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At least 595 records · Page 33

Seasat-A and the commercial ocean community

The Seasat-A program has been initiated as a 'proof-of-concept' mission to evaluate the effectiveness of remotely sensing oceanology and related meteorological phenomena from a satellite platform in space utilizing sensors developed on previous space and aircraft test programs. The sensors include three active microwave sensors; a radar altimeter, a windfield scatterometer, and a synthetic aperture radar. A passive scanning multifrequency microwave radiometer, visual and infrared radiometer are also included. All weather, day-night measurements of sea surface temperature, surface wind speed/direction and sea state and directional wave spectra will be made. Two key programs are planned for data utilization with users during the mission. Foremost is a program with the commercial ocean community to test the utility of Seasat-A data and to begin the transfer of ocean remote sensing technology to the civil sector. A second program is a solicitation of investigations, led by NOAA, to involve the ocean science community in a series of scientific investigations.

Montgomery, D. R.↗

Assessment of the use of space technology in the monitoring of oil spills and ocean pollution: Technical volume. Executive summary

The potential of space systems and technology for detecting and monitoring ocean oil spills and waste pollution was assessed as well as the impact of this application on communication and data handling systems. Agencies charged with responsibilities in this area were identified and their measurement requirements were ascertained in order to determine the spatial resolution needed to characterize operational and accidental discharges. Microwave and optical sensors and sensing techniques were evaluated as candidate system elements. Capabilities are described for the following: synthetic aperture radar, microwave scatterometer, passive microwave radiometer, microwave altimeter, electro-optical sensors currently used in airborne detection, existing space-based optical sensors, the thematic mapper, and the pointable optical linear array.

Alvarado, U. R.↗

Towards the Development of a Global, Satellite-Based, Terrestrial Snow Mission Planning Tool

A global, satellite-based, terrestrial snow mission planning tool is proposed to help inform experimental mission design with relevance to snow depth and snow water equivalent (SWE). The idea leverages the capabilities of NASA's Land Information System (LIS) and the Tradespace Analysis Tool for Constellations (TAT-C) to harness the information content of Earth science mission data across a suite of hypothetical sensor designs, orbital configurations, data assimilation algorithms, and optimization and uncertainty techniques, including cost estimates and risk assessments of each hypothetical permutation. One objective of the proposed observing system simulation experiment (OSSE) is to assess the complementary or perhaps contradictory information content derived from the simultaneous collection of passive microwave (radiometer), active microwave (radar), and LIDAR observations from space-based platforms. The integrated system will enable a true end-to-end OSSE that can help quantify the value of observations based on their utility towards both scientific research and applications as well as to better guide future mission design. Science and mission planning questions addressed as part of this concept include: What observational records are needed (in space and time) to maximize terrestrial snow experimental utility? How might observations be coordinated (in space and time) to maximize this utility? What is the additional utility associated with an additional observation? How can future mission costs be minimized while ensuring Science requirements are fulfilled?

Mission Desig↗

Interdisciplinary applications and interpretations of remotely sensed data

An interdisciplinary approach to use remote sensor for the inventory of natural resources is discussed. The areas under investigation are land use, determination of pollution sources and damage, and analysis of geologic structure and terrain. The geographical area of primary interest is the Susquehanna River Basin. Descriptions of the data obtained by aerial cameras, multiband cameras, optical mechanical scanners, and radar are included. The Earth Resources Technology Satellite and Skylab program are examined. Interpretations of spacecraft data to show specific areas of interest are developed.

Peterson, G. W.↗

Multisensor comparison of ice concentration estimates in the marginal ice zone

Aircraft remote sensing data collected during the 1984 summer Marginal Ice Zone Experiment in the Fram Strait are used to compare ice concentration estimates derived from synthetic aperture radar (SAR) imagery, passive microwave imagery at several frequencies, aerial photography, and spectral photometer data. The comparison is carried out not only to evaluate SAR performance against more established techniques but also to investigate how ice surface conditions, imaging geometry, and choice of algorithm parameters affect estimates made by each sensor.Active and passive microwave sensor estimates of ice concentration derived using similar algorithms show an rms difference of 13 percent. Agreement between each microwave sensor and near-simultaneous aerial photography is approximately the same (14 percent). The availability of high-resolution microwave imagery makes it possible to ascribe the discrepancies in the concentration estimates to variations in ice surface signatures in the scene.

Burns, B. A.↗

Spaceborne imaging radar on EOS

A multiparameter synthetic aperture imaging radar is planned as a facility instrument for the Earth Orbiting System (EOS). This sensor will operate at L, C, and X and at all possible polarizations (HH, VV, HV, VH), thus allowing the acquisition of detailed information about the surface physical and electrical properties. When combined with the visible and IR imaging spectrometry data and the surface topography, a full description of the surface structure, composition, thermal properties and physical properties could then be extracted.

Elachi, Charles↗

Cassini/Huygens Science Instruments, Spacecraft, and Mission

The Cassini spacecraft will take 18 scientific instruments to Saturn. After launch and a seven-year cruise, Cassini will arrive at Saturn and separate into a Saturn orbiter and an atmospheric probe, called Huygens, which will descend to the surface of Titan. The orbiter will orbit the planet for four years, making close flybys of five satellites, including multiple flybys of Titan. Communication with Earth is at X-band; the maximum downlink rate from Saturn is 166 x 10(exp 3) bps. Orbiter instruments are body mounted; the spacecraft must be turned to point some of them toward objects of interest. The orbiter carries 12 instruments. Optical instruments provide imagery and spectrometry. Radar supplies imaging, altimetry, and radiometry. Radio links contribute information about intervening material and gravity fields. Other instruments measure electromagnetic fields and the properties of plasma, energetic particles, and dust particles. The probe is spin stabilized. It returns data via an S-band link to the orbiter. The probe's six instruments include sensors to determine atmospheric physical properties and composition. Radiometric and optical sensors will produce data on thermal balance and obtain images of Titan's atmosphere and surface. Doppler measurements between probe and orbiter will provide wind profiles. Surface sensors will measure impact acceleration, thermal and electrical properties, and, if the surface is liquid, density and refractive index. This design will enable Cassini to determine the composition; the physical, morphological, and geological nature; and the physical and chemical processes of the atmospheres, surfaces, and magnetosphere of the Saturnian system. This paper briefly describes the Cassini mission and spacecraft and, in somewhat more detail, the scientific instruments.

Jaffe, Leonard D.↗

Discovering the Ancient Maya From Space

The Peten region of northern Guatemala contains some of the most significant Mayan archeological sites in Latin America. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper, IKONOS, and QuickBird satellite, and airborne STAR-3i and AIRSAR radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as sites, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. Through the use of various airborne and satellite sensor systems we have been able to detect and map ancient causeways, temples, reservoirs, and land forms, and locate these features on the ground through GPS technology. Recently, we have discovered that there is a strong relationship between a tropical forest vegetation signature in satellite imagery and the location of archeological sites. We believe that the use o f limestone and lime plasters in ancient Maya construction affects the moisture, nutrition, and plant species of the surface vegetation. We have mapped these vegetation signatures in the imagery and verified through field survey that they are indicative of archeological sites. Through the use of remote sensing and GIS technology it is possible to identify unrecorded archeological features in a dense tropical forest environment and monitor these cultural features for their protection.

Sever, T. L.↗

Discovering the Ancient Maya from Space

The Pet6n region of northern Guatemala contains some of the most significant Mayan archeological sites in Latin America. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper, IKONOS, and QuickBird satellite, and airborne STAR-3i and AIRSAR radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as sites, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. Through the use of various airborne and satellite sensor systems we have been able to detect and map ancient causeways, temples, reservoirs, and land forms, and locate these features on the ground through GPS technology. Recently, we have discovered that there is a strong relationship between a tropical forest vegetation signature in satellite imagery and the location of archeological sites. We believe that the use of limestone and lime plasters in ancient Maya construction affects the moisture, nutrition, and plant species of the surface vegetation. We have mapped these vegetation signatures in the imagery and verified through field survey that they are indicative of archeological sites. Through the use of remote sensing and GIS technology it is possible to identify unrecorded archeological features in a dense tropical forest environment and monitor these cultural features for their protection.

Sever, T. L.↗

Investigation of Seasonal Landscape Freeze/Thaw Cycles in Relation to Cloud Structure in the High Northern Latitudes

The seasonal freezing and thawing of Earth's cryosphere (the portion of Earth's surface permanently or seasonally frozen) has an immense impact on Earth's climate as well as on its water, carbon and energy cycles. During the spring, snowmelt and the transition between frozen and non-frozen states lowers Earth's surface albedo. This change in albedo causes more solar radiation to be absorbed by the land surface, raising surface soil and air temperatures as much as 5 C within a few days. The transition of ice into liquid water not only raises the surface humidity, but also greatly affects the energy exchange between the land surface and the atmosphere as the phase change creates a latent energy dominated system. There is strong evidence to suggest that the thawing of the cryosphere during spring and refreezing during autumn is correlated to local atmospheric conditions such as cloud structure and frequency. Understanding the influence of land surface freeze/thaw cycles on atmospheric structure can help improve our understanding of links between seasonal land surface state and weather and climate, providing insight into associated changes in Earth's water, carbon, and energy cycles that are driven by climate change.Information on both the freeze/thaw states of Earth's land surface and cloud characteristics is derived from data sets collected by NOAA's Special Sensor Microwave/Imager (SSM/I), the Advanced Microwave Scanning Radiometer on NASA's Earth Observing System(AMSR-E), NASA's CloudSat, and NASA's SeaWinds-on-QuickSCAT Earth remote sensing satellite instruments. These instruments take advantage of the microwave spectrum to collect an ensemble of atmospheric and land surface data. Our analysis uses data from radars (active instruments which transmit a microwave signal toward Earth and measure the resultant backscatter) and radiometers (passive devices which measure Earth's natural microwave emission) to accurately characterize salient details on Earth's surface and atmospheric states. By comparing the cloud measurements and the surface freeze-thaw data sets, a correlation between the two phenomena can be developed.

clouds↗

Carolina Coastal Plain Ecological Forecasting: Utilizing NASA Earth Observations to Map Suitable Venus Flytrap Habitat in an Effort to Inform Conservation, Seed Banking, and Reintroduction in the Carolina Coastal Plain and Sandhills Regions

Although the carnivorous plant Venus flytrap (Dionaea muscipula) is recognized globally, its native range is restricted to a small portion of the North and South Carolina Coastal Plain and Sandhills. Within this limited range, Venus flytrap populations are threatened by habitat loss, fire suppression, and poaching. NASA DEVELOP partnered with the North Carolina Botanical Garden (NCBG), the University of North Carolina Herbarium (NCU), and the North Carolina Natural Heritage Program (NCNHP) to support Venus flytrap conservation. The team developed models based on species presence data and environmental variables using the Software for Assisted Habitat Modeling (SAHM) to create a 2021 habitat suitability map for Venus flytrap. These models incorporated Earth observations collected by Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Land Observation Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR), and Sentinel-2 Multispectral Instrument (MSI). To predict areas at high risk of development, the team produced a 2050 land-use change map using TerrSet Land Change Modeler. The team found potential areas of conflict between predicted habitat and forecasted future development. Many areas of suitable habitat were concentrated along the coast where development was likely to occur, placing populations there at risk of extirpation. Overlaying suitable habitat with forecasted land change also identified suitable habitats with minimal risk of development, which may serve as lasting Venus flytrap habitat. These results can inform the NCBG and NCNHP’s conservation decision-making, including targeted seed banking, reintroduction, and prioritization of enduring habitats for protection and management.

Monika Rock↗

Carolina Coastal Plain​ Ecological Forecasting

Although the carnivorous plant Venus flytrap (Dionaea muscipula) is recognized globally, its native range is restricted to a small portion of the North and South Carolina Coastal Plain and Sandhills. Within this limited range, Venus flytrap populations are threatened by habitat loss, fire suppression, and poaching. NASA DEVELOP partnered with the North Carolina Botanical Garden (NCBG), the University of North Carolina Herbarium (NCU), and the North Carolina Natural Heritage Program (NCNHP) to support Venus flytrap conservation. The team developed models based on species presence data and environmental variables using the Software for Assisted Habitat Modeling (SAHM) to create a 2021 habitat suitability map for Venus flytrap. These models incorporated Earth observations collected by Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Land Observation Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR), and Sentinel-2 Multispectral Instrument (MSI). To predict areas at high risk of development, the team produced a 2050 land-use change map using TerrSet Land Change Modeler. The team found potential areas of conflict between predicted habitat and forecasted future development. Many areas of suitable habitat were concentrated along the coast where development was likely to occur, placing populations there at risk of extirpation. Overlaying suitable habitat with forecasted land change also identified suitable habitats with minimal risk of development, which may serve as lasting Venus flytrap habitat. These results can inform the NCBG and NCNHP’s conservation decision-making, including targeted seed banking, reintroduction, and prioritization of enduring habitats for protection and management.

Monika Rock↗

Assessing Resilience in Lane Detection Methods: Infrastructure-Based Sensors and Traditional Approaches for Autonomous Vehicles

Traditional autonomous vehicle perception subsystems that use onboard sensors have the drawbacks of high computational load and data duplication. Infrastructure-based sensors, which can provide high quality information without the computational burden and data duplication, are an alternative to traditional autonomous vehicle perception subsystems. However, these technologies are still in the early stages of development and have not been extensively evaluated for lane detection system performance. Therefore, there is a lack of quantitative data on their performance relative to traditional perception methods, especially during hazardous scenarios, such as lane line occlusion, sensor failure, and environmental obstructions. We address this need by evaluating the influence of hazards on the resilience of three different lane detection methods in simulation: (1) traditional camera detection using a U-Net algorithm, (2) radar detections using infrastructure-based radar retro-reflectors (RRs), and (3) direct communication of lane line information using chip-enabled raised pavement markers (CERPMs). The performance of each of these methods is assessed using resilience engineering metrics by simulating the individual methods for each sensor technology’s response to related hazards in the CARLA simulator. Using simulation techniques to replicate these methods and hazards acquires extensive datasets without lengthy time investments. Specifically, the resilience triangle was used to quantitatively measure the resilience of the lane detection system to obtain unique insights into each of the three lane detection methods; notably the infrastructure-based CERPMs and RRs had high resistance to hazards and were not as easily affected as the vision-based U-Net. However, while U-Net was able to recover the fastest from the disruption as compared to the other two methods, it also had the most performance loss. Overall, this study demonstrates that while infrastructure-based lane keeping technologies are still in early development, they have great potential as alternatives to traditional ones.

Patil, Pritesh↗

A survey of the goals and accomplishments of the Seasat mission

The objectives of the Seasat mission, which was dedicated to establishing the utility of microwave sensors for the remote sensing of the earth's oceans, and data collected during some three months of orbital operations are briefly reviewed. In particular, consideration is given to the Seasat sensors and measurement goals, surface and in situ observations, evaluation organization, and current status of geophysical evaluation for each sensor (altimeter, Seasat-A scatterometer system, scanning multichannel microwave radiometer, visible and infrared radiometer, and synthetic aperture radar). Finally, future plans related to the Seasat project are discussed.

Born, G. H.↗

Future Imaging Sensor Capabilities

Advanced imaging sensor technologies that are being developed for future NASA earth observation missions are discussed. These include the multilinear array, the Shuttle imaging spectrometer, and the Shuttle imaging radar. The principal specifications and functional descriptions of the instruments are presented, and it is shown that the advanced technologies will enable a synergistic approach to the use of VIS/IR and microwave imaging sensors for remote sensing research and applications. The key problems posed by these future imaging sensor technologies are discussed, with particular attention given to data rates, power consumption, and data processing.

Carver, K. R.↗

Radiosonde pressure sensor performance - Evaluation using tracking radars

The standard balloon-borne radiosonde employed for synoptic meteorology provides vertical profiles of temperature, pressure, and humidity as a function of elapsed time. These parameters are used in the hypsometric equation to calculate the geopotential altitude at each sampling point during the balloon's flight. It is important that the vertical location information be accurate. The present investigation was conducted with the objective to evaluate the altitude determination accuracy of the standard radiosonde throughout the entire balloon profile. The tests included two other commercially available pressure sensors to see if they could provide improved accuracy in the stratosphere. The pressure-measuring performance of standard baroswitches, premium baroswitches, and hypsometers in balloon-borne sondes was correlated with tracking radars. It was found that the standard and premium baroswitches perform well up to about 25 km altitude, while hypsometers provide more reliable data above 25 km.

Parsons, C. L.↗

Digital simulation of the SIR-C sensor electronics

In this paper software for simulation of the response of the SIR-C sensor to a point target is described. Synthetic SAR data is generated by passing successive chirps through a simulation of the transmitter electronics, propagation path and receiver electronics. This result is then processed with a digital correlator to yield the point target response of the system. This allows an accurate assessment of the effect of the radar design on the final image product.

Klein, Jeffrey D.↗

Remote Characterization of Biomass Measurements: Case Study of Mangrove Forests

Accurately quantifying forest biomass is of crucial importance for climate change studies. By quantifying the amount of above and below ground biomass and consequently carbon stored in forest ecosystems, we are able to derive estimates of carbon sequestration, emission and storage and help close the carbon budget. Mangrove forests, in addition to providing habitat and nursery grounds for over 1300 animal species, are also an important sink of biomass. Although they only constitute about 3% of the total forested area globally, their carbon storage capacity -- in forested biomass and soil carbon -- is greater than that of tropical forests (Lucas et al, 2007). In addition, the amount of mangrove carbon -- in the form of litter and leaves exported into offshore areas is immense, resulting in over 10% of the ocean's dissolved organic carbon originating from mangroves (Dittmar et al, 2006) The measurement of forest above ground biomass is carried out on two major scales: on the plot scale, biomass can be measured using field measurements through allometric equation derivation and measurements of forest plots. On the larger scale, the field data are used to calibrate remotely sensed data to obtain stand-wide or even regional estimates of biomass. Currently, biomass can be calculated using average stand biomass values and optical data, such as aerial photography or satellite images (Landsat, Modis, Ikonos, SPOT, etc.). More recent studies have concentrated on deriving forest biomass values using radar (JERS, SIR-C, SRTM, Airsar) and/or lidar (ICEsat/GLAS, LVIS) active remote sensing to retrieve more accurate and detailed measurements of forest biomass. The implementation of a generation of new active sensors (UAVSar, DesdynI, Alos/Palsar, TerraX) has prompted the development of new tecm'liques of biomass estimation that use the combination of multiple sensors and datasets, to quantify past, current and future biomass stocks. Focusing on mangrove forest biomass estimation, this book chapter has 3 main objectives: a) To describe in detail the field methodologies used to derive accurate estimates of biomass in mangrove forests b) To explain how mangrove forest biomass can be measured using several remote sensing techniques and datasets c) To give a detailed explanation of the measurement challenges and errors that arise in each estimate of forest biomass

Fatoyinbo, Temilola E.↗