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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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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Evaluation of a technique for satellite-derived area estimation of forest fires

The advanced very high resolution radiometer (AVHRR), has been found useful for the location and monitoring of both smoke and fires because of the daily observations, the large geographical coverage of the imagery, the spectral characteristics of the instrument, and the spatial resolution of the instrument. This paper will discuss the application of AVHRR data to assess the geographical extent of burning. Methods have been developed to estimate the surface area of burning by analyzing the surface area effected by fire with AVHRR imagery. Characteristics of the AVHRR instrument, its orbit, field of view, and archived data sets are discussed relative to the unique surface area of each pixel. The errors associated with this surface area estimation technique are determined using AVHRR-derived area estimates of target regions with known sizes. This technique is used to evaluate the area burned during the Yellowstone fires of 1988.

Cahoon, Donald R., Jr.↗
NASA NTRS1975

Utilization of EREP data in geological evaluation, regional planning, forest management, and water management in North Carolina

The author has identified the following significant results. The S190A, S190B, and S192 photographs and imagery were studied, using standard air-photo interpretation techniques supplemented by color additive viewing and density slicing. The EREP data were found to have potential usefulness for natural resource inventory work, water quality monitoring, and land use mapping for specific problems at scales up to 1:30,000. Distinctions between forest types in North Carolina are limited to conifers, mixed conifer-hardwoods, and hardwoods. Geologic interpretation was limited to detection of lineaments; lithologic differentiation and soil group mapping have proved infeasible in North Carolina except for differentiation of wetland soils in the coastal plain. Imagery from the S192 multispectral scanner has proved to be capable of useful discriminations for vegetation and crop analysis.

Welby, C. W.↗
NASA NTRS1999

Environmental and Archaeological Research in the Peten, Guatemala

The Peten, Northern Guatemala, was once inhabited by a population of several million Maya before their collapse in the 9th century A.D.. The seventh and eight centuries were a time of crowning glory four millions of Maya; by 930 A.D. only a few scattered houses remained, testifying to the greatest disaster in human history. What is known is that at the time of their collapse the Maya had cut down most of their trees. After centuries of regeneration the Peten now represent the largest remaining tropical forest in Central America but is experiencing rapid deforestation in the wake of an invasion of settlers. The successful adaptive techniques of the indigenous population are being abandoned in favor of the destructive techniques of monoculture and cattle raising. Remote sensing and Geographic Information System (GIS) analysis are being used to address issues in Maya archeology as well as monitor the effects of increasing deforestation in the area today. One thousand years ago the forests of the Peten were nearly destroyed by the ancient Maya who after centuries of successful adaptation finally overused their resources. Current inhabitants are threatening to do the same thing today in a shorter time period with a lesser population. Through the use of remote sensing/GIS analysis we are attempting to answer questions about the past in order to protect the resources of the future.

Sever, Thomas L.↗
NASA NTRS1975

Surveys of the earth's resources and environment by satellites

The potential and promise of observing the earth from the vantage point of space is discussed. The systematic surveying of processes and phenomena occurring on the surface of the earth by Landsat 1 and Nimbus 5 is considered to be useful in the following areas: assessment of water resources; mineral and petroleum exploration; land use planning; crop, forest, and rangeland inventory; assessment of flood, earthquake, and other environmental hazards; monitoring coastal processes; environmental effects of industrial effluents and of air pollution; mapping the distribution and types of ice covering the earth's polar caps and global soil moisture distributions.

Nordberg, W.↗
NASA NTRS1975

NASA Earth Resources Survey Symposium. Volume 1-A: Agriculture, environment

A number of papers dealing with the practical application of imagery obtained from remote sensors on LANDSAT satellites, the Skylab Earth resources experiment package, and aircraft to problems in agriculture and the environment were presented. Some of the more important topics that were covered included: range management and resources, environmental monitoring and management, crop growth and inventory, land management, multispectral band scanners, forest management, mapping, marshlands, strip mining, water quality and pollution, ecology.

