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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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62 records · Page 4

The MELISSA pilot plant facility as as integration test-bed for advanced life support systems

The different advances in the Micro Ecological Life Support System Alternative project (MELISSA), fostered and coordinated by the European Space Agency, as well as in other associated technologies, are integrated and demonstrated in the MELISSA Pilot Plant laboratory. During the first period of operation, the definition of the different compartments at an individual basis has been achieved, and the complete facility is being re-designed to face a new period of integration of all these compartments. The final objective is to demonstrate the potentiality of biological systems such as MELISSA as life support systems. The facility will also serve as a test bed to study the robustness and stability of the continuous operation of a complex biological system. This includes testing of the associated instrumentation and control for a safe operation, characterization of the chemical and microbial safety of the system, as well as tracking the genetic stability of the microbial strains used. The new period is envisaged as a contribution to the further development of more complete biological life support systems for long-term manned missions, that should be better defined from the knowledge to be gained from this integration phase. This contribution summarizes the current status of the Pilot Plant and the planned steps for the new period. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Waste Management/instrumentation/methods↗

Okefenokee Water Resources: Using Earth Observations to Assess Hydrologic Changes and Wildfire Risk in the Okefenokee Swamp

The Okefenokee Swamp is a vital ecosystem known for its protection of biodiversity, peatland carbon sinks, and recreational and economic opportunities for local residents. The swamp has experienced several wildfires since the 1990s, and new development along the borders of Okefenokee National Wildlife Refuge (ONWR) threatens to alter hydrologic activity and increase fire frequency. NASA DEVELOP partnered with staff at the ONWR to determine the feasibility of using satellite imagery to assess wildfire risk and map changes in vegetation cover. Using data from NASA satellites Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI), Soil Moisture Active Passive (SMAP) data from the USDA’s Crop Condition and Soil Moisture Analytics Tool (Crop-CASMA), European Space Agency (ESA) Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR), and Sentinel-2 Multispectral Instrument (MSI), the DEVELOP team assessed the relationship between hydrologic change, vegetation cover, and wildfire risk in the swamp. Results showed that the southern portion of ONWR has been burned the most since 1990 and has greater water stability than other areas of the refuge. The team also found that the largest pockets of mature forests remain in the northernmost regions. Soil moisture anomaly readings may serve as an indicator of fire conditions. The team used these results to create a vegetation map, a swamp water visibility time series map, a historical wildfire correlation analysis, and a methodology tutorial. These products will assist the ONWR in making informed management decisions about the future of the Okefenokee Swamp.

Brianne Kendall↗

Spatio-Temporal Patterns of Optimal Landsat Data for Burn Severity Index Calculations: Implications for High Northern Latitudes Wildfire Research

Satellite remote sensing has been widely used for the evaluation of wildfire burn severity in various ecosystems. While a variety of remote sensing-based burn severity indices have been developed, the Landsat-based differ-enced Normalized Burn Ratio (dNBR) presents the most widely-used approach to burn severity assessment for fire research and management. Although dNBR-based approaches have been continuously updated, including the development of the relative dNBR (RdNBR) and the Relativized Burn Ratio (RBR), one key obstacle for the reliable applications of the burn severity indices in the high northern latitudes has not been adequately addressed. Specifically, optimal Landsat image pairs are very rarely available for the calculation of the burn severity indices in certain regions of the high northern latitudes (HNL), resulting in the burn severity index outputs calculated for a large number of wildfires being considerably affected by non-fire-related factors. The suboptimal selection of image pairs may have partially contributed to the lack of consistency in the performance of the burn severity indices in the HNL regions. In this paper, we systematically evaluated the impacts of sub-optimal image pairs on signal stability through two sets of analyses conducted at different spatial scales. First, at the regional scale, we examined the burn severity indices calculated for a selection of wildfires in Alaska. Here, we demonstrate the inconsistent performance of the same index calculated based on Landsat data that are typically considered as “optimal”. In addition, we show that the calculated indices may be more prone to the negative impacts of these inconsistencies, thus leading to reduced reliability, when there is limited Landsat data availability. Second, at the continental scale, we show that certain areas in the HNL, especially Alaska during the pre-2000 era, are subject to the potentially strong negative impact associated with the limited data availability. Through systematically analyzing this issue, we hope to not only divert more attention to it but also to provide potential solutions, based on which further improvements that may be of particular importance for research on Arctic wildfires could be made.

Dong Chen↗

Evaluating MODIS Snow Products Using an Extensive Wildlife Camera Network

Snow covers a maximum of 47 million km 2 of Earth's northern hemisphere each winter and is an important component of the planet's energy balance, hydrology cycles, and ecosystems. Monitoring regional and global snow cover has increased in urgency in recent years due to warming temperatures and declines in snow cover extent. Optical satellite instruments provide large-scale observations of snow cover, but cloud cover and dense forest canopy can reduce accuracy in mapping snow cover. Remote camera networks deployed for wildlife monitoring operate below cloud cover and in forests, representing a virtually untapped source of snow cover observations to supplement satellite observations. Using images from 1,181 wildlife cameras deployed by the Norwegian Institute for Nature Research (NINA), we compared snow cover extracted from camera images to Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products during winter months of 2018–2020. Ordinal snow classifications (scale = 0–4) from cameras were closely related to normalized difference snow index (NDSI) values from the MODIS Terra Snow Cover Daily L3 Global 500m (MOD10A1) Collection 6 product (R 2 = 0.70). Tree canopy cover, the normalized difference vegetation index (NDVI), and image color mode influenced agreement between camera images and MOD10A1 NDSI values. For MOD10A1F, MOD10A1's corresponding cloud-gap filled product, agreement with cloud-gap filled values decreased from 78.5% to 56.4% in the first three days of cloudy periods and stabilized thereafter. Using our camera data as validation, we derived a threshold to create daily binary maps of snow cover from the MOD10A1 product. The threshold corresponding to snow presence was an NDSI value of 40.50, which closely matched a previously defined global binary threshold of 40 using the MOD10A2 8-day product. These analyses demonstrate the utility of camera trap networks for validation of snow cover products from satellite remote sensing, as well as their potential to identify sources of inaccuracy.

Validation↗

Urban Surface Radiative Energy Budgets Determined Using Aircraft Scanner Data

It is estimated that by the year 2025, 80% of the world's population will live in cities. The extent of these urban areas across the world can be seen in an image of city lights from the Defense Meteorological Satellite Program. In many areas of North America and Europe, it is difficult to separate individual cities because of the dramatic growth and sprawl of urbanized areas. This conversion of the natural landscape vegetation into man-made urban structures such as roads and buildings drastically alter the regional surface energy budgets, hydrology, precipitation patterns, and meteorology. One of the earliest recognized and measured phenomena of urbanization is the urban heat island (UHI) which was reported as early as 1833 for London and 1862 for Paris. The urban heat island results from the energy that is absorbed by man-made materials during the day and is released at night resulting in the heating of the air within the urban area. The magnitude of the air temperature difference between the urban and surrounding countryside is highly dependent on the structure of the urban area, amount of solar immolation received during the day, and atmospheric conditions during the night. These night time air temperature differences can be in the range of 2 to 5 C. or greater. Although day time air temperature differences between urban areas and the countryside exists during the day, atmospheric mixing and stability reduce the magnitude. This phenomena is not limited to large urban areas, but also occurs in smaller metropolitan areas. The UHI has significant impacts on the urban air quality, meteorology, energy use, and human health. The UPI can be mitigated through increasing the amount of vegetation and modification of urban surfaces using high albedo materials for roofs and paved surfaces. To understand why the urban heat island phenomenon exists it is useful to define the surface in terms of the surface energy budget. Surface temperature and albedo is a major component of the surface energy budget. Knowledge of it is important in any attempt to describe the radiative and mass fluxes which occur at the surface. Use of energy terms in modeling surface energy budgets allows the direct comparison of various land surfaces encountered in a urban landscape, from vegetated (forest and herbaceous) to non-vegetated (bare soil, roads, and buildings). These terms are also easily measured using remote sensing from aircraft or satellite platforms allowing one to examine the spacial variability. The partitioning of energy budget terms depends on the surface type. In natural landscapes, the partitioning is dependent on canopy biomass, leaf area index, aerodynamic roughness, and moisture status, all of which are influenced by the development stage of the ecosystem. In urban landscapes, coverage by man-made materials substantially alters the surface face energy budget. The remotely sensed data obtained from aircraft and satellites, when properly calibrated allows the measurement of important terms in the radiative surface energy budget a urban landscape scale.

Luvall, Jeffrey C.↗

Mapping Temperate Forest Phenology Using Tower, UAV, and Ground-Based Sensors

Phenology is a distinct marker of the impacts of climate change on ecosystems. Accordingly, monitoring the spatiotemporal patterns of vegetation phenology is important to understand the changing Earth system. A wide range of sensors have been used to monitor vegetation phenology, including digital cameras with different viewing geometries mounted on various types of platforms. Sensor perspective, view-angle, and resolution can potentially impact estimates of phenology. We compared three different methods of remotely sensing vegetation phenology—an unoccupied aerial vehicle (UAV)-based, downward-facing RGB camera, a below-canopy, upward-facing hemispherical camera with blue (B), green (G), and near-infrared (NIR) bands, and a tower-based RGB PhenoCam, positioned at an oblique angle to the canopy—to estimate spring phenological transition towards canopy closure in a mixed-species temperate forest in central Virginia, USA. Our study had two objectives: (1) to compare the above- and below-canopy inference of canopy greenness (using green chromatic coordinate and normalized difference vegetation index) and canopy structural attributes (leaf area and gap fraction) by matching below-canopy hemispherical photos with high spatial resolution (0.03 m) UAV imagery, to find the appropriate spatial coverage and resolution for comparison; (2) to compare how UAV, ground-based, and tower-based imagery performed in estimating the timing of the spring phenological transition. We found that a spatial buffer of 20 m radius for UAV imagery is most closely comparable to below-canopy imagery in this system. Sensors and platforms agree within +/− 5 days of when canopy greenness stabilizes from the spring phenophase into the growing season. We show that pairing UAV imagery with tower-based observation platforms and plot-based observations for phenological studies (e.g., long-term monitoring, existing research networks, and permanent plots) has the potential to scale plot-based forest structural measures via UAV imagery, constrain uncertainty estimates around phenophases, and more robustly assess site heterogeneity.

Jeff W. Atkins↗

Using NASA Earth Observations to Identify Wildfire Impacts on Hydrologic Functions and Recovery in the Gila National Forest

Wildfires can dramatically influence both abiotic and biotic components of a landscape, including soil stability and chemistry; vegetation health, density, and composition; and water flow and quality. In addition to the immediate hazards posed by wildfires, subsequent hazards such as flooding and debris flow can impact the area. In New Mexico’s Gila National Forest, wildfire events have occurred with increasing frequency and severity over recent years, notably including the Whitewater Baldy Complex Fire (2012) and Silver Fire (2013), which burned over 290,000 acres and 138,698 acres, respectively, according to the Burned Area Emergency Response Team Executive Summary reports. Following a significant wildfire, land and resource management decisions are made, including when and where to focus vegetation and stream restoration efforts. This research is the result of a collaboration between the NASA DEVELOP National Program and the US Forest Service, which aimed to utilize NASA Earth observations to help inform those critical land management decisions. The project had two main objectives: 1) assess the efficacy of post-fire vegetation restoration efforts and 2) analyze the impact of burn events on the hydrology at the watershed-scale. To accomplish this first goal, data from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) were used to study the vegetation health over time of treated and non-treated burn areas. To accomplish the latter, various aspects of stream behavior were examined in relation to burn events, including the runoff coefficient and “flashiness” of streams based on USGS stream gauge data and Integrated Multi-satelllite Retrievals for GPM (IMERG) precipitation data. This will allow land managers to better understand the complex ecological relationship between the cascading effects after wildfire and the greater forest ecosystem.

Madeline Allen↗

Highly ordered vertical structure of Synechococcus populations within the one-millimeter-thick photic zone of a hot spring cyanobacterial mat

A variety of contemporary techniques were used to investigate the vertical distribution of thermophilic unicellular cyanobacteria, Synechococcus spp., and their activity within the upper 1-mm-thick photic zone of the mat community found in an alkaline siliceous hot spring in Yellowstone National Park in Wyoming. Detailed measurements were made over a diel cycle at a 61 degrees C site. Net oxygenic photosynthesis measured with oxygen microelectrodes was highest within the uppermost 100- to 200-microm-thick layer until midmorning, but as the day progressed, the peak of net activity shifted to deeper layers, stabilizing at a depth of 300 microm from midday throughout the afternoon. Examination of vertical thin sections by bright-field and autofluorescence microscopy revealed the existence of different populations of Synechococcus which form discrete bands at different vertical positions. Denaturing gradient gel electrophoresis analysis of PCR-amplified 16S rRNA gene segments from horizontal cryosections obtained at 100-microm-thick vertical intervals also suggested vertical stratification of cyanobacterial, green sulfur bacterium-like, and green nonsulfur bacterium-like populations. There was no evidence of diel migration. However, image analysis of vertical thin sections revealed the presence of a narrow band of rod-shaped Synechococcus cells in which the cells assumed an upright position. These upright cells, located 400 to 800 microm below the surface, were observed only in mat samples obtained around noon. In mat samples obtained at other time points, the cells were randomly oriented throughout the mat. These combined observations reveal the existence of a highly ordered structure within the very thin photic zone of this hot spring microbial mat, consisting of morphologically similar Synechococcus populations that are likely to be differentially adapted, some co-occurring with green sulfur bacterium-like populations, and all overlying green nonsulfur bacterium-like populations.

Non-NASA Center↗