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We have developed a model for production of ba-sin ejecta deposits to address provenances of materials collected at the Apollo and Luna landing sites and for consideration in interpreting remote sensing data.
We have developed a model for production of basin ejecta deposits to address provenances of materials collected at the Apollo and Luna landing sites and for consideration in interpreting remote sensing data.
The Small Business Innovation Research (SBIR) Program increases opportunities for small businesses to participate in research and development (R&D), increases employment, and improves U.S. competitiveness. Specifically the program stimulates U.S. technological innovation by using small businesses to meet federal R&D needs, increasing private-sector commercialization of innovations derived from federal R&D, and fostering and encouraging the participation of socially disadvantaged businesses. In 2000, the Small Business Technology Transfer (STTR) Program extended and strengthened the SBIR Program, increasing its emphasis on pursuing commercial applications by awarding contracts to small business concerns for cooperative R&D with a nonprofit research institution. Modeled after the SBIR Program, STTR is nevertheless a separately funded activity. Technologies that have resulted from the Johnson Space Center SBIR STTR Program include: a device for regenerating iodinated resin beds; laser-assisted in-situ keratomileusis or LASIK; a miniature physiological monitoring device capable of collecting and analyzing a multitude of real-time signals to transmit medical data from remote locations to medical centers for diagnosis and intervention; a new thermal management system for fibers and fabrics giving rise to new line of garments and thermal-enhancing environments; and a highly electropositive material that attracts and retains electronegative particles in water.
The goals of the project are to provide information from satellite remote sensing to support numeric nutrient criteria development and to determine data processing methods and data quality requirements to support nutrient criteria development and implementation. The approach is to identify water quality indicators that are used by decision makers to assess water quality and that are related to optical properties of the water; to develop remotely sensed data products based on algorithms relating remote sensing imagery to field-based observations of indicator values; to develop methods to assess estuarine water quality, including trends, spatial and temporal variability, and seasonality; and to develop tools to assist in the development and implementation of estuarine and coastal nutrient criteria. Additional slides present process, criteria development, typical data sources and analyses for criteria process, the power of remote sensing data for the process, examples from Pensacola Bay, spatial and temporal variability, pixel matchups, remote sensing validation, remote sensing in coastal waters, requirements for remotely sensed data products, and needs assessment. An additional presentation examines group engagement and information collection. Topics include needs assessment purpose and objectives, understanding water quality decision making, determining information requirements, and next steps.
The objective of this work was to identify and estimate complexity and risks associated with the development and testing of new low-cost medium-scale X-plane aircraft primarily focused on air transport operations. Piloting modes that were evaluated for this task were manned, remotely piloted, and unmanned flight research programs. This analysis was conducted early in the data collection period for X-plane concept vehicles before preliminary designs were complete. Over 50 different aircraft and system topics were used to evaluate the three piloting control modes. Expert group evaluations from a diverse set of pilots, engineers, and other experts at Aeronautics Research Mission Directorate centers within the National Aeronautics and Space Administration provided qualitative reasoning on the many issues surrounding the decisions regarding piloting modes. The group evaluations were numerically rated to evaluate each topic quantitatively and were used to provide independent criteria for vehicle complexity and risk. An Edwards Air Force Base instruction document was identified that emerged as a source of the effects found in our qualitative and quantitative data. The study showed that a manned aircraft was the best choice to align with test activities for transport aircraft flight research from a low-complexity and low-risk perspective. The study concluded that a manned aircraft option would minimize the risk and complexity to improve flight-test efficiency and bound the cost of the flight-test portion of the program. Several key findings and discriminators between the three modes are discussed in detail.
The objective of this work was to identify and estimate complexity and risks associated with the development and testing of new low-cost medium-scale X-plane aircraft primarily focused on air transport operations. Piloting modes that were evaluated for this task were manned, remotely piloted, and unmanned flight research programs. This analysis was conducted early in the data collection period for X-plane concept vehicles before preliminary designs were complete. Over 50 different aircraft and system topics were used to evaluate the three piloting control modes. Expert group evaluations from a diverse set of pilots, engineers, and other experts at Aeronautics Research Mission Directorate centers within the National Aeronautics and Space Administration provided qualitative reasoning on the many issues surrounding the decisions regarding piloting modes. The group evaluations were numerically rated to evaluate each topic quantitatively and were used to provide independent criteria for vehicle complexity and risk. An Edwards Air Force Base instruction document was identified that emerged as a source of the effects found in our qualitative and quantitative data. The study showed that a manned aircraft was the best choice to align with test activities for transport aircraft flight research from a low-complexity and low-risk perspective. The study concluded that a manned aircraft option would minimize the risk and complexity to improve flight-test efficiency and bound the cost of the flight-test portion of the program. Several key findings and discriminators between the three modes are discussed in detail.
Drought can cause immense agricultural and ecological damage resulting in high mitigation and compensation costs. Climate variability in future decades is expected to cause severe drought conditions and threaten necessary water resources. Stakeholders seek to implement effective drought assessments in preparation for potential economic and environmental damage invoked by drought. Although in-situ measurements are accurate, the current infrastructure is spatially limited and costly to maintain. A framework was created to compare modeled, satellite and in-situ data in drought monitoring. Here we show that the comparison of in-situ and remotely sensed soil moisture (SM) measurements can increase the spatiotemporal range of SM assessments. Data collected between 2003 and 2021 by NASA’s SPoRT Land Information System (SPoRT-LIS) and Soil Moisture Active Passive (SMAP) mission were standardized and compared with in-situ data provided through the Illinois Climate Network (WARM). Statistical analysis results including the Pearson correlation coefficient (r), root mean squared error, mean absolute error and others were calculated to compare the WARM measurements to the SMAP and SPoRT-LIS products. Results indicate that both satellite products demonstrate seasonally variable bias that is not present in the in-situ measurements. Bias was highest in the winter months and lowest in the late summer and early fall months in both satellite datasets. Overall, WARM-SPoRT comparisons resulted in lower seasonal variability. However, on average, the SMAP comparison demonstrated higher correlation values and lower error values. The WARM-SMAP average correlation (r) was 0.61 compared to the WARM-SPoRT average correlation (r) value of 0.54. Average mean absolute error values calculated for the SMAP and SPoRT comparisons were 0.07 and 0.08 percent soil moisture by volume, respectively. These analyses suggest integrating in-situ measurements and those provided by NASA Earth observations can be utilized in a multi-faceted SM evaluation, a valuable contribution to drought monitoring and water resource decision making.
Devices, systems, and techniques for data collecting network such as wireless sensors are disclosed. A described technique includes detecting one or more remote nodes included in the wireless sensor network using a local power level that controls a radio range of the local node. The technique includes transmitting a local outdegree. The local outdegree can be based on a quantity of the one or more remote nodes. The technique includes receiving one or more remote outdegrees from the one or more remote nodes. The technique includes determining a local node type of the local node based on detecting a node type of the one or more remote nodes, using the one or more remote outdegrees, and using the local outdegree. The technique includes adjusting characteristics, including an energy usage characteristic and a data compression characteristic, of the wireless sensor network by selectively modifying the local power level and selectively changing the local node type.
The present conference discusses such topics as density crossovers in lunar picrites, the geology of the Cassini impact basin, Mars, nanobacteria in carbonates, the properties of shocked aerogels, a chemical model of Comet Halley, lunar mascons, the impact evolution of icy regoliths, the geology of the Venera 8 landing site, the photogeologic mapping of northern Venus, HST observations of Mars, observational constraints on the rotational dynamics of Mars, and primordial magnetic field measurements from the moon. Also discussed are models of the S2 fluorescence spectra of comets, Martian crater ejecta, the heights of Venusian steep-sided domes, cloud-climate interactions on Venus, the Humorum basin geology from Clementine data, an early Amazonian lake in the Gale crater of Mars, nebular fractionations and Mn-Cr systematics, the Rock Chipper planetary surface sample collection, Mariner 10 stereo images of Mercury, remote and local stresses and Calderas on Mars, the electrostatic charging of saltating particles, SO2 detected on Callisto, the Mars Explorer Planetary Data System, an assessment of explosive venting on Europa, the sequential faulting history of the Mars Valles Marineris, a search for Martian sediments, the composition and internal structure of Europa, long-term and 'diurnal' tidal stresses on Europa, and episodic greenhouse climates on Mars.
The International Space Station (ISS) has been acquiring Earth imagery since 2000, primarily in the form of astronaut photography using hand-held film and digital cameras. Recent additions of more sophisticated multispectral and hyperspectral sensor systems have expanded both the capabilities and relevance of the ISS to basic research, applied Earth science, and development of new sensor technologies. Funding opportunities established within NASA, the US National Laboratories and the international partner organizations have generated instrument proposals that will further enhance these capabilities. With both internal and external sensor location options, and the availability of both automated and human-tended operational environments, the ISS is a unique platform within the constellation of Earth-observing satellites currently in orbit. Current progress and challenges associated with development of ISS terrestrial remote sensing capabilities in the area of disaster response and support of relief efforts will be presented. The ISS orbit allows for imaging of the Earth's surface at varying times of day and night, providing opportunities for data collection over approximately 95% of the populated regions. These opportunities are distinct from--yet augment--the data collection windows for the majority of sensors on polar-orbiting satellites. In addition to this potential for "being in the right place at the right time" to collect critical information on an evolving disaster, the presence of a human crew also allows for immediate recognition of an event from orbit, notification of relevant organizations on the ground, and re-tasking of available remote sensing resources to support humanitarian response and relief efforts. Challenges to establishing an integrated response capability are both technical (coordination of sensor targeting and data collection, rapid downlink and posting of data to a central accessible hub, timely generation and distribution of relevant data products) and operational (notification and engagement of sensor support teams, international partner agency sanction of astronaut support activities). To better collaborate on common issues and strengthen applications, including using the data to support disaster response, we established an ISS Program Science Forum Working Group for Earth Observations comprised of representatives from the international partner agencies. This international forum welcomes input and support from relevant United Nations task groups regarding our disaster response and humanitarian aid to enable development of the ISS capabilities in this area for greatest value to the international community.
A recent study that evaluated issues associated with remote interaction with an autonomous vehicle within the framework of grounding found that missing contextual information led to uncertainty in the interpretation of collected data, and so introduced errors into the command logic of the vehicle. As the vehicles became more autonomous through the activation of additional capabilities, more errors were made. This is an inefficient use of the platform, since the behavior of remotely located autonomous vehicles didn't coincide with the "mental models" of human operators. One of the conclusions of the study was that there should be a way for the autonomous vehicles to describe what action they choose and why. Robotic agents with enough self-awareness to dynamically adjust the information conveyed back to the Operations Center based on a detail level component analysis of requests could provide this description capability. One way to accomplish this is to map the behavior base of the robot into a formal mathematical framework called a cost-calculus. A cost-calculus uses composition operators to build up sequences of behaviors that can then be compared to what is observed using well-known inference mechanisms.
To adapt successfully to the major changes - climate, environment, economic, social and industrial - which have taken place across the Arctic. in recent years, indigenous communities such as reindeer herders must become increasingly empowered with the best available technologies to add to their storehouse of traditional knowledge. Remotely-sensed data and observations are providing increased capabilities for monitoring, risk mapping, and surveillance of parameters critical to the characterization of pasture quality and migratory routes, such as vegetation distribution, snow cover, infrastructure development, and pasture damages due to fires. This paper describes a series of remote sensing capabilities, which are useful to reindeer husbandry, and gives the results of the first year of a project, "Reindeer Mapper", which is a remote sensing and GIs-based system to bring together space technologies with indigenous knowledge for sustainable reindeer husbandry in the Russian Arctic. In this project, reindeer herders and scientists are joining together to utilize technologies to create a system for collecting and sharing space-based and indigenous knowledge in the Russian Arctic. The "Reindeer Mapper" system will help make technologies more readily available to the herder community for observing, data collection and analysis, monitoring, sharing, communications, and dissemination of information - to be integrated with traditional, local knowledge. This paper describes some of the technologies which comprise the system including an intranet system to enable to the team members to work together and share information electronically, remote sensing data for monitoring environmental parameters important to reindeer husbandry (e.g., SAR, Landsat, AVHRR, MODIS), indigenous knowledge about important environmental parameters, acquisition of ground- based measurements, and the integration of all useful data sets for more informed decision-making.
Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the boreal domain. ArcticDEM is a collection of high-resolution (2 m) space-borne stereogrammetric digital surface models (DSM) covering the entire land area north of 60° of latitude. The free-availability of ArcticDEM data offers new possibilities for aboveground biomass mapping (AGB) across boreal forests, and thus it is necessary to evaluate the potential for these data to map AGB over alternative open-data sources (i.e., Sentinel-2). This study was performed over the entire land area of Norway north of 60° of latitude, and the Norwegian national forest inventory (NFI) was used as a source of field data composed of accurately geolocated field plots (n=7710) systematically distributed across the study area. Separate random forest models were fitted using NFI data, and corresponding remotely sensed data consisting of either: i) a canopy height model (ArcticCHM) obtained by subtracting a high-quality digital terrain model (DTM) from the ArcticDEM DSM height values, ii) Sentinel-2 (S2), or iii) a combination of the two (ArcticCHM+S2). Furthermore, we assessed the effect of the forest- and terrain-specific factors on the models’ predictive accuracy. The best model (,i.e., ArcticCHM+S2) explained nearly 60% of the variance of the training set, which translated in the largest accuracy in terms of root mean square error (RMSE=41.4 t/ha). This result highlights the synergy between 3D and multispectral data in AGB modelling. Furthermore, this study showed that despite the importance of ArcticCHM variables, the S2 model performed slightly better than ArcticCHM model. This finding highlights some of the limitations of ArcticDEM, which, despite the unprecedented spatial resolution, is highly heterogeneous due to the blending of multiple acquisitions across different years and seasons. We found that both forest- and terrain-specific characteristics affected the uncertainty of the ArcticCHM+S2 model and concluded that the combined use of ArcticCHM and Sentinel-2 represents a viable solution for AGB mapping across boreal forests. The synergy between the two data sources allowed for a reduction of the saturation effects typical of multispectral data while ensuring the spatial consistency in the output predictions due to the removal of artifacts and data voids present in ArcticCHM data. While the main contribution of this study is to provide the first evidence of the best-case-scenario (i.e., availability of accurate terrain models) that ArcticDEM data can provide for large-scale AGB modelling, it remains critically important for other studies to investigate how ArcticDEM may be used in areas where no DTMs are available as is the case for large portions of the boreal zone.