Source record↗
NASA NTRS2020

The bioclimatic extent and pattern of the cold edge of the boreal forest: the circumpolar taiga-tundra ecotone

Current configurations of forest structure at the cold edge of the boreal may help understand the future of ecosystem functioning in high northern latitudes. The circumpolar biome boundary at the boreal (taiga) forest and tundra interface is an ecological transition zone (taiga-tundra ecotone; TTE) experiencing changes that affect its forest structure. We accounted for the TTE's horizontal forest structure with an estimate of its extent and pattern as represented by tree canopy cover (TCC). We quantified TCC patterns with an algorithm that describes its spatial gradient, and summarized landscape patterns of structure to represent heterogeneity, capturing abrupt, diffuse, and uniform forest at mesoscales. We used these landscape patterns to constrain the spatial extent of sparse and open canopy forest, and non-forest (forest-adjacent) edge that defines the TTE extent. The resulting map of the TTE extent is based on forest structure spatial patterns resolved at 30 m, highlights structural variability across landscapes, and helps distinguish tundra from boreal domains. We classified 14 594 landscapes as those associated with the TTE within a circumpolar bioclimatic envelope (11.575 million km2), where 44.83% of the area of these landscapes were forest and non-forest edge, yet 36.43% contributed to the TTE extent. We report the overall extent of the TTE (3.032 million km2) across North America and Greenland (53%), and Eurasia (47%), where 0.697 million km2 is non-forest edge, 0.549 million km2 is sparse forest, and 1.787 million km2 is open canopy forest. Diffuse forest landscapes dominate the TTE (79%), and abrupt landscapes (~19%) indicate portions of the TTE where sparse forest and non-forest edge are the prevailing structural patterns. This account of the TTE quantifies the area of the cold edge of the boreal forest where previous global estimates show high discrepancies, and can help target monitoring and prediction of circumpolar dynamics.

Paul M Montesano↗
NASA NTRS2022

The 2019 Raikoke volcanic eruption -Part 2: Particle-phase dispersion and concurrent wildfire smoke emissions

Between 27 June and 14 July 2019 aerosol layers were observed by the United Kingdom (UK) Raman lidar network in the upper troposphere and lower stratosphere. The arrival of these aerosol layers in late June caused some concern within the London Volcanic Ash Advisory Centre (VAAC) as according to dispersion simulations the volcanic plume from the 21 June 2019 eruption of Raikoke was not expected over the UK until early July. Using dispersion simulations from the Met Office Numerical Atmospheric-dispersion Modelling Environment (NAME), and supporting evidence from satellite and in situ aircraft observations, we show that the early arrival of the stratospheric layers was not due to aerosols from the explosive eruption of the Raikoke volcano but due to biomass burning smoke aerosols associated with intense forest fires in Alberta, Canada, that occurred 4 d prior to the Raikoke eruption. We use the observations and model simulations to describe the dispersion of both the volcanic and forest fire aerosol clouds and estimate that the initial Raikoke ash aerosol cloud contained around 15 Tg of volcanic ash and that the forest fires produced around 0.2 Tg of biomass burning aerosol. The operational monitoring of volcanic aerosol clouds is a vital capability in terms of aviation safety and the synergy of NAME dispersion simulations, and lidar data with depolarising capabilities allowed scientists at the Met Office to interpret the various aerosol layers over the UK and attribute the material to their sources. The use of NAME allowed the identification of the observed stratospheric layers that reached the UK on 27 June as biomass burning aerosol, characterised by a particle linear depolarisation ratio of 9 %, whereas with the lidar alone the latter could have been identified as the early arrival of a volcanic ash–sulfate mixed aerosol cloud. In the case under study, given the low concentration estimates, the exact identification of the aerosol layers would have made little substantive difference to the decision-making process within the London VAAC. However, our work shows how the use of dispersion modelling together with multiple observation sources enabled us to create a more complete description of atmospheric aerosol loading.

Martin J Osborne↗
NASA NTRS1993

Recent advances in radar remote sensing of forest

On a global scale, forests represent most of the terrestrial standing biomass (80 to 90 percent). Thus, natural and anthropogenic change in forest covers can have major impacts not only on local ecosystems but also on global hydrologic, climatic, and biogeochemical cycles that involve exchange of energy, water, carbon, and other elements between the earth and atmosphere. Quantitative information on the state and dynamics of forest ecosystems and their interactions with the global cycles appear necessary to understand how the earth works as a natural system. The information required includes the lateral and vertical distribution of forest cover, the estimates of standing biomass (woody and foliar volume), the phenological and environmental variations and disturbances (clearcutting, fires, flood), and the longer term variations following deforestation (regeneration, successional stages). To this end, seasonal, annual, and decadal information is necessary in order to separate the long term effects in the global ecosystem from short term seasonal and interannual variations. Optical remote sensing has been used until now to study the forest cover at local, regional, and global scales. Radar remote sensing, which provides recent SAR data from space on a regular basis, represents an unique means of consistently monitoring different time scales, at all latitudes and in any atmospheric conditions. Also, SAR data have shown the potential to detect several forest parameters that cannot be inferred from optical data. The differences--and complementarity--lie in the penetration capabilities of SAR data and their sensitivity to dielectric and geometric properties of the canopy volume, whereas optical data are sensitive to the chemical composition of the external foliar layer of the vegetation canopy.

Letoan, Thuy↗
NASA NTRS2000

Archaeological and Environmental Research of the Peten, Guatemala, Using Remote Sensing/GIS Research

The Peten, northern Guatemala, was once inhabited by a population of several million Maya before their collapse in the 9th century AD. Although the seventh and eight centuries were a time of crowning glory for millions of Maya; by 930 A.D. only a few scattered houses remained. What is known, is that at the time of their collapse, the Maya had cut down most of their trees. After centuries of regeneration the Peten now represent the largest remaining tropical forest in Central America but is experiencing rapid deforestation in the wake of an invasion of settlers. The successful adaptive techniques of the indigenous population are being abandoned in favor of the destructive techniques of monoculture and cattle raising. These techniques also contribute to the destruction and looting of unrecorded archeological sites. Remote sensing and GIS analysis are being used to address issues in Maya archeology as well as monitor the effects of increasing deforestation in the area today. One thousand years ago the forests of the Peten were nearly destroyed by the ancient Maya, who, after centuries of successful adaptation, finally overused their resources. Current inhabitants are threatening to do the same thing today in a shorter time period with a lesser population. Through the use of remote sensing/GIS analysis we are attempting to answer questions about the past in order to protect the resources of the future.

Sever, Thomas L.↗
DOE OSTI2026

Comprehensive framework for assessing and optimizing existing research networks

Conservation, monitoring, and research networks, or collections of ecological research sites unified under a common mission of data collection or a research mission, are essential infrastructure for understanding large landscapes. However, most networks developed opportunistically over decades rather than through systematic design, creating potential limitations in the ability to address conservation challenges across entire regions. We developed a framework to evaluate how well an existing research network represents the environmental conditions its members study and devised an approach to rank sites of priority for strategic expansion. Our approach measures performance through environmental representativeness, geographic coverage, and adequacy for scientific inference and thus optimizes limited monitoring resources to maximize scientific impact. We demonstrated this approach with the U.S. Department of Agriculture (USDA) Forest Service Experimental Forests and Ranges Network (EFRN), a 79‐site network across the United States that grew opportunistically over a century. At the national scale, the network effectively captured high‐biomass forests important for carbon cycle research; 82% of forest biomass was in well‐represented areas. Some areas in Texas, Florida, the Rocky Mountains, and the West Coast had no relevant EFRN sites, which limits the ability to make regional inferences. A fundamental challenge for the EFRN was that sites improving regional extent coverage sometimes provided minimal national benefits, which can create conflicts between local and global priorities. Adding the highest‐ranked candidate site provided a relevant site for 17% of currently poorly represented 1‐km pixel cells nationally, but regional and national site rankings varied considerably due to nested spatial inference. This framework provides quantitative tools for strategic infrastructure decision‐making, ensures that limited monitoring resources maximize conservation impact, and can be applied broadly to address the widespread challenge of optimizing conservation and monitoring networks worldwide.

additional site↗
NASA NTRS2011

The Invasive Species Forecasting System

The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these features enable a degree of decentralization and distributed ownership that have helped other types of scientific information services succeed in recent years.

Schnase, John↗
NASA NTRS1975

Factors affecting snow assessment from LANDSAT data

Problems associated with using LANDSAT as a snow monitoring satellite are studied. Data cover problems of slop hinderance in thematic mapping of snow and detection of snow in forested areas. It was concluded that if detector saturation threshold is raised and the upper spectral limit of the MSS is extended, snow extent mapping will be improved along with the likelihood of monitoring some aspects of the physical condition of snow pack.

Mcginnis, D. F., Jr.↗
NASA NTRS2021

Evaluating the success of treatments that slow spread of an invasive insect pest

BACKGROUND Treatments for the suppression and eradication of insect populations undergo substantial testing to ascertain their efficacy and safety, but the generally limited spatial and temporal scope of such studies limit knowledge of how contextual factors encountered in operational contexts shape the relative success of pest management treatments. These contextual factors potentially include ecological characteristics of the treated area, or the timing of treatments relative to pest phenology and weather events. We used an extensive database on over 1000 treatments of nascent populations of Lymantria dispar (L.) (gypsy moth) to examine how place-based and time-varying conditions shape the success of management treatments. RESULTS We found treatment success to vary across states and years, and to be highest in small treatment blocks that are isolated from other populations. In addition, treatment success tended to be lower in treatment blocks with open forest canopies, possibly owing to challenges of effectively distributing treatments in these areas. CONCLUSIONS Our findings emphasize the importance of monitoring for early detection of nascent gypsy moth colonies in order to successfully slow the spread of the invasion. Additionally, operations research should address best practices for effectively treating with patchy and open forest canopies. © 2021 Society of Chemical Industry.

Jonathan A Walter↗
DOE OSTI2024

Effects of hurricane disturbance and increased temperature on carbon cycling and storage of a Puerto Rican forest: a mechanistic investigation of above- and belowground processes (Final Technical Report)

The overall goal of the Tropical Responses for Altered Climate Experiment (TRACE) is to assess the effects of increasing temperature on tropical plant and soil carbon fluxes and storage as the forest recovers from major hurricane disturbance that occurred in September 2017. Ultimately, we aimed to reduce uncertainty and increase confidence with which tropical forests are represented in Earth System models to make more accurate global forecasts of future climate. We focused on both above- and belowground processes and explored temperature controls over critical aspects of carbon and nutrient cycling for tropical plants, soil, and microbes. TRACE is located in a wet tropical forest in the Luquillo Experimental Forest close to the USDA Forest Service Sabana Field Research Station in Luquillo, Puerto Rico. The warming treatment consists of six 4.7 m diameter plots. Three of the plots receive infrared warming and three have the same infrastructure but are not warmed (using ‘dummy’ heaters). Each plot was monitored from 2018-2023 to investigate two major questions: 1) Are there legacy effects of prior warming on forest recovery following hurricane disturbance? 2) Will the trajectory of forest recovery following disturbance be affected by warmer temperatures? Concurrent soil incubation experiments were conducted to enable more controlled mechanistic investigations of temperature response on microbial function. In sum, our goal was to use this novel climate manipulation experiment (the only of its kind in any tropical forest) and once-in-a-lifetime chance to assess how temperature and hurricane disturbance interact to affect coupled biogeochemical cycling in a tropical forest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Autonomous fabrication of tailored defect structures in 2D materials using machine learning-enabled scanning transmission electron microscopy

Materials with tailored quantum properties can be engineered from atomic-scale assembly techniques, but existing methods often lack the agility and accuracy to precisely and intelligently control the manufacturing process. Here, we demonstrate a fully autonomous approach for fabricating atomic-level defects using electron beams in scanning transmission electron microscopy (STEM) that combines advanced machine learning and automated beam control. As a proof of concept, we achieved controlled fabrication of MoS-nanowire (MoS-NW) edge structures by iterative and targeted exposure of MoS 2 monolayer to a focused electron beam to selectively eject sulfur atoms, utilizing high-angle annular dark-field (HAADF) imaging for feedback-controlled monitoring of structural evolution of defects. A machine learning framework combining a random forest model and a convolutional neural network (CNN) was developed to decode the HAADF image and accurately identify atomic positions and species. This atomic-level information was then integrated into an autonomous decision-making platform, which applied predefined fabrication strategies to instruct beam control about atomic sites to be ejected. The selected sites were subsequently exposed to a localized electron beam using an FPGA-controlled scan routine with precise control over beam positioning and duration. While the MoS-NW edge structures produced exhibit promising mechanical and electronic properties, the proposed methods to build the autonomous fabrication framework is material-agnostic and can be extended to other 2D materials for the creation of diverse defect structures and heterostructures beyond Mo S2 .

