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DOE OSTI2025

Scaling Arctic landscape and permafrost features improves active layer depth modeling

Tundra ecosystems in the Arctic store up to 40% of global below-ground organic carbon but are exposed to the fastest climate warming on Earth. However, accurately monitoring landscape changes in the Arctic is challenging due to the complex interactions among permafrost, micro-topography, climate, vegetation, and disturbance. This complexity results in high spatiotemporal variability in permafrost distribution and active layer depth (ALD). Moreover, these key tundra processes interact at different scales, and an observational mismatch can limit our understanding of intrinsic connections and dynamics between above and below-ground processes. Consequently, this could limit our ability to model and anticipate how ALD will respond to climate change and disturbances across tundra ecosystems. In this paper, we studied the fine-scale heterogeneity of ALD and its connections with land surface characteristics across spatial and spectral scales using a combination of ground, unoccupied aerial system, airborne, and satellite observations. We showed that airborne sensors such as AVIRIS-NG and medium-resolution satellite Earth observation systems like Sentinel-2 can capture the average ALD at the landscape scale. We found that the best observational scale for ALD modeling is heavily influenced by the vegetation and landform patterns occurring on the landscape. Landscapes characterized by small-scale permafrost features such as polygon tussock tundra require high-resolution observations to capture the intrinsic connections between permafrost and small-scale land surface and disturbance patterns. Conversely, in landscapes dominated by water tracks and shrubs, permafrost features manifest at a larger scale and our model results indicate the best performance at medium resolution (5 m), outperforming both higher (0.4 m) and lower resolution (10 m) models. This transcends our study to show that permafrost response to climate change may vary across dominant ecosystem types, driven by different above- and below-ground connections and the scales at which these connections are happening. We thus recommend tailoring observational scales based on landforms and characteristics for modeling permafrost distribution, thereby mitigating the influences of spatial-scale mismatches and improving the understanding of vegetation and permafrost changes for the Arctic region.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2007

Advanced Image Processing for NASA Applications

The future of space exploration will involve cooperating fleets of spacecraft or sensor webs geared towards coordinated and optimal observation of Earth Science phenomena. The main advantage of such systems is to utilize multiple viewing angles as well as multiple spatial and spectral resolutions of sensors carried on multiple spacecraft but acting collaboratively as a single system. Within this framework, our research focuses on all areas related to sensing in collaborative environments, which means systems utilizing intracommunicating spatially distributed sensor pods or crafts being deployed to monitor or explore different environments. This talk will describe the general concept of sensing in collaborative environments, will give a brief overview of several technologies developed at NASA Goddard Space Flight Center in this area, and then will concentrate on specific image processing research related to that domain, specifically image registration and image fusion.

LeMoign, Jacqueline↗

NASA NTRS2000

Insights on How NASA's Earth Observing System (EOS) Monitors Our World Environment

King, Michael D.↗

NASA NTRS1999

Earth Observing System: Present Capabilities and Promises for the Future

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year 5 EOS science missions are scheduled for launch, representing observations of (i) total solar irradiance, (ii) Earth radiation budget, (iii) land cover & land use change, (iv) ocean processes (vector wind, sea surface temperature, and ocean color), (v) atmospheric processes (aerosol and cloud properties, water vapor, and temperature and moisture profiles), and (vi) atmospheric chemistry (both tropospheric and stratospheric). In succeeding years many more satellites will be launched that will contribute immeasurably to our understanding of the Earth's environment. In this presentation I will describe how scientists intend to use MODIS, an earth-viewing cross-track scanning spectroradiometer to be launched on the Terra satellite in summer 1999, for the remote sensing of cloud and aerosol properties. MODIS will scan a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km. In addition, I will describe key elements of other instruments recently launched or planned for flight in the coming months. Finally, I will lay out a plan for the future space-based observing system being planned by NASA and its partners.

King, Michael D.↗

NASA NTRS1999

Clouds and Radiation from the Earth Observing System

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, four EOS science missions are scheduled for launch, representing observations of (i) total solar irradiance, (ii) Earth radiation budget, (iii) land cover & land use change, (iv) ocean processes (vector wind, sea surface temperature, and ocean color), (v) atmospheric processes (aerosol and cloud properties, water vapor, and temperature and moisture profiles), and (vi) tropospheric chemistry. In succeeding years many more satellites will be launched that will contribute immeasurably to our understanding of the Earth's environment. In this presentation we will describe how scientists are using MODIS (Moderate Resolution Imaging Spectroradiometer), an earth-viewing cross-track scanning spectroradiometer on the Terra (AM-1) satellite, for the remote sensing of cloud and aerosol properties. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 pm with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmosphere processes.

King, Michael D.↗

NASA NTRS2001

Earth Observing System: Global Observations to Study the Earth's Environment

King, Michael D.↗

NASA NTRS2003

Earth Observing System: Global Observations to Study the Earth's Environment

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During the last couple of years, four EOS science missions were launched, representing observations of (i) total solar irradiance, (ii) Earth radiation budget, (iii) land cover & land use change, (iv) ocean processes (vector wind, sea surface temperature, and ocean color), (v) atmospheric processes (aerosol and cloud properties, water vapor, and temperature and moisture profiles), and (vi) tropospheric chemistry. In succeeding years many more satellites will be launched that will contribute immeasurably to our understanding of the Earth's environment. In this presentation I will describe how scientists are using NASA's Earth science data to examine land use and natural hazards, environmental air quality, including: dust storms over the worlds deserts, cloud and radiation properties, sea surface temperature, and winds over the ocean, with a special emphasis on satellite observations available for studying the southern African environment.

King, Michael D.↗

NASA NTRS2009

MODIS Science Algorithms and Data Systems Lessons Learned

For almost 10 years, standard global products from NASA's Earth Observing System s (EOS) two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors are being used world-wide for earth science research and applications. This paper discusses the lessons learned in developing the science algorithms and the data systems needed to produce these high quality data products for the earth sciences community. Strong science team leadership and communication, an evolvable and scalable data system, and central coordination of QA and validation activities enabled the data system to grow by two orders of magnitude from the initial at-launch system to the current system able to reprocess data from both the Terra and Aqua missions in less than a year. Many of the lessons learned from MODIS are already being applied to follow-on missions.

Wolfe, Robert E.↗

NASA NTRS1989

Science requirements for passive microwave sensors on earth science geostationary platforms

It is suggested that the science requirements for passive geostationary microwave observations be met by near- and far-term sensors for each of two overlapping bands, with each band covering no more than a decade in frequency. The low-frequency band includes channels near 6, 10, 18, 22, 31 to 37, and possibly 50 to 60 GHz. The high-frequency band includes channels near 220 to 230, 183, 166, 118, 90 to 110, and possibly 50 to 60 and 31 to 37 GHz. The precise channel specifications will have to comply with international frequency allocations. The near-term goal is a high-frequency sensor based on a filled-aperture solid reflector antenna, which should rely on currently existing technology. The most critical issues for the near-term sensor are momentum compensation and the design of the feed assembly; these issues are coupled through the desired scan rate. The successful demonstration of the near-term (high-frequency) sensor will be essential for the continued development of far-term sensors satisfying the ideal science requirements. The far-term goal includes both a high-frequency sensor which meets the ideal science requirements, and a low-frequency sensor whose design will depend on advances in large antenna technology. The low-frequency (far-term) sensor might be based on one of several concepts: a deployable mesh reflector antenna of diameter at least 20 m, which shows promise for use at frequencies up to 30-GHz, a synthetic aperture interferometer of maximum baseline from 100 to 300 m, or a deployable phased-array bootlace lens, of diameter from 100 to 300 m. The first of these, a deployable mesh reflector antenna, will satisfy only the adequate spatial resolution requirements. The last two concepts meet the ideal spatial resolution science requirements, although they present significant structural and meteorological challenges.

Gasiewski, A. J.↗

NASA NTRS2000

NASA's Earth Observation Program: Past, Present and Future

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. In this electronic theater presentation I will illustrate how scientists can learn about the Earth's atmosphere, land, oceans, and cryosphere from the vantage point of space-based global observations. This presentation will emphasize, but will not be limited to, Earth observations from space that highlight the ecosystem and environment of southern Africa, including: (i) dynamic geosynchronous satellite observations of southern Africa and nearby Indian Ocean, (ii) vegetation dynamics (normalized difference vegetation index and leaf area index), (iii) sea surface temperature, ocean topography, and surface winds over the Benguela and Agulhas Currents, (iv) Landsat 7 imagery of Cape Town, Etosha Pan, and other regions of southern Africa (v) fire distribution and dynamics in the Miombo woodland of Zambia, Angola, and Malawi, (vi) aerosol and cloud properties in southern Africa, and (vii) ice sheet distribution in and around Antarctica. We will illustrate these and other topics with a dynamic theater-style presentation, along with animations of satellite launch deployments and orbital mapping to highlight aspects of Earth observations from space.

King, Michael D.↗

NASA NTRS2008

Using Sensor Web Processes and Protocols to Assimilate Satellite Data into a Forecast Model

The goal of the Sensor Management Applied Research Technologies (SMART) On-Demand Modeling project is to develop and demonstrate the readiness of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities to integrate both space-based Earth observations and forecast model output into new data acquisition and assimilation strategies. The project is developing sensor web-enabled processing plans to assimilate Atmospheric Infrared Sounding (AIRS) satellite temperature and moisture retrievals into a regional Weather Research and Forecast (WRF) model over the southeastern United States.

