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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Antarctic Iceberg Tracking Based on Time Series of Aqua AMSRE Microwave Brightness Temperature Measurements

Observations of icebergs are identified as one of the requirements for the GEOSS (Global Earth Observation System of Systems) in the area of reducing loss of life and property from natural and human-induced disasters. However, iceberg observations are not included among targets in the GEOSS 10-Year Implementation Plan, and thus there is an unfulfilled need for iceberg detection and tracking in the near future. Large Antarctic icebergs have been tracked by the National Ice Center and by the academic community using a variety of satellite sensors including both passive and active microwave imagers, such as SSM/I (Special Sensor Microwave/Imager) deployed on the DMSP (Defense Meteorological Satellite Program) spacecraft. Improvements provided in recent years by NASA and non-NASA satellite radars, scatterometers, and radiometers resulted in an increased number of observed icebergs and even prompted a question: Is The Number of Antarctic Icebergs Really Increasing? [D.G. Long, J. Ballantyne, and C. Bertoia, Eos, Transactions of the American Geophysical Union 83 (42): 469 & 474, 15 October 2002]. AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System) represents an improvement over SSM/I, its predecessor. AMSR-E has more measurement channels and higher spatial resolution than SSM/I. For example, the instantaneous field of view of the AMSR-E s 89-GHz channels is 6 km by 4 km versus 16 km by 14 km for SSM/I s comparable 85-GHz channels. AMSR-E, deployed on the Aqua satellite, scans across a 1450-km swath and provides brightness temperature measurements with nearglobal coverage every one or two days. In polar regions, overlapping swaths generate coverage up to multiple times per day and allow for creation of image time series with high temporal resolution. Despite these advantages, only incidental usage of AMSR-E data for iceberg tracking has been reported so far, none in an operational environment. Therefore, an experiment was undertaken in the RPC (Rapid Prototyping Capability) of NASA s (National Aeronautics and Space Administration) Applied Science Program to demonstrate that passive microwave brightness temperature measurements acquired by AMSR-E can be effectively used to track iceberg movement around Antarctica. The RPC s robust computation environment enabled processing of terabytes of data products available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. Iceberg tracking based on the AMSR-E Level 2A data product was compared with records from the National Ice Center for currently existing icebergs. Some icebergs as small as roughly 10 km in size were easily observed, but tracking of many others, even larger ones, was obscured by presence of sea ice surrounding the icebergs. The best results, such as for the large iceberg A22A, were achieved when an iceberg was in open ocean.

Blonski, Slawomir↗
NASA NTRS2001

Science Autonomy in Robotic Exploration

Historical mission operations have involved: (1) return of scientific data; (2) evaluation of these data by scientists; (3) recommendations for future mission activity by scientists; (4) commands for these transmitted to the craft; and (5) the activity being undertaken. This cycle is repeated throughout the mission with command opportunities once or twice per day. For a rover, this historical cycle is not amenable to rapid long range traverses or rapid response to any novel or unexpected situations. In addition to real-time response issues, imaging and/or spectroscopic devices can produce tremendous data volumes during a traverse. However, such data volumes can rapidly exceed on-board memory capabilities prior to the ability to transmit it to Earth. Additionally, the necessary communication band-widths are restrictive enough so that only a small portion of these data can actually be returned to Earth. Such scenarios suggest enabling some science decisions to be made on-board the robots. These decisions involve automating various aspects of scientific discovery instead of the electromechanical control, health, and navigation issues associated with robotic operations. The robot retains access to the full data fidelity obtained by its scientific sensors, and is in the best position to implement actions based upon these data. Such an approach would eventually enable the robot to alter observations and assure only the highest quality data is obtained for analysis. Additionally, the robot can begin to understand what is scientifically interesting and implement alternative observing sequences, because the observed data deviate from expectations based upon current theories/models of planetary processes. Such interesting data and/or conclusions can then be prioritized and selectively transmitted to Earth; reducing memory and communications demands. Results of Ames' current work in this area will be presented.