Engineering↗
DOE OSTI2025

Source Analysis of Ozone Pollution in Liaoyuan City’s Atmosphere Based on Machine Learning Models and HYSPLIT Clustering Method

Firstly, this study investigates the spatiotemporal distribution characteristics of the ozone (O 3 ) pollution in Liaoyuan City using monitoring data from 2015 to 2024. Then, three machine learning models (ML)—random forest (RF), support vector machine (SVM), and artificial neural network (ANN)—are employed to quantify the influence of meteorological and non-meteorological factors on O 3 concentrations. Finally, the HYSPLIT clustering method and CMAQ model are utilized to analyze inter-regional transport characteristics, identifying the causes of O 3 pollution. The results indicate that O 3 pollution in Liaoyuan exhibits a distinct seasonal pattern, with the highest concentrations found in spring and summer, peaking in the afternoon. Among the three ML models, the random forest model demonstrates the best predictive performance (R 2 = 0.9043). Feature importance identifies NO 2 as the primary driving factor, followed by meteorological conditions in the second quarter and land surface characteristics. Furthermore, regional transport significantly contributes to O 3 pollution, with approximately 80% of air mass trajectories in heavily polluted episodes originating from adjacent industrial areas and the sea. The combined effects of transboundary precursors and O 3 transport with local emissions and meteorological conditions further increase the O 3 pollution level. This study highlights the need to strengthen coordinated NO X and VOCs emission reductions and enhance regional joint prevention and control strategies in China.

HYSPLIT clustering↗
NASA NTRS1981

San Juan National Forest Land Management Planning Support System (LMPSS) requirements definition

The role of remote sensing data as it relates to a three-component land management planning system (geographic information, data base management, and planning model) can be understood only when user requirements are known. Personnel at the San Juan National Forest in southwestern Colorado were interviewed to determine data needs for managing and monitoring timber, rangelands, wildlife, fisheries, soils, water, geology and recreation facilities. While all the information required for land management planning cannot be obtained using remote sensing techniques, valuable information can be provided for the geographic information system. A wide range of sensors such as small and large format cameras, synthetic aperture radar, and LANDSAT data should be utilized. Because of the detail and accuracy required, high altitude color infrared photography should serve as the baseline data base and be supplemented and updated with data from the other sensors.

Werth, L. F.↗
NASA NTRS1990

Forest Fire Mapping

The Fire Logistics Airborne Mapping Equipment (FLAME) system, mounted in a twin-engine and airplane operated by the U.S. Forest Service (USFS) of the U.S. Department of Agriculture (USDA), is an airborne instrument for detecting and pinpointing forest fires that might escape ground detection. The FLAME equipment rack includes the operator interface, a video monitor, the system's control panel and film output. FLAME's fire detection sensor is an infrared line scanner system that identifies fire boundaries. Sensor's information is correlated with the aircraft's position and altitude at the time the infrared imagery is acquired to fix the fire's location on a map. System can be sent to a fire locale anywhere in the U.S. at the request of a regional forester. USFS felt a need for a more advanced system to deliver timely fire information to fire management personnel in the decade of the 1990s. The Jet Propulsion Laboratory (JPL) conducted a study, jointly sponsored by NASA and USDA, on what advanced technologies might be employed to produce an end-to-end thermal infrared fire detection and mapping system. That led to initiation of the Firefly system, currently in development at JPL and targeted for operational service beginning in 1992. Firefly will employ satellite-reference position fixing and provide performance superior to FLAME.

Source record↗