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At least 145 records · Page 8

Examining the Uppermost Surface of the Moon

Understanding the properties of the uppermost lunar surface is critical as it is the optical surface that is probed by remote-sensing data, like that which is and will be generated by instruments on orbiting missions (e.g. M3, LRO). The uppermost material is also the surface with which future lunar astronauts and their equipment will be in direct contact, and thus understanding its properties will be important for dust mitigation and toxicology issues. Furthermore, exploring the properties of this uppermost surface may provide insight into conditions at this crucial interface, such as grain charging and levitation

Noble, Sarah K.↗

Remote Sensing Based Yield Monitoring: Application to Winter Wheat in United States and Ukraine

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Earth observation data from space can contribute to agricultural monitoring, including crop yield assessment and forecasting. In this study, we present a new crop yield model based on the Difference Vegetation Index (DVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1 km resolution and the un-mixing of DVI at coarse resolution to a pure wheat signal (100 percent of wheat within the pixel). The model was applied to estimate the national and subnational winter wheat yield in the United States and Ukraine from 2001 to 2017. The model at the subnational level shows very good performance for both countries with a coefficient of determination higher than 0.7 and a root mean square error (RMSE) of lower than 0.6 t/ha (tonnes per hectare) (15-18 percent). At the national level for the United States (US) and Ukraine the model provides a strong coefficient of determination of 0.81 and 0.86, respectively, which demonstrates good performance at this scale. The model was also able to capture low winter wheat yields during years with extreme weather events, for example 2002 in US and 2003 in Ukraine. The RMSE of the model for the US at the national scale is 0.11 t/ha (3.7 percent) while for Ukraine it is 0.27 t/ha (8.4 percent).

DVI↗

The Mars Reconnaissance Orbiter Mission

The Mars Reconnaissance Orbiter (MRO) will be launched in August 2005 by an Atlas HIB expendable launch vehicle from Cape Canaveral Air Force Station. It will deliver to Mars orbit a payload to conduct remote sensing science observations, identify and characterize sites for future landers, and provide critical telecom/navigation relay capability for follow-on missions.

Mars↗

Polarization as a Discriminator of Light-Absorbing Impurities in or Above Snow

This conceptual study presents advanced radiative transfer computations of light polarization originating from a snowpack consisting of nonspherical grains and variable content of light-absorbing impurities, either embedded in the snowpack or (with the same optical properties) lofted above it in the form of atmospheric aerosols. The results highlight the importance of considering shapes other than spherical for the snow grains, which otherwise can lead to non-negligible errors in the retrieval of snow albedo from remote sensing observations. More importantly, it is found that polarimetric measurements provide a means to partition light-absorbing impurities embedded in the snowpack from absorbing aerosols aloft, a task traditionally prohibitive for sensors capable exclusively of measurements of total reflectance. Heritage techniques to obtain snow grain size from shortwave infrared observations of total reflectance are well established, as are those that leverage polarimetric, multiangular observations across the entire optical spectrum to characterize the optical and microphysical properties of atmospheric aerosols. The polarization signatures of near-infrared (e.g., 864 nm) observations carry critical information on snow grain shape. The prospected launch of space-borne polarimeters with proven accuracy, therefore, advocates for the development of data inversion schemes, to boost the accuracy of simultaneous retrievals of atmospheric and surface parameters in the polar and snow-covered regions, critical to climate studies.

light polarization↗

Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters

Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.

radiative transfer↗

Critical Evaluation of 0-30 km Profile Information in Ground-Based Zenith-Sky and Satellite-Measured Backscattered UV Radiation

We now have several decades of experience in deriving vertical ozone profiles from the measurements of diffuse ultraviolet radiation by both ground and satellite-based instruments using Umkehr and BUV techniques. Continuing technological advances are pushing the state-of-the-art of these measurements to high spectral resolution and broader wavelength coverage. These modern instruments include the ground-based Brewer and satellite-based Global Ozone Monitoring Experiment (GOME) instruments, as well as advanced instruments being developed by ESA(SCIAMACHY), Netherlands(OMI) and Japan(ODUS). However, one of the issues that remains unresolved is the 0-30 km ozone profile information retrievable from these measurements. Though it is commonly believed that both the Umkehr and the satellite-based BUV techniques have very limited profile information below 30 km, there are those who argue that the data from these instruments should continue to be reported in this altitude range for they compare well with ozonesondes and hence there is useful scientific information. Others claim that the limitations of the Umkehr and BUV techniques are largely due to their low spectral resolution, and that the profile information below 30 km can be greatly improved by going to high spectral resolution instruments, such as Brewer and GOME. The purpose of this paper is to provide a critical evaluation of the 0-30 km ozone profile information in the various UV remote sensing techniques. We use a database of individual ozone profiles created using ozonesondes and SAGE and 4D ozone fields generated by data assimilation techniques to simulate radiances measured by the various techniques. We then apply a common inversion approach to all the methods to systematically examine how much profile information is available simply from the knowledge of total ozone, how much additional profile information is added by the traditional Dobson Umkehr and satellite buv techniques, and how much better one can do by adding additional wavelengths and by going to higher spectral resolution. An open and honest discussion of these issues is critical to provide the ozone science community a realistic assessment of the quality of data in the lower stratosphere and troposphere expected from both past and future instruments.

Bhartia, Pawan↗

Sensing the Ocean Biological Carbon Pump from Space: A Review of Capabilities, Concepts, Research Gaps and Future Developments

The element carbon plays a central role in climate and life on Earth. It is capable of moving among the geosphere, cryosphere, atmosphere, biosphere and hydrosphere. This flow of carbon is referred to as the Earth's carbon cycle. It is also intimately linked to the cycling of other elements and compounds. The ocean plays a fundamental role in Earth's carbon cycle, helping to regulate atmospheric CO2 concentration. The ocean biological carbon pump (OBCP), defined as a set of processes that transfer organic carbon from the surface to the deep ocean, is at the heart of the ocean carbon cycle. Monitoring the OBCP is critical to understanding how the Earth's carbon cycle is changing. At present, satellite remote sensing is the only tool available for viewing the entire surface ocean at high temporal and spatial scales. In this paper, we review methods for monitoring the OBCP with a focus on satellites. We begin by providing an overview of the OBCP, defining and describing the pools of carbon in the ocean, and the processes controlling fluxes of carbon between the pools, from the surface to the deep ocean, and among ocean, land and atmosphere. We then examine how field measurements, from ship and autonomous platforms, complement satellite observations, provide validation points for satellite products and lead to a more complete view of the OBCP than would be possible from satellite observations alone. A thorough analysis is then provided on methods used for monitoring the OBCP from satellite platforms, covering current capabilities, concepts and gaps, and the requirement for uncertainties in satellite products. We finish by discussing the potential for producing a satellite-based carbon budget for the oceans, the advantages of integrating satellite-based observations with ecosystem models and field measurements, and future opportunities in space, all with a view towards bringing satellite observations into the limelight of ocean carbon research.

Robert J. W. Brewin↗

Smart Composite Overwrapped Pressure Vessel - Integrated Structural Health Monitoring System to Meet Space Exploration and International Space Station Mission Assurance Needs

Currently there are no integrated NDE methods for baselining and monitoring defect levels in fleet for Composite Overwrapped Pressure Vessels (COPVs) or related fracture critical composites, or for performing life-cycle maintenance inspections either in a traditional remove-and-inspect mode or in a more modern in situ inspection structural health monitoring (SHM) mode. Implicit in SHM and autonomous inspection is the existence of quantitative accept-reject criteria. To be effective, these criteria must correlate with levels of damage known to cause composite failure. Furthermore, implicit in SHM is the existence of effective remote sensing hardware and automated techniques and algorithms for interpretation of SHM data. SHM of facture critical composite structures, especially high pressure COPVs, is critical to the success of nearly every future NASA space exploration program as well as life extension of the International Space Station. It has been clearly stated that future NASA missions may not be successful without SHM [1]. Otherwise, crews will be busy addressing subsystem health issues and not focusing on the real NASA mission

Saulsberry, Regor↗

A review of mission planning systems

A general definition of Mission Planning is given. The definition covers the full scope of an end-to-end mission planning system. Noting the mission-specific nature of most mission planning systems, a classification of autonomous spacecraft missions is made into Observatory, Survey, multi-instrument science, and Telecommunications missions. The mission planning approach for one mission in each category is examined critically. The following missions were chosen: ISO (Infrared Space Observatory); ERS-1 (European Remote Sensing Satellite); and Eureca (European Retrievable Carrier). The paper gives a summary of lessons learned from these missions suggesting improvements in areas such as requirements analysis, testing, user interfacing, rules, and constraints handling. The paper will also examine commonalities in functions, which could constitute a basis for identification of generic mission planning support tools.

Jones, M.↗

InGaAsSb Detectors' Characterization for 2-Micron CO2 Lidar/DIAL Applications

Recent interest in monitoring atmospheric CO2 focuses attention on infrared remote sensing using the 2-micron lidar/differential absorption lidar (DIAL) technique. Quantum detectors are critical components in this technique, and many research efforts concentrate on developing such devices for the 2-micron wavelength. Characterization results of InGaAsSb quantum detectors for the 2-micron wavelength range are presented, including experimental setup and procedure. Detectors are prototype devices manufactured by using separate absorption and multiplication (SAM) structures. Characterization experiments include V-I measurements, spectral response and its variation with bias voltage and temperature, noise measurements, noise-equivalent-power (NEP) and detectivity calculations, and signal-to-noise ratio (SNR) estimation. A slight increase in the output signal occurred with increased bias voltage and was associated with a noise level increase. Cooling down the detectors reduces noise and shifts the cutoff wavelength to shorter values. Further improvement in the design and manufacturing process, by increasing the device gain and lowering its noise level, is necessary to meet the required CO2 lidar/DIAL specifications.

Refaat, Tamer F.↗

InGaAsSb Detectors Characterization for 2-Micron CO2 Lidar/DIAL Applications

Recent interest in monitoring atmospheric CO2 focuses attention on infrared remote sensing using the 2-micron lidar/differential absorption lidar (DIAL) technique. Quantum detectors are critical components in this technique, and many research efforts concentrate on developing such devices for the 2-micron wavelength. Characterization results of InGaAsSb quantum detectors for the 2-micron wavelength range are presented, including experimental setup and procedure. Detectors are prototype devices manufactured by using separate absorption and multiplication (SAM) structures. Characterization experiments include V-I measurements, spectral response and its variation with bias voltage and temperature, noise measurements, noise-equivalent-power (NEP) and detectivity calculations, and signal-to-noise ratio (SNR) estimation. A slight increase in the output signal occurred with increased bias voltage and was associated with a noise level increase. Cooling down the detectors reduces noise and shifts the cutoff wavelength to shorter values. Further improvement in the design and manufacturing process, by increasing the device gain and lowering its noise level, is necessary to meet the required CO2 lidar/DIAL specifications.

Refaat, Tamer F.↗

Further Studies on the Physical and Biogeochemical Causes for Large Interannual Changes in the Patagonian Shelf Spring-Summer Phytoplankton Bloom Biomass

A very strong and persistent phytoplankton bloom was observed by ocean color satellites during September - December 2003 along the northern Patagonian shelf. The 2003 bloom had the highest extent and chlorophyll a (Chl-a) concentrations of the entire Sea-viewing Wide Field-of-view Sensor (SeaWiFS) period (1997 to present). SeaWiFS-derived Chl-a exceeded 20 mg/cu m in November at the bloom center. The bloom was most extensive in December when it spanned more than 300 km across the shelf and nearly 900 km north-south (35degS to 43degS). The northward reach and the deep penetration on the shelf of the 2003 bloom were quite anomalous when compared with other years, which showed the bloom more confined to the Patagonian shelf break (PSB). The PSB bloom is a conspicuous austral spring-summer feature detected by ocean color satellites and its timing can be explained using the Sverdrup critical depth theory. Based on high-resolution numerical simulations, in situ and remote sensing data, we provide some suggestions for the probable mechanisms responsible for that large interannual change of biomass as seen by ocean color satellites. Potential sources of macro and micro (e.g., Fe) nutrients that sustain the high phytoplankton productivity of the Patagonian shelf waters are identified, and the most likely physical processes that maintain the nutrient balance in the region are discussed.

Signorini, Sergio R.↗

Spaceborne Microwave Instrument for High Resolution Remote Sensing of the Earth's Surface Using a Large-Aperture Mesh Antenna

This report describes a two-year study of a large-aperture, lightweight, deployable mesh antenna system for radiometer and radar remote sensing of the Earth from space. The study focused specifically on an instrument to measure ocean salinity and Soil moisture. Measurements of ocean salinity and soil moisture are of critical . importance in improving knowledge and prediction of key ocean and land surface processes, but are not currently obtainable from space. A mission using this instrument would be the first demonstration of deployable mesh antenna technology for remote sensing and could lead to potential applications in other remote sensing disciplines that require high spatial resolution measurements. The study concept features a rotating 6-m-diameter deployable mesh antenna, with radiometer and radar sensors, to measure microwave emission and backscatter from the Earth's surface. The sensors operate at L and S bands, with multiple polarizations and a constant look angle, scanning across a wide swath. The study included detailed analyses of science requirements, reflector and feedhorn design and performance, microwave emissivity measurements of mesh samples, design and test of lightweight radar electronic~., launch vehicle accommodations, rotational dynamics simulations, and an analysis of attitude control issues associated with the antenna and spacecraft, The goal of the study was to advance the technology readiness of the overall concept to a level appropriate for an Earth science emission.

Njoku, E.↗

Using MODIS and GLAS Data to Develop Timber Volume Estimates in Central Siberia

The boreal forest is the Earth's largest terrestrial biome, covering some 12 million km2 and accounting for about one third of this planet's total forest area. Mapping of boreal forest's type, structure parameters and biomass are critical for understanding the boreal forest's significance in the carbon cycle, its response to and impact on global climate change. Ground based forest inventories, have much uncertainty in the inventory data, particularly in remote areas of Siberia where sampling is sparse and/or lacking. In addition, many of the forest inventories that do exist for Siberia are now a decade or more old. Thus, available forest inventories fail to capture the current conditions. Changes in forest structure in a particular forest-type and region can change significantly due to changing environment conditions, and natural and anthropogenic disturbance. Remote sensing methods can potentially overcome these problems. Multispectral sensors can be used to provide vegetation cover maps that show a timely and accurate geographic distribution of vegetation types rather than decade old ground based maps. Lidar sensors can be used to directly obtain measurements that can be used to derive critical forest structure information (e.g., height, density, and volume). These in turn can used to estimate biomass components using allometric equations without having to use out dated forest inventory. Finally, remote sensing data is ideally suited to provide a sampling basis for a rigorous statistical estimate of the variance and error bound on forest structure measures. In this study, new remote sensing methods were applied to develop estimates timber volume using NASA's MODerate resolution Imaging Spectroradiometer (MODIS) and unique waveform data of the geoscience laser altimeter system (GLAS) for a 10 deg x 10 deg area in central Siberia. Using MODIS and GLAS data, maps were produced for cover type and timber volume for 2003, and a realistic variance (error bound) for timber volume was calculated for the study area. In this 'study we used only GLAS footprints that had a slope value of less than 10 deg. This was done to avoid large errors due to the effect of slope on the GLAS models. The method requires the integration of new remote sensing methods with available ground studies of forest timber volume conducted in Russian forests. The results were compared to traditional ground forest inventory methods reported in the literature and to ground truth collected in the study area.

Ranson, K. Jon↗

Tonlé Sap Food Security & Agriculture III: Evaluating Changes in Ecosystem Vitality and Freshwater Health in the Tonlé Sap Basin using Remotely Sensed Data

Tonlé Sap Lake, located in Cambodia, Southeast Asia, is one of the most productive inland fisheries in the world. With the unique reverse flow hydrology of the Tonlé Sap River, this freshwater system contains rich biodiversity and provides critical freshwater resources for the local community. Overfishing, stronger seasonality, drought, dam construction, forest fires, and untreated industrial domestic sewage threaten the ecosystem vitality and economic success of Tonlé Sap. In collaboration with Conservation International and the Cambodian Ministry of Water Resources and Meteorology’s Tonlé Sap Authority, we calibrated and finalized remotely-sensed proxies for sub-indicators of the Freshwater Health Index (FHI). We used NASA Earth observation data from Moderate Resolution Imaging Spectroradiometer (MODIS), and the Gravity Recovery and Climate Experiment (GRACE). These datasets were used in RS proxies and a Soil and Water Assessment Tool (SWAT) model that previous teams developed for sub-indicators of FHI. They included landcover, bank modification, and water quality metrics. It was determined that the ground water storage in Tonlé Sap Lake exhibited a slight declining trend over from April 1st, 2002 to February 3rd, 2017. To calculate chlorophyll-a concentration in the Tonlé Sap Lake, we used Copernicus Global Land Service mission data which provided a Trophic State Index of the lake. Between January 1st, 2000 and December 31st, 2020, the lake and surrounding region within the study area boundary displayed a slight decrease in vegetation density and consistently high chlorophyll-a concentrations. The SWAT model calculated nitrogen and phosphorus content measured in outlet points of the lake. We demonstrated that remotely sensed data is valuable for providing additional information for the FHI, but is not fully capable of replacing its in situ counterpart. We also concluded the water quantity is on a slowly declining trend within the basin.

Joey Lindsay↗

Remote sensing of sea ice thickness by a combined spatial and frequency domain interferometer : formulations, instrument design & development

The thickness of Arctic sea ice plays a critical role in Earth's climate and ocean circulation. An accurate measurement of this parameter on synoptic scales at regular intervals would enable characterization of this important component for the understanding of ocean circulation and the global heat balance. Presented in this paper is a low frequency VHF interferometer technique and associated radar instrument design to measure sea ice thickness based on the use of backscatter correlation functions. The sea ice medium is represented as a multi-layered medium consisting of snow, seaice and sea water, with the interfaces between layers characterized as rough surfaces. This technique utilizes the correlation of two radar waves of different frequencies and incident and observation angles, scattered from the sea ice medium. The correlation functions relate information about the sea ice thickness. Inversion techniques such as the genetic algorithm, gradient descent, and least square methods, are used to derive sea ice thickness from the phase information related by the correlation functions.

remote sensing↗

Proximity sensor technology for manipulator end effectors

Optical proximity sensing techniques which could be used to help control the critical grasping phase of a remote manipulation are described. The proximity sensors described use a triangulation geometry to detect a surface located in a pre-determined region. The design of the proximity sensors themselves is discussed, as well as their application to manipulator control with a local control loop, and possibilities for future development are discussed.

Johnston, A. R.↗

Improving Ocean Color Data Products using a Purely Empirical Approach: Reