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At least 343 records · Page 19

Monitoring VIIRS Thermal Emissive Bands Long-Term Performance Using Lunar Observations

Two Visible Infrared Imaging Radiometer Suite (VIIRS) instruments are currently operating in space, one onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite launched on October 28, 2011 and the other onboard the NOAA-20 satellite launched on November 18, 2017. The performance of the seven VIIRS thermal emissive bands (TEBs) is monitored via on-orbit calibration data, the analysis of Earth view observations, as well as inter-comparisons with other sensors. The Moon has been used as a unique invariant target for on-orbit sensor calibration because its surface property is considered extremely stable over time in spectra, radiometry, and geometry with a repeatable lunar phase. This paper presents the assessments of the S-NPP and NOAA-20 VIIRS TEB on-orbit calibration stability using near-monthly scheduled lunar observations over their respective missions. The methodology previously developed for MODIS is now applied to VIIRS to monitor the TEB long-term stability by extracting and trending the lunar brightness temperatures from selected unsaturated pixels. It includes a correction applied to reduce any impact from the Sun–Moon geometry (e.g. Sun-Moon distance variation). The results show that the mission-long brightness temperature trends from the lunar surface are stable for all VIIRS TEBs, despite noticeable seasonal variations in the lunar thermal emissive radiance.

VIIRS↗

Cloud-Based Solutions for Monitoring Coastal Ecosystems and Prioritization of Restoration Efforts Across Belize

In recent years the availability of automated change detection algorithms in Google Earth Engine has permitted cloud-based processing of large time series of satellite imagery. Models such as the Continuous Change Detection and Classification (CCDC), CCDC-Spectral Mixture Analysis (CCDC-SMA), and Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) allow users to exploit decades of Earth Observations (EO) , leveraging the Landsat archive and data from other sensors to detect disturbance in forest ecosystems. Despite the wide adoption of these methods, robust documentation and growing community of users, little research has explored their use in mangrove environments. Mangroves are dynamic environments subject to changes due to not only the natural migration of mudflats but also coastal erosion, urban expansion, aquaculture practices, etc. This work aims to identify best practices for the application of these models to identify and monitor changes in the Belizean mangroves, which experienced an estimated 5.4% decrease in extent between 1980 and 2017 (Cherrington et al. 2020). Partnering directly with the Belizean Forest Department, our team will develop a replicable, efficient methodology to annually update the country’s mangrove extent employing EO-based change detection. This collaboration supports Belize’s marine conservation and climate resilience efforts, such as its Blue Bond agreement with the Nature Conservancy, building on national processes to monitor these critical ecosystems.

Mangroves↗

Sensor Technology at Submillimeter Wavelengths for Space Applications

Our universe is most luminous at far-infrared and submillimeter wavelengths (100 GHz - 10 THz) after the Cosmic Microwave Background (CMB) radiation. This region of the electromagnetic spectrum provides critical tracers for the study of a wide range of astrophysical and planetary phenomena. This spectral range contains information on the origin of the planets, stars, galaxies, and clusters; the geometry and matter/energy content of the Universe, atmospheric constituents and dynamics of the planets and comets and tracers for global monitoring and the ultimate health of the Earth. Sensors at far-infrared and submillimeter wavelengths provide unprecedented sensitivity for astrophysical, planetary, and earth observing instruments. Very often, for a spaced based platform where the instruments are not limited by atmospheric losses and absorption, the overall instrument sensitivity is dictated by the sensitivity of the sensors themselves. Moreover, some of the cryogenic sensors at submillimeter wavelengths provide almost quantum-limited sensitivity. This paper provides an overview of the submillimeter-wave sensors and their performance and capabilities for space applications.