Roush, Ted L.↗
NASA NTRS2001

Robotic Exploration: The Role of Science Autonomy

Historical mission operations have involved: (1) return of scientific data; (2) evaluation of these data by scientists; (3) recommendations for future mission activity by scientists; (4) commands for these transmitted to the craft; and (5) the activity being, undertaken. This cycle is repeated throughout the mission with command opportunities once or twice per day. For a rover, this historical cycle is not amenable to rapid long range traverses or rapid response to any novel or unexpected situations. In addition to real-time response issues, imaging and/or spectroscopic devices can produce tremendous data volumes during a traverse. However, such data volumes can rapidly exceed on-board memory capabilities prior to the ability to transmit it to Earth. Additionally, the necessary communication band-widths are restrictive enough so that only a small portion of these data can actually be returned to Earth. Such scenarios suggest enabling some science decisions to be made on-board the robots. These decisions involve automating various aspects of scientific discovery instead of the electromechanical control, health, and navigation issues associated with robotic operations. The robot retains access to the full data fidelity obtained by its scientific sensors, and is in the best position to implement actions based upon these data. Such an approach would eventually enable the robot to alter observations and assure only the highest quality data is obtained for analysis. Additionally, the robot can begin to understand what is scientifically interesting and implement alternative observing sequences, because the observed data deviate from expectations based upon current theories/models of planetary processes. Such interesting data and/or conclusions can then be prioritized and selectively transmitted to Earth; reducing memory and communications demands. Results of Ames' current work in this area will be presented.

Roush, Ted L.↗
NASA NTRS2006

Enhancing Science and Automating Operations using Onboard Autonomy

In this paper, we will describe the evolution of the software from prototype to full time operation onboard Earth Observing One (EO-1). We will quantify the increase in science, decrease in operations cost, and streamlining of operations procedures. Included will be a description of how this software was adapted post-launch to the EO-1 mission, which had very limited computing resources which constrained the autonomy flight software. We will discuss ongoing deployments of this software to the Mars Exploration Rovers and Mars Odyssey Missions as well as a discussion of lessons learned during this project. Finally, we will discuss how the onboard autonomy has been used in conjunction with other satellites and ground sensors to form an autonomous sensor-web to study volcanoes, floods, sea-ice topography, and wild fires. As demonstrated on EO-1, onboard autonomy is a revolutionary advance that will change the operations approach on future NASA missions...

Earth Observing One (EO-1)↗
NASA NTRS1975

Orbit and attitude state recoveries from Landmark data

The navigation of earth-referenced satellites with imaging data rather than, or in addition to, conventional radio tracking and attitude sensor telemetry is gaining increased popularity. Driving forces include a trend towards spacecraft autonomy, a need for timely and highly accurate griding information, and a growing awareness of the presence of high quality navigation information contained in such data. This paper describes the techniques used and the results obtained in an experiment to determine the orbit and attitude state of the geosynchronous SMS-1 spacecraft from Landmark observations extracted from earth images generated by the on-board Visible and Infrared Spin-Scan Radiometer (VISSR).

Fuchs, A. F.↗
NASA NTRS1975

Orbit and attitude state recoveries from Landmark data

The navigation of earth-referenced satellites with imaging data rather than, or in addition to, conventional radio tracking and attitude sensor telemetry is gaining increased popularity. Driving forces include a trend towards spacecraft autonomy, a need for timely and highly accurate gridding information, and a growing awareness of the presence of high quality navigation information contained in such data. This paper describes the techniques used and the results obtained in an experiment to determine the orbit and attitude state of the geosynchronous SMS-1 spacecraft from Landmark observations extracted from earth images generated by the on-board Visible and Infrared Spin-Scan Radiometer (VISSR).