GIS technology and ground reference data often play vital roles in assessing land cover maps derived from remotely sensed data. This poster illustrates these roles, using results from a study done in Northeast Yellowstone National Park. This area holds many forest, range, and wetland cover types of interest to park managers. Several recent studies have focused on this locale, including the NASA Earth Observations Commercial Applications Program (EOCAP) hyperspectral project performed by Yellowstone Ecosystems Studies (YES) on riparian and in-stream habitat mapping. This poster regards a spin-off to the EOCAP project in which YES and NASA's Earth Science Applications Directorate explored the potential for synergistic use of hyperspecral, synthetic aperture radar, and multiband thermal imagery in mapping land cover types. The project included development of a ground reference GIS for site-specific data needed to evaluate maps from remotely sensed imagery. Field survey data included reflectance of plant communities, native and exotic plant species, and forest health conditions. Researchers also collected GPS points, annotated aerial photographs, and took hand held photographs of reference sites. The use of ESRI, ERDAS, and ENVI software enabled reference data entry into a GIS for comparision to georeferenced imagery and thematic maps. The GIS-based ground reference data layers supported development and assessment of multiple maps from remotely sensed data sets acquired over the study area.
Multilevel remote-sensing techniques were combined to provide land resource and land-use information for rural development planning in Arusha Region, Tanzania. Enhanced Landsat imagery, supplemented by low-level aerial survey data, slope angle data from topographic sheets, and existing reports on vegetation and soil conditions, was used jointly by image analysts and district-level land-management officials to divide the region's six districts into land-planning units. District-planning officials selected a number of these land-planning units for priority planning and development activities. For the priority areas, natural color aerial photographs provided detailed information for land-use planning discussions between district officials and villagers. Consideration of the efficiency of this remote sensing approach leads to general recommendations for similar applications. The technology and timing of data collection and interpretation activities should allow maximum participation by intended users of the information.
Electronic system collects, manipulates, and displays in real time results of manipulation of streams of data transmitted from remote scientific instrumentation. Interface circuit shifts data-and-clock signal from differential logic levels of multiplexer to single-ended logic levels of computer. System accommodates nonstandard data-transmission protocol. Software useful in applications where Macintosh computers used in real-time display and recording of data.
Earth's 4.5 billion year history is a study in change. Natural geological forces have been rearranging the surface features and climatic conditions of our planet since its beginning. There is scientific evidence that some of these natural changes have not only led to mass extinctions of species (e.g., dinosaurs), but have also severely impacted human civilizations. For instance, there is evidence that a relatively sudden climate change caused a 300-year drought that contributed to the downfall of Akkadia, one of the most powerful empires in the Middle-East region around 2200 BC. More recently, the "little ice age" from 1200-1400 AD forced the Vikings to abandon Greenland when temperatures there dropped by about 1.5 C, rendering it too difficult to grow enough crops to sustain the population. Today, there is compelling scientific evidence that human activities have attained the magnitude of a geological force and are speeding up the rate of global change. For example, carbon dioxide levels have risen 30 percent since the industrial revolution and about 40 percent of the world's land surface has been transformed by humans. We don't understand the cause-and-effect relationships among Earth's land, ocean, and atmosphere well enough to predict what, if any, impacts these rapid changes will have on future climate conditions. We need to make many measurements all over the world, over a long period of time, in order to assemble the information needed to construct accurate computer models that will enable us to forecast climate change. In 1988, the Earth System Sciences Committee, sponsored by NASA, issued a report calling for an integrated, long-term strategy for measuring the vital signs of Earth's climate system. The report urged that the measurements must all be intimately coupled with focused process studies, they must facilitate development of Earth system models, and they must be stored in an information system that ensures open access to consistent, long-term data. This committee emphasized that the only feasible way to collect these consistent, long-term data is through the use of space-based Earth "remote sensors" (instruments that can measure from a distance things like temperature).
Omni Technologies, Inc. worked with Stennis Space Center to develop the FOTR-125, a redundant fiber-optic transceiver for remote transmission of high-speed digital data. The 125-megabit-per-second transceiver can collect data for up to 25 kilometers, much longer than standard coaxial cable, which is limited to 50 meters. The Research Triangle Institute assisted in determining the commercial marketplace for the technology.