Northwest National Laboratory and US Forest Service, the team examined ECOSTRESS ET for the two years before the Bootleg Fire and assessed the relationship between ET, topography, and vegetation. Remotely sensed data from Shuttle Radar Topography Mission (SRTM) and Global Ecosystem Dynamics Investigation (GEDI) along with ancillary data from the National Land Cover Database (NLCD) and Landscape Fire Resource Management Planning Tools (LANDFIRE) were incorporated. The team examined data in relation to soil burn severity from the Burned Area Emergency Response (BAER) program. From ET median composites for April 1st – July 5th, 2021 and 2019, the Bootleg Fire area showed a 7 mm/day decrease in ET and a relative 75% decrease in ET between 2019 and 2021. Approximately 6% of the Bootleg Fire area was identified as having a high soil burn severity and these areas were found predominantly in the evergreen forest land cover class and northward facing slopes with a mean ET decrease of 3 mm/day between 2019 and 2021. The team also analyzed ECOSTRESS Water Use Efficiency products as an additional vegetation moisture indicator of pre-fire conditions in the study area. The end products will allow the partners to assess if higher resolution vegetation moisture datasets from ECOSTRESS will improve wildfire modeling for other susceptible areas.

Brenna Hatch↗
NASA NTRS1998

Satellite Investigations of Fire, Smoke, and Carbon Monoxide during April 1994 MAPS Mission: Case Studies over Tropical Asia

During April 9-19, 1994, the Measurement of Air Pollution from Satellites (MAPS) measured free tropospheric carbon monoxide (CO) concentrations on a near-global basis. For these eleven days the global lkm advanced very high resolution radiometer (AVHRR) Pathfinder data are used to detect fires and smoke over the Indo-Burma region (85 degrees E - 110 degrees E; 10 degrees N -30 degrees N). The fire activities are categorized for four major ecosystems that include (1) cropland/natural vegetation mosaic (CNVM), (2) evergreen broadleaf forest (EBF), (3) mixed forest (MFD), and (4) grassland (GL). Using published emission rates between particulate matter and carbon monoxide concentrations from temperate areas, the fire counts along with other information are used to obtain estimates of CO concentrations from the AVERR data. More than 7000 fires are detected during the study period with 23%, 43%, 24%, and 10% fires in the CNVM, EBF, MFD, and GL ecosystems, respectively. The enhanced CO concentrations over the area of study are either over or downwind of the fires detected by the AVHRR. The preliminary AVHRR estimates of CO concentrations are smaller than the MAPS-measured values by a factor of 4 to 5 for fire counts areater than 200. The differences are attributed to the lack of transport mechanisms and other assumptions in the current model. However, these results show a good potential for usino the AVHRR measurements to detect fires and smoke and also to estimate CO concentrations.

Christopher, Sundar A.↗
NASA NTRS2016

Texas Disasters II: Utilizing NASA Earth Observations to Assist the Texas Forest Service in Mapping and Analyzing Fuel Loads and Phenology in Texas Grasslands

The risk of severe wildfires in Texas has been related to weather phenomena such as climate change and recent urban expansion into wild land areas. During recent years, Texas wild land areas have experienced sequences of wet and dry years that have contributed to increased wildfire risk and frequency. To prevent and contain wildfires, the Texas Forest Service (TFS) is tasked with evaluating and reducing potential fire risk to better manage and distribute resources. This task is made more difficult due to the vast and varied landscape of Texas. The TFS assesses fire risk by understanding vegetative fuel types and fuel loads. To better assist the TFS, NASA Earth observations, including Landsat and Moderate Resolution Imaging Specrtoradiometer (MODIS) data, were analyzed to produce maps of vegetation type and specific vegetation phenology as it related to potential wildfire fuel loads. Fuel maps from 2010-2011 and 2014-2015 fire seasons, created by the Texas Disasters I project, were used and provided alternating, complementary map indicators of wildfire risk in Texas. The TFS will utilize the end products and capabilities to evaluate and better understand wildfire risk across Texas.

Brooke, Michael↗
NASA NTRS2023

Semi-Autonomous Transportation of Emergency Supplies via sUAS

Over the past several decades, the extent and severity of wildfires in the United States has increased dramatically. This, accordingly, has put ever-increasing pressure on wildland firefighters to mitigate the effects of fire damage. Wildland firefighters have exceptionally dangerous and strenuous jobs. The United States Forest Service has an interest to develop an autonomous sUAS logistics payload delivery system to transport supplies to crews on the fireline. A design reference mission which includes the transportation of portable drinking water from a helicopter drop site closer to crews on the fire line was developed. Two delivery methods were designed and prototyped within this project, with one of them tested in flight.