Goodman, H. Michael↗

NASA NTRSDate not supplied

Bridging the Last Mile with Open-Source Advancements: Empowering Communities through Fusion of Aerosol Optical Depth (AOD) Products from Multi-Satellite Sensors

Aerosol Optical Depth (AOD) is a crucial parameter for understanding atmospheric aerosol distribution and their impact on climate and air quality. With the growing number of Earth observation satellites, there is an abundance of AOD products derived from various sensors onboard both geostationary and low-orbit satellites. The availability of multiple datasets provides an opportunity to harness the strengths of each sensor and create comprehensive and accurate AOD datasets for climate and air quality studies at different temporal and spatial scales. Our NASA aerosol MEaSURES project has made significant strides in recent years by undertaking the ambitious task of developing an open-source package tailored for fusing AOD products from different sources. The package is based on OOP (Object-Oriented Programming) design and is implemented in Python modules. Generic interfaces enable easy inclusion of large and heterogeneous data. The package may be utilized to produce harmonized AOD datasets with enhanced spatial and temporal coverage. The latest version of the package is able to process and integrate the dark-target AOD data from six different sensors: AHI Himawari-8, ABI GOES-West, ABI GOES-East, MODIS AQUA, MODIS TERRA, and VIIRS SNPP. Rigorous validation and intercomparison studies have been performed to assess the accuracy and reliability of the fused AOD product against ground-based measurements and reference datasets. The open-source nature of the developed package ensures transparency, reproducibility, and community engagement. The research community and stakeholders can access, contribute to, and further improve the fusion methodology, making it adaptable to other studies, or expanding it to include new satellite data as they become available. In this poster presentation, we will introduce the accomplishments and challenges faced during the development of the open-source package for AOD data fusion, and demonstrate the advantages of combining AOD products from the six aforementioned satellite sensors. The presentation aims to foster discussions, collaborations, and future directions in integrating Earth observation and remote sensing data, which may contribute to a better understanding of atmospheric aerosols and their impacts on our environment.

Zhaohui Zhang↗

NASA NTRS2001

Fires and Smoke Observed from the Earth Observing System MODIS Instrument: Products, Validation, and Operational Use

The MODIS sensor, launched on NASA's Terra satellite at the end of 1999, was designed with 36 spectral channels for a wide array of land, ocean, and atmospheric investigations. MODIS has a unique ability to observe fires, smoke, and burn scars globally. Its main fire detection channels saturate at high brightness temperatures: 500 K at 4 microns and 400 K at 11 microns, which can only be attained in rare circumstances at the I kin fire detection spatial resolution. Thus, unlike other polar orbiting satellite sensors with similar thermal and spatial resolutions, but much lower saturation temperatures (e.g. AVHRR and ATSR), MODIS can distinguish between low intensity ground surface fires and high intensity crown forest fires. Smoke column concentration over land is for the first time being derived from the MOMS solar channels, extending from 0.41 microns to 2.1 microns. The smoke product has been provisionally validated both globally and regionally over southern Africa and central and south America. Burn scars are observed from MODIS even in the presence of smoke, using the 1.2 to 2.1 micron channels. MODIS burned area information is used to estimate pyrogenic emissions. A wide range of these fire and related products and validation are demonstrated for the wild fires that occurred in northwestern United States in the summer of 2000. The MODIS rapid response system and direct broadcast capability is being developed to enable users to obtain and generate data in near real time. It is expected that health and land management organizations will use these systems for monitoring the occurrence of fires and the dispersion of smoke within two to six hours after data acquisition.

Kaufman, Y. J.↗

NASA NTRS2004

NASA's Earth Observing System (EOS): Observing the Atmosphere, Land, Oceans, and Ice from Space

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, the last of the first series of EOS missions, Aura, was launched. Aura is designed exclusively to conduct research on the composition, chemistry, and dynamics of the Earth's upper and lower atmosphere, employing multiple instruments on a single spacecraft. Aura is the third in a series of major Earth observing satellites to study the environment and climate change and is part of NASA's Earth Science Enterprise. The first and second missions, Terra and Aqua, are designed to study the land, oceans, atmospheric constituents (aerosols, clouds, temperature, and water vapor), and the Earth's radiation budget. The other seven EOS spacecraft include satellites to study (i) land cover & land use change, (ii) solar irradiance and solar spectral variation, (iii) ice volume, (iv) ocean processes (vector wind and sea surface topography), and (v) vertical variations of clouds, water vapor, and aerosols up to and including the stratosphere. Aura's chemistry measurements will also follow up on measurements that began with NASA's Upper Atmosphere Research Satellite and continue the record of satellite ozone data collected from the TOMS missions. In this presentation I will describe how scientists are using EOS data to examine the health of the earth's atmosphere, including atmospheric chemistry, aerosol properties, and cloud properties, with a special but not exclusive look at the latest earth observing mission, Aura.

King, Michael D.↗

NASA NTRS2005

NASA's Earth Observing System (EOS): Observing the Atmosphere, Land, Oceans, and Ice from Space

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by whch scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, the last of the first series of EOS missions, Aura, was launched. Aura is designed exclusively to conduct research on the composition, chemistry, and dynamics of the Earth's upper and lower atmosphere, employing multiple instruments on a single spacecraft. Aura is the third in a series of major Earth observing satellites to study the environment and climate change and is part of NASA's Earth Science Enterprise. The first and second missions, Terra and Aqua, are designed to study the land, oceans, atmospheric constituents (aerosols, clouds, temperature, and water vapor), and the Earth's radiation budget. The other seven EOS spacecraft include satellites to study (i) land cover & land use change, (ii) solar irradiance and solar spectral variation, (iii) ice volume, (iv) ocean processes (vector wind and sea surface topography), and (v) vertical variations of clouds, water vapor, and aerosols up to and including the stratosphere. Aura's chemistry measurements will also follow up on measurements that began with NASA's Upper Atmosphere Research Satellite and continue the record of satellite ozone data collected from the TOMS missions. In this presentation I will describe how scientists are using EOS data to examine the health of the earth's atmosphere, including atmospheric chemistry, aerosol properties, and cloud properties, with a special look at the latest earth observing mission, Aura.

King, Michael D.↗

NASA NTRS1989

MODIS - Advanced facility instrument for studies of the earth as a system

The moderate resolution imaging spectrometer (MODIS) is discussed as an earth-viewing sensor that is planned as a facility instrument for the Earth Observing System (EOS) scheduled to begin functioning in the mid-1990s. The MODIS is composed of two mutually supporting sensors that cover a swath width sufficient to provide nearly complete two-day global coverage from a polar-orbiting, sun-synchronous, serviceable platform. High signal-to-noise ratios are to be provided, e.g., 500 to 1 or greater with 10-12-bit quantization over the dynamic ranges of the spectral bands. MODIS' lifetime is expected to be about ten years. One of the MODIS sensors is termed MODIS-N, where N signifies nadir-viewing. The companion to MODIS-N is MODIS-T, where T signifies a tiltable field-of-view. The development of the MODIS facility from conceptual design studies (Phase-A) into detailed design studies (Phase-B) is discussed.

Salomonson, Vincent V.↗

NASA NTRS1998

Does the UVI on Polar Detect Cosmic Snowballs?

Frank and Sigwarth [1997a] claim that the dark pixels observed in dayglow images obtained by the Earth sensor of the Visible Imaging System (VIS) are due to bombardment of Earth by 20 to 40 ton cosmic snowballs. We have independently studied the same one hour of VIS data Frank and Sigwarth used and have performed detailed statistical analysis of the dark pixels. The characteristics of the dark pixels from the VIS images have been compared to those obtained from the overlapping images from the Ultraviolet Imager (UVI). We find the occurrence distributions of the dark pixels, single and multiple, from VIS and UVI are nearly identical. This result cannot be explained by a -eophysical source since the two cameras have different pixel resolutions: A search for evidence of of spacecraft "wobble" motion, whose presence would indicate that the source is external to the camera, has found that pairs of dark pixel clusters are uniformly distributed in an-le and no preference is observed in the wobble direction. Instrument artifacts as the source of the dark pixels is the most likely explanation for these results. Probability estimates for the occurrence of dark pixel clusters lead us to expect coincident events of instrumental origin to occur frequently in the two cameras. The conclusion of this study is that neither VIS nor UVI provide any scientific evidence that the origin of dark pixels is geophysical.

Parks, G. K.↗

NASA NTRS2012

Geophysical Information from Advanced Sounder Infrared Spectral Radiance

Advanced satellite sensors are tasked with improving global observations of the Earth's atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring capability, and environmental change detection. Satisfying this type of improvement for inferred geophysical information from these observations requires optimal usage of data from current systems as well as enhancements to future sensors. This presentation addresses the information content present in infrared spectral radiance from advanced atmospheric sounders with an emphasis on knowledge of thermodynamic state and trace species. Results of trade-off studies conducted to evaluate the impact of spectral resolution, spectral coverage, instrument noise, and a priori knowledge on remote sensing system information content will be discussed. A focus is placed on information achievable from the Atmospheric InfraRed Sounder (AIRS) on the NASA EOS Aqua satellite in orbit since 2002, the Infrared Atmospheric Sounding Interferometer (IASI) aboard MetOp-A since 2006, and the Cross-track Infrared Sounder (CrIS) instrument aboard the NPP and JPSS series of satellites which began 28 October 2011.

Larar, Allen M.↗