Fuchs, A. F.↗
NASA NTRS2005

NASA GES DISC On-line Visualization and Analysis System for Gridded Remote Sensing Data

The ability to use data stored in the current NASA Earth Observing System (EOS) archives for studying regional or global phenomena is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. Gaining this understanding and applying it to data reduction is a time-consuming task that must be undertaken before the core investigation can begin. This is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets that are usually of different formats, structures, and resolutions. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step towards meeting this challenge by developing an infrastructure with a Web interface that allows users to perform interactive analysis online without downloading any data, the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni." Giovanni provides interactive, online, analysis tools for data users to facilitate their research. There have been several instances of this interface created to serve TRMM users, Aerosol scientists, Ocean Color and Agriculture applications users. The first generation of these tools support gridded data only. The user selects geophysical parameters, area of interest, time period; and the system generates an output on screen in a matter of seconds. The currently available output options are: Area plot averaged or accumulated over any available data period for any rectangular area; Time plot time series averaged over any rectangular area; Hovmoller plots image view of any longitude-time and latitude-time cross sections; ASCII output for all plot types; Image animation for area plot. Another analysis suite deals with parameter intercomparison: scatter plots, temporal correlation maps, GIs-compatible outputs, etc. This allow user to focus on data content (i.e. science parameters) and eliminate the need for expensive learning, development and processing tasks that are redundantly incurred by an archive's user community. The current implementation utilizes the GrADS-DODS Server (GDS), and provides subsetting and analysis services across the Internet for any GrADS-readable dataset. The subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large dataset, eliminating the need to download everything simply to access a small relevant portion of a dataset. The analysis capability allows users to retrieve the results of an operation applied to one or more datasets on the server. We use this approach to read pre-processed binary files and/or to read and extract the needed parts directly from HDF or HDF-EOS files. These subsets then serve as inputs into GrADS analysis scripts. It can be used in a wide variety of Earth science applications: climate and weather events study and monitoring; modeling. It can be easily configured for new applications.

Leptoukh, Gregory G.↗
NASA NTRS2021

Coastal California Water Resources II: Utilizing NASA Earth Observations to Detect and Assess the Impacts of Estuarine Breach Events for Improved Coastal Wetland Monitoring and Management

Estuaries are dynamic environments that provide a host of vital ecosystem services. California’s Marine Life Protection Act protects such ecosystems by creating Marine Protected Areas. California has approximately 440,000 acres of estuarine habitats as well as 23 Estuarine Marine Protected Areas (EMPAs); thus, in situ data collection is often difficult due to time and resource constraints. This project used remote sensing to gather data that examined the health and dynamics of California EMPAs in order to supplement ground-based field measurements. Through the use of Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Sentinel-2 Multispectral Instrument (MSI) and Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), this project assessed mouth state, inundation extent, turbidity, temperature, and tidal measurements for observable estuaries. The Normalized Water Difference Index from Sentinel-2 MSI captured estuary mouth state and inundation extent. Landsat 8 OLI and Sentinel-2 MSI detected differences in water quality metrics that correlated to changes in estuary mouth state (i.e., open or closed). The team’s California Estuary Assessment (CEA) tool in Google Earth Engine was successful in analyzing estuary mouth state, inundation, and water quality. It was most effective when breach events were larger than 10 meters in resolution, water surface was smooth, and imagery was unimpeded by algae or sun glint. The CEA tool will allow the partners, the Ocean Protection Council, Central Coast Wetlands Group, Southern California Coastal Water Research Project, and University of California Los Angeles (UCLA) and Davis (UCD), to better understand estuary dynamics and more effectively conduct in situ estuary monitoring.

Sarah Payne↗
NASA NTRS2013

NASA Orbital Debris Large-Object Baseline Population in ORDEM 3.0

The NASA Orbital Debris Program Office (ODPO) has created and validated high fidelity populations of the debris environment for the latest Orbital Debris Engineering Model (ORDEM 3.0). Though the model includes fluxes of objects 10 um and larger, this paper considers particle fluxes for 1 cm and larger debris objects from low Earth orbit (LEO) through Geosynchronous Transfer Orbit (GTO). These are validated by several reliable radar observations through the Space Surveillance Network (SSN), Haystack, and HAX radars. ORDEM 3.0 populations were designed for the purpose of assisting, debris researchers and sensor developers in planning and testing. This environment includes a background derived from the LEO-to-GEO ENvironment Debris evolutionary model (LEGEND) with a Bayesian rescaling as well as specific events such as the FY-1C anti-satellite test, the Iridium 33/Cosmos 2251 accidental collision, and the Soviet/Russian Radar Ocean Reconnaissance Satellite (RORSAT) sodium-potassium droplet releases. The environment described in this paper is the most realistic orbital debris population larger than 1 cm, to date. We describe derivations of the background population and added specific populations. We present sample validation charts of our 1 cm and larger LEO population against Space Surveillance Network (SSN), Haystack, and HAX radar measurements.

Krisco, Paula H.↗
NASA NTRS2015

Global Lightning Climatology from the Tropical Rainfall Measuring Mission (TRMM), Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD)

The Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) has been collecting observations of total lightning in the global tropics and subtropics (roughly 38 deg S - 38 deg N) since December 1997. A similar instrument, the Optical Transient Detector, operated from 1995-2000 on another low earth orbit satellite that also saw high latitudes. Lightning data from these instruments have been used to create gridded climatologies and time series of lightning flash rate. These include a 0.5 deg resolution global annual climatology, and lower resolution products describing the annual cycle and the diurnal cycle. These products are updated annually. Results from the update through 2013 will be shown at the conference. The gridded products are publicly available for download. Descriptions of how each product can be used will be discussed, including strengths, weaknesses, and caveats about the smoothing and sampling used in various products.

Cecil, Daniel J.↗
NASA NTRS2021

Informing Improvements in Freeze/Thaw State Classification Using Subpixel Temperature

Freeze/thaw (FT) processes at the earth’s surface can have a considerable effect on global carbon, energy, and hydrologic cycles. Therefore, an accurate representation of FT is valuable to adequately monitor and model these processes. In this study, we assess the relationship between satellite-based FT products and modeled surface and soil temperatures over North America. In addition, hourly land surface temperature (LST) from the Geostationary Operational Environmental Satellite (GOES) system is also compared to FT classifications. Utilizing the higher spatial resolution temperatures (5 km), we assess subgrid-scale variability and its relationship to coarser microwave FT classifications (>25 km). We also examine product agreement and subpixel characteristics across the land cover, climate, and topography. FT classifications are shown to vary widely depending on these variables, leading to an ambiguous definition of frozen and thawed states. Our results suggest that current products can characterize FT transitions with consistent subfreezing surface characteristics in far northern regions (>50 °N). However, uncertainty associated with FT classifications is shown to increase considerably as latitude decreases. Our results also suggest that fractional FT products, utilizing data inputs, such as LST, would provide a considerable improvement in mountainous regions with high intergrid cell heterogeneity, in regions characterized by ephemeral FT events (i.e., regions <40 °N), as well as during freeze and thaw onset periods. This study also provides insight to improving the representation of surface FT state by providing a clearer definition of the subpixel scale temperature characteristics that govern existing frozen classifications.

Earth observing systems↗
NASA NTRSDate not supplied

Using DSCOVR EPIC as a Transfer Radiometer to Scale Leo Imagers to the Same Calibration Reference

The NASA CERES project provides climate-quality observed TOA and computed surface fluxes to the climate community. The CERES instruments are on board the Terra, Aqua, Suomi-NPP, and NOAA-20 low earth orbiting (LEO) satellites, where they are used in tandem with the MODIS and VIIRS instruments to retrieve cloud properties required for converting CERES radiance observations into fluxes. The CERES project radiometrically scales the MODIS and VIIRS imager visible channel radiances to the Aqua-MODIS reference to retrieve consistent imager cloud properties between sensors. The NPP, NOAA-20, and the future NOAA-21 VIIRS imagers will be in the same sun-synchronous orbit but spaced equally apart, allowing for no simultaneous nadir overpasses (SNO) to inter-calibrate the VIIRS imagers to each other. Currently, the CERES project uses Aqua-MODIS to radiometrically scale between VIIRS imagers. Once the Terra and Aqua satellites start drifting toward the terminator, Aqua can no longer be utilized as the transfer radiometer between VIIRS sensors and there will be no SNOs in common between neither MODIS nor VIIRS imagers. The DSCOVR satellite orbits the Lagrange-1 (L1) point about 1.5 million kilometers from Earth. The Earth Polychromatic Imaging Camera (EPIC) instrument on the Earth-facing side of DSCOVR takes images ranging from the UV to the NIR of the sunlit side of the Earth. While the EPIC sensor has no onboard calibration systems, multiple inter-calibration studies have indicated that the EPIC instrument response is radiometrically stable. The stability of the EPIC instrument allows it to be used as a transfer radiometer between all MODIS and VIIRS imagers. The study will demonstrate the use of EPIC to radiometrically scale VIIRS and MODIS imagers to the same Aqua-MODIS calibration reference. The EPIC-based NPP and N20-VIIRS scaling factors will be compared with the Aqua-MODIS based NPP and N20-VIIRS scaling factors.

C. O. Haney↗
NASA NTRS2017

Improvements in the On-Orbit Response Versus Scan Angle Characterization of the Aqua MODIS Reflective Solar Bands

The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) has been chosen by the Global Space-based Inter-Calibration System operational community as the reference sensor in cross-sensor calibration. A number of geostationary orbit and low-earth orbit sensors use the 0.64-μm band from Aqua MODIS as a calibration reference. After over 15 years on-orbit, the performance characteristics of the MODIS instrument have changed, with effects evident at short wavelengths. MODIS employs a reflectance-based calibration using the solar diffuser measurements with the monthly lunar observations facilitating a response versus scan angle characterization on-orbit. As the instrument continues to operate beyond its design lifetime of 6 years, the on-board calibrators alone are insufficient to accurately characterize the instrument's response at all scan angles. This results in a long-term reflectance drift, particularly observed in the 0.64- and 0.85-μm bands, while observing the temporally invariant desert sites. Long-term reflectance drifts of up to 2% and 3% are observed at the beginning of scan for the 0.64- and 0.85-μm bands, respectively. An approach using earth-view response to supplement the on-board calibrator measurements has been shown to overcome these inadequacies and is now implemented for the 0.64-, 0.85-, 0.46-, and 0.55-μm land bands of Aqua MODIS. This paper presents the details related to the algorithm implementation and an independent evaluation using the Dome Concordia site and deep-convective clouds. This approach has been reviewed, tested, and approved by the MODIS science team and has been implemented in the forward production of the MODIS L1B Collection 6 starting July 9, 2016. This enhanced approach has also been adopted in the MODIS L1B Collection 6.1 reprocess for the entire mission to facilitate an improved quality of downstream science products. The results with the enhanced approach reduce the reflectance drifts to within 0.5% for most cases.

Angal, Amit↗
DOE OSTI2026

Ecological Insights from Transferable Plant Biomass Mapping across the Arctic using High-resolution Structure-from-Motion and LiDAR Data

Warmer temperatures, permafrost thaw, and increased wildfire activity are driving rapid ecological change across the Arctic, significantly altering plant productivity and aboveground biomass (AGB). These rapid changes highlight the urgent need to improve monitoring of vegetation dynamics in the Earth’s northern ecosystems, where high spatiotemporal heterogeneity occurs at scales finer than those captured by traditional satellite observations. The growing use of Unoccupied Aerial Systems (UASs) presents an opportunity to overcome this limitation. Yet, the diversity of UAS platforms, sensors, and data collection and processing workflows presents challenges for developing standardized, generalizable approaches. To address this challenge, we compiled 672 AGB plots co-located with 183 UAS-based Structure-from-Motion (SfM) or Light Detection and Ranging (LiDAR) surveys collected across the Arctic. Here, we: (1) evaluated the generalizability of UAS-derived canopy structure derived from high-resolution SfM and LiDAR for estimating AGB, (2) assessed scaling errors and their sources in two recent satellite-based AGB products derived from Landsat and MODIS, and (3) demonstrated the use of high-resolution AGB maps to quantify biomass variation across tundra plant functional types (PFTs) and to monitor post-fire recovery. Our results show that both SfM and LiDAR accurately captured AGB and its variability across tundra PFTs using a Random Forest (RF) model (overall RMSE: 0.336 kg/m2), with mapping performance varying slightly by region and data source. Using UAS-derived AGB maps as a benchmark, we identified systematic biases in satellite-derived AGB products, largely attributable to the magnitude of AGB and structural heterogeneity within coarse-resolution pixels. Applying our model to repeat UAS surveys following a tundra fire on Seward Peninsula, we observed rapid AGB recovery in non-shrub patches, with biomass recovering to pre-fire levels within 2 years. In contrast, shrub patches recovered more slowly, with AGB gains continuing over 2–4 years through both in-patch growth and lateral expansion (via dispersal) into remaining burned areas. Overall, these findings demonstrate the generalizability of UAS-based SfM and LiDAR data for estimating tundra AGB and highlight the potential of our approach to be broadly applied to generate high-quality AGB data for ecological monitoring and model benchmarking across the Arctic.

Yang, Daryl [ORNL] (ORCID:0000000317057823)↗
NASA NTRS1985

Cartographic potential of SPOT image data

In late 1985, the SPOT (Systeme Probatoire d'Observation de la Terre) satellite is to be launched by the Ariane rocket from French Guiana. This satellite will have two High Resolution Visible (HRV) line array sensor systems which are capable of providing monoscopic and stereoscopic coverage of the earth. Cartographic applications are related to the recording of stereo image data and the acquisition of 20-m data in a multispectral mode. One of the objectives of this study involves a comparison of the suitability of SPOT and TM image data for mapping urban land use/cover. Another objective is concerned with a preliminary assessment of the potential of SPOT image data for map revision when merged with conventional map sheets converted to raster formats.

Welch, R.↗
NASA NTRS1988

An attempt to remotely sense from space the surface heat budget over the Indian Ocean during the 1979 monsoon

Satellite data are used to estimate the net surface heat flux (Q) over the Indian Ocean during June 1979. Ten-day and monthly average fields of Q and its components are produced and analyzed in relation to monsoon dynamics. When compared to ship-based estimates, the satellite-derived fluxes exhibit correct orders of magnitude and their temporal evolution is consistent with the present monsoon knowledge. This study, which represents a first attempt to remotely sense from space the earth surface net heat flux, demonstrates that current satellite sensor data can be combined to accurately describe net heat flux changes in areas such as the Arabian Sea, where they are large, rapid, and spatially extended, and therefore not fully observed by ships.

Gautier, Catherine↗
NASA NTRS2003

Automated Data Processing as an AI Planning Problem

NASA s vision for Earth Science is to build a "sensor web"; an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving his vision will require automation not only in the scheduling of the observations but also in the processing af tee resulting data. Ta address this need, we have developed a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products. Data processing domains are substantially different from other planning domains that have been explored, and this has led us to substantially different choices in terms of representation and algorithms. We discuss some of these differences and discuss the approach we have adopted.

Golden, Keith↗
NASA NTRS2017

The High Definition Earth Viewing (HDEV) Payload

The High Definition Earth Viewing (HDEV) payload enables long-term experimentation of four, commercial-of-the-shelf (COTS) high definition video, cameras mounted on the exterior of the International Space Station. The payload enables testing of cameras in the space environment. The HDEV cameras transmit imagery continuously to an encoder that then sends the video signal via Ethernet through the space station for downlink. The encoder, cameras, and other electronics are enclosed in a box pressurized to approximately one atmosphere, containing dry nitrogen, to provide a level of protection to the electronics from the space environment. The encoded video format supports streaming live video of Earth for viewing online. Camera sensor types include charge-coupled device and complementary metal-oxide semiconductor. Received imagery data is analyzed on the ground to evaluate camera sensor performance. Since payload deployment, minimal degradation to imagery quality has been observed. The HDEV payload continues to operate by live streaming and analyzing imagery. Results from the experiment reduce risk in the selection of cameras that could be considered for future use on the International Space Station and other spacecraft. This paper discusses the payload development, end-to- end architecture, experiment operation, resulting image analysis, and future work.

Muri, Paul↗