Wildfire UAS Logistics↗
NASA NTRS1997

Remote Sensing of Global Fire Patterns, Aerosol Optical Thickness, and Carbon Monoxide During April 1994

Fires play a crucial role in several ecosystems. They are routinely used to burn forests in order to accommodate the needs of the expanding population, clear land for agricultural purposes, eliminate weeds and pests, regenerate nutrients in grazing and crop lands and produce energy for cooking and heating purposes. Most of the fires on earth are related to biomass burning in the tropics, although they are not confined to these latitudes. The boreal and tundra regions also experience fires on a yearly basis. The current study examines global fire patterns, Aerosol Optical Thickness (AOT) and carbon monoxide concentrations during April 9-19, 1994. Recently, global Advanced Very High Resolution Radiometer (AVHRR) data at nadir ground spatial resolution of 1 km are made available through the NASA/NOAA Pathfinder project. These data from April 9-19, 1994 are used to map fires over the earth. In summary, our analysis shows that fires from biomass burning appear to be the dominant factor for increased tropospheric CO concentrations as measured by the MAPS. The vertical transport of CO by convective activities, along with horizontal transport due to the prevailing winds, are responsible for the observed spatial distribution of CO.

Christopher, Sundar A.↗
NASA NTRS2007

Advanced NASA Earth Science Mission Concept for Vegetation 3D Structure, Biomass and Disturbance

Carbon in forest canopies represents about 85% of the total carbon in the Earth's aboveground biomass (Olson et al., 1983). A major source of uncertainty in global carbon budgets derives from large errors in the current estimates of these carbon stocks (IPCC, 2001). The magnitudes and distributions of terrestrial carbon storage along with changes in sources and sinks for atmospheric C02 due to land use change remain the most significant uncertainties in Earth's carbon budget. These uncertainties severely limit accurate terrestrial carbon accounting; our ability to evaluate terrestrial carbon management schemes; and the veracity of atmospheric C02 projections in response to further fossil fuel combustion and other human activities. Measurements of vegetation three-dimensional (3D) structural characteristics over the Earth's land surface are needed to estimate biomass and carbon stocks and to quantify biomass recovery following disturbance. These measurements include vegetation height, the vertical profile of canopy elements (i.e., leaves, stems, branches), andlor the volume scattering of canopy elements. They are critical for reducing uncertainties in the global carbon budget. Disturbance by natural phenomena, such as fire or wind, as well as by human activities, such as forest harvest, and subsequent recovery, complicate the quantification of carbon storage and release. The resulting spatial and temporal heterogeneity of terrestrial biomass and carbon in vegetation make it very difficult to estimate terrestrial carbon stocks and quantify their dynamics. Vegetation height profiles and disturbance recovery patterns are also required to assess ecosystem health and characterize habitat. The three-dimensional structure of vegetation provides habitats for many species and is a control on biodiversity. Canopy height and structure influence habitat use and specialization, two fundamental processes that modify species richness and abundance across ecosystems. Accurate and consistent 3D measurements of forest structure at the landscape scale are needed for assessing impacts to animal habitats and biodiversity following disturbance.

Ranson, K. Jon↗
NASA NTRSDate not supplied

An Observation-Driven Framework for Modeling Post-Fire Hydrologic Response: Evaluation for Two Central California Case Studies

In a warming climate, wildfires are becoming increasingly common, especially in semi-arid environments. Wildfires can disrupt forest ecosystems and induce changes to the land surface. Collectively, these impacts can alter the hydrologic response of a catchment following a fire, resulting in increased potential for surface runoff, reduced evapotranspiration, and, ultimately, a higher risk for flash flooding and mass wasting. The timescale for post-fire recovery of hydrological processes to return to pre-fire conditions is not well established due to the lack of ground measurements. Accurate characterization of fire impacts on hydrologic response is also challenging to simulate, given the complex interplay of various processes. Here, we present a generalized framework to quantify wildfire impacts on runoff generation. We consider the vegetation and soil disturbances as the primary contributors to post-fire floods. Using an ensemble modeling structure to account for parameter uncertainty and consider model sensitivity, remotely sensed leaf area index (LAI) is assimilated into a land surface model (LSM) to simulate vegetation disturbance, and the maximum land surface saturation LSM parameter is decreased to parameterize the soil disturbance following observed fires. We evaluated the impacts of fire-induced changes to LAI and soil saturation on hydrologic states like runoff and evapotranspiration. Analysis of two events in central California shows that 1) the LAI assimilation has a greater impact on water balance; and 2) the soil scheme captures a range of outcomes, with substantial impacts on surface runoff for some ensemble members, which could affect flood potential.

Timothy M Lahmers↗