terahertz↗

Overview of the NASA tropospheric environmental quality remote sensing program

This paper will summarize the current NASA Tropospheric Environmental Quality Remote Sensing Program for studying the global and regional troposphere from space, airborne and ground-based platforms. As part of the program to develop remote sensors for utilization from space, NASA has developed a series of passive and active remote sensors which have undergone field test measurements from airborne and ground platforms. Recent measurements with active lidar and passive gas filter correlation and infrared heterodyne techniques will be summarized for measurements of atmospheric aerosols, CO, SO2, O3, and NH3. These measurements provide the data base required to assess the sensitivity of remote sensors for applications to urban and regional field measurement programs. Studies of Earth Observation Satellite Systems are currently being performed by the scientific community to assess the capability of satellite imagery to detect regions of elevated pollution in the troposphere. The status of NASA sponsored research efforts in interpreting satellite imagery for determining aerosol loadings over land and inland bodies of water will be presented, and comments on the potential of these measurements to supplement in situ and airborne remote sensors in detecting regional haze will be made.

Allario, F.↗

Earth observation from geostationary orbit

The paper describes a number of satellite-borne infrared spin-scan sensors and discusses the operational requirements for which they were designed. The sensors considered are the spin scan cloud cameras of ATS 1 and 3, the SMS/GOES visible-infrared spin-scan radiometer, and the VISSR atmospheric sounder.

Hummer, R. F.↗

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

Welton, Ellsworth J.↗

Operational Implementation of Sea Ice Concentration Estimates from the AMSR2 Sensor

An operation implementation of a passive microwave sea ice concentration algorithm to support NOAA's operational mission is presented. The NASA team 2 algorithm, previously developed for the NASA advanced microwave scanning radiometer for the Earth observing system (AMSR-E) product suite, is adapted for operational use with the JAXA AMSR2 sensor through several enhancements. First, the algorithm is modified to process individual swaths and provide concentration from the most recent swaths instead of a 24-hour average. A latency (time since observation) field and a 24-hour concentration range (maximum-minimum) are included to provide indications of data timeliness and variability. Concentration from the Bootstrap algorithm is a secondary field to provide complementary sea ice information. A quality flag is implemented to provide information on interpolation, filtering, and other quality control steps. The AMSR2 concentration fields are compared with a different AMSR2 passive microwave product, and then validated via comparison with sea ice concentration from the Suomi visible and infrared imaging radiometer suite. This validation indicates the AMSR2 concentrations have a bias of 3.9% and an RMSE of 11.0% in the Arctic, and a bias of 4.45% and RMSE of 8.8% in the Antarctic. In most cases, the NOAA operational requirements for accuracy are met. However, in low-concentration regimes, such as during melt and near the ice edge, errors are higher because of the limitations of passive microwave sensors and the algorithm retrieval.

Arctic↗

Joint Retrieval of Surface BRDF from Geostationary and Polar-Orbiting Satellite Sensors

The latest geostationary sensors like GOES 16/17 ABI and Himawari 8/9 AHI provide high frequent observations of the Earth surface with continuously changing solar illumination geometries, which allow us to retrieve the surface Bidirectional Reflectance Distribution Function (BRDF) with dedicated atmospheric correction algorithms like MAIAC (Multi-Angle Implementation of Atmospheric Correction). However, because the viewing geometry of a specific location from the geostationary satellites are fixed, the angular sampling of surface BRDF by GEO (Geostationary Earth Orbit) sensors is far from comprehensive. This study tries to address this issue by exploring a GEO-LEO (Low-Earth-Orbit) synergy, in particular, jointly retrieving surface BRDF parameters with concurrent ABI/AHI and VIIRS top-of-atmosphere (TOA) reflectance for the near-infrared (NIR) band. The NIR band is chosen because the ABI, AHI, and VIIRS instruments have very similar spectral response functions in this band and therefore simplifies the requirements for cross-sensor radiometric calibration. We compile ABI/AHI and VIIRS TOA data with the best quality (cloud-free and low aerosol loading) at chosen AERONET sites. We then run the GeoNEX MAIAC algorithm to retrieve the Ross-Thick-Li-Sparse (RTLS) surface BRDF parameters with or without the AEORNET measured atmospheric aerosol optical depth (AOD) as inputs. The joint retrieval results are considered the best estimate of surface BRDF. We compare the joint BRDF retrievals with the corresponding MAIAC BRDF products, retrieved with ABI/AHI or VIIRS separately, to evaluate their differences. We expect that the jointly retrieved BRDF data are more robust than the standard products and may help us reduce uncertainties in higher-level earth observation satellite products.

Remote Sensing↗

Stray-Light Correction of the Marine Optical Buoy

In ocean-color remote sensing, approximately 90% of the flux at the sensor originates from atmospheric scattering, with the water-leaving radiance contributing the remaining 10% of the total flux. Consequently, errors in the measured top-of-the atmosphere radiance are magnified a factor of 10 in the determination of water-leaving radiance. Proper characterization of the atmosphere is thus a critical part of the analysis of ocean-color remote sensing data. It has always been necessary to calibrate the ocean-color satellite sensor vicariously, using in situ, ground-based results, independent of the status of the pre-flight radiometric calibration or the utility of on-board calibration strategies. Because the atmosphere contributes significantly to the measured flux at the instrument sensor, both the instrument and the atmospheric correction algorithm are simultaneously calibrated vicariously. The Marine Optical Buoy (MOBY), deployed in support of the Earth Observing System (EOS) since 1996, serves as the primary calibration station for a variety of ocean-color satellite instruments, including the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Japanese Ocean Color Temperature Scanner (OCTS) , and the French Polarization and Directionality of the Earth's Reflectances (POLDER). MOBY is located off the coast of Lanai, Hawaii. The site was selected to simplify the application of the atmospheric correction algorithms. Vicarious calibration using MOBY data allows for a thorough comparison and merger of ocean-color data from these multiple sensors.

Brown, Steven W.↗

Passive remote sensing of stratospheric and mesospheric winds

A passive infrared sensor is described for remote sounding of the wind field in the stratosphere and mesosphere from near Earth orbital spacecraft. The instrument uses gas correlation spectroscopy together with electro-optic phase modulation techniques to measure winds in the 20- to 120-km altitude range globally, both in the day and at night, and with a vertical resolution of better than the atmospheric scale height. Measurement of temperature and the amounts of key atmospheric species may also be made simultaneously and in coincident fields of view with the wind observations. The sensor is currently being developed at the Jet Propulsion Laboratory as a candidate for the upcoming NASA Earth Observation System.

Mccleese, Daniel J.↗

The Critical Need for Continued Data Collection and Development of Future Thermal Satellite Sensors

There is a rich and long history of thermal infrared (TIR) remote sensing data for multidisciplinary Earth science research. The continuity of TIR data collection, however, is now in jeopardy given there are no planned future Earth observing TIR remote sensing satellite systems with moderately high spatial resolutions to replace those currently in orbit on NASA's Terra suite of sensors. This session will convene researchers who have actively worked in the field of TIR remote sensing to present results that elucidate the importance of thermal remote sensing to the wider Earth science research community. Additionally, this session will also exist as a forum for presenting concepts and ideas for new thermal sensing systems with high spatial resolutions for future Earth science satellite missions, as opposed to planned systems such as the Visible/Infrared Imager/Radiometer (VIIRS) suite of sensors on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) that will collect TIR data at very coarse spatial resolutions.

Quattrochi, Dale A.↗

Introduction to the Special Session on Thermal Remote Sensing Data for Earth Science Research: The Critical Need for Continued Data Collection and Development of Future Thermal Satellite Sensors

There is a rich and long history of thermal infrared (TIR) remote sensing data for multidisciplinary Earth science research. The continuity of TIR data collection, however, is now in jeopardy given there are no planned future Earth observing TIR remote sensing satellite systems with moderately high spatial resolutions to replace those currently in orbit on NASA's Terra suite of sensors. This session will convene researchers who have actively worked in the field of TIR remote sensing to present results that elucidate the importance of thermal remote sensing to the wider Earth science research community. Additionally, this session will also exist as a forum for presenting concepts and ideas for new thermal sensing systems with high spatial resolutions for future Earth science satellite missions, as opposed to planned systems such as the Visible/Infrared Imager/Radiometer (VIIRS) suite of sensors on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) that will collect TIR data at very coarse ~~~iairesolutions.

Quattrochi, Dale a.↗

Sensor Web and Intelligent Sensors for Earth Science Applications

There is a significant interest in the Earth Science remote sensing community in substantially increasing the number of observations relative to the current frequency of collection. The obvious reason for such a push is to improve the temporal and surface coverage of measurements. However, there is little analysis available in terms of benefits, costs and optimized set of sensors needed to make these necessary observations. This is a complex problem that should be carefully studied and balanced over many boundaries. For example, the question of technology maturity versus users' desire for obtaining additional measurements is noncongruent. This is further complicated by the limitations of the laws of physics and the economic conditions. With the advent of advanced technology, it is anticipated that developments in spacecraft technology will enable advanced capabilities to become more affordable. However, specialized detector subsystems, and precision flying techniques may still require substantial innovation, development time and cost. Additionally, the space deployment scheme should also be given careful attention because of the high associated expense. Nonetheless, it is important to carefully examine the science priorities and steer the development efforts that can commensurate with the tangible requirements. This presentation will focus on a possible set of architectural concepts beneficial for future Earth science studies and research its and potential benefits.

Habib, Shahid↗

Shifting the Inertial Navigation Paradigm with MEMS Technology

Why don t you use MEMS? is one of the most common questions posed to navigation systems engineers designing inertial navigation solutions in the modern era. The question stems from a general understanding that great strides have been made in terrestrial MEMS accelerometers and attitude rate sensors in terms of accuracy, mass, and power. Yet, when compared on a unit-to-unit basis, MEMS devices do not provide comparable performance (accuracy) to navigation grade sensors. This paper will propose a paradigm shift where the comparison in performance is between multiple MEMS devices and a single navigation grade sensor. The concept is that systematically, a sufficient number of MEMS sensors may mathematically provide comparable performance to a single navigation grade device and be competitive in terms power and mass allocations when viewed on a systems level. The implication is that both inertial navigation system design and fault detection, identification, and recovery could benefit from a system of MEMS devices in the same way that swarm sensing has benefited Earth observation and astronomy. A survey of the state of the art in inertial sensor accuracy scaled by mass and power will be provided to show the specific error in MEMS and navigation graded devices, a mathematical comparison of multi-unit to single-unit sensor errors will be developed, and preliminary applications to Constellation vehicles will be explored.

Crain, Timothy↗

Shifting the Intertial Navigation Paradigm with the MEMS Technology

"Why don't you use MEMS?" is of the most common questions posed to navigation systems engineers designing inertial navigation solutions in the modern era. The question stems from a general understanding that great strides have been made in terrestrial MEMS accelerometers and attitude rate sensors in terms of accuracy, mass, and power. Yet, when compared on a unit-to-unit basis, MEMS devices do not provide comparable performance (accuracy) to navigation grade sensors in several key metrics. This paper will propose a paradigm shift where the comparison in performance is between multiple MEMS devices and a single navigation grade sensor. The concept is that systematically, a sufficient number of MEMS sensors may mathematically provide comparable performance to a single navigation grade device and be competitive in terms power and mass allocations when viewed on a systems level. The implication is that both inertial navigation system design and fault detection, identification, and recovery could benefit from a system of MEMS devices in the same way that swarm sensing has benefited Earth observation and astronomy. A survey of the state of the art in inertial sensor accuracy scaled by mass and power will be provided to show the scaled error in MEMS and navigation graded devices, a mathematical comparison of multi-unit to single-unit sensor errors will be developed, and preliminary application to an Orion lunar skip atmospheric entry trajectory will be explored.

Crain, Timothy P., II↗

Investigation of transient earth resources phenomena: Continuation study

Calculated sensitivity requirements for an earth resource satellite in a geostationary orbit are reported. Radiance levels at the satellite sensor were computed for twenty top-priority Synchronous Earth Observatory Satellite (SEOS) applications. The observation requirements were reviewed and re-evaluated in terms of spectral band definition, spectral signatures of targets and backgrounds, observation time, and site location. With these data and an atmospheric attenuation and scattering model, the total radiances observed by the SEOS sensor were calculated as were the individual components contributed by the target, target variations, and the atmosphere.

Goldman, G. C.↗

SERVIR: Leveraging the Expertise of a Space Agency and a Development Agency to Increase Impact of Earth Observation in the Developing World

SERVIR is a joint initiative of the National Aeronautics and Space Administration (NASA) and the U.S. Agency for International Development (USAID), in collaboration with leading technical organizations around the world-- called SERVIR hubs--that serve and empower developing countries to use satellite data addressing critical challenges in food security and agriculture; water and water-related disasters; land cover, land use and ecosystems; and weather and climate. Over the past fourteen years, the program has worked with stakeholders in 50 countries across the world, partnered with 390 institutions, and generated and shared over 70 products from 27 satellites and sensors. In that process, around 7,400 specialists have been trained in the application of Earth observation data and technology. In its lifetime, SERVIR has been agile and innovative in shifting from what was essentially an incubator for testing and deploying Earth observation science and technology to making co-development the hallmark of its work, exemplified by both South-South and North-South scientific collaborations. SERVIR’s approach has embodied the concept that to solve really big problems, big, creative solutions are needed. SERVIR represents the world working together to address environmental challenges using spaced-based and geospatial technologies. Aligning with the very meaning of SERVIR, i.e. “to serve,” the program continues to be demand-driven in developing and deploying services (versus one-off products) which address development challenges using geospatial tools and Earth observation science. In 2016, as part of SERVIR’s evolution, USAID and NASA released the ‘SERVIR Service Planning Toolkit,’ a guidance document which provides a framework for how geospatial services can be used to tackle development challenges in a sustained manner. Since then, the Service Planning Toolkit’s systematic approach has begun to catch on in other Earth observation efforts. To improve access and use, SERVIR launched a Service Catalogue in February 2019, a searchable collection of demand-driven geospatial services that use Earth observations to support decision making. SERVIR implementing hub partners –include SERVIR-West Africa at the Agrometeorology, Hydrology and Meteorology (AGRHYMET) Regional Center, in Niamey, Niger; SERVIR-Eastern & Southern Africa at the Regional Centre for Mapping of Resources for Development in Nairobi, Kenya; SERVIR-Hindu Kush Himalaya at the International Centre for Integrated Mountain Development in Kathmandu, Nepal; SERVIR-Mekong at the Asian Disaster Preparedness Center in Bangkok, Thailand; and SERVIR’ -Amazonia, at the International Center for Tropical Agriculture (CIAT) in Cali, Colombia.

Searby, Nancy D.↗

HMMR (High-Resolution Multifrequency Microwave Radiometer) Earth observing system, volume 2e. Instrument panel report

Recommendations and background are provided for a passive microwave remote sensing system of the future designed to meet the observational needs of Earth scientist in the next decade. This system, called the High Resolution Multifrequency Microwave Radiometer (HMMR), is to be part of a complement of instruments in polar orbit. Working together, these instruments will form an Earth Observing System (EOS) to provide the information needed to better understand the fundamental, global scale processes which govern the Earth's environment. Measurements are identified in detail which passive observations in the microwave portion of the spectrum could contribute to an Earth Observing System in polar orbit. Requirements are established, e.g., spatial and temporal resolution, for these measurements so that, when combined with the other instruments in the Earth Observing System, they would yield a data set suitable for understanding the fundamental processes governing the Earth's environment. Existing and/or planned sensor systems are assessed in the light of these requirements, and additional sensor hardware needed to meet these observational requirements are defined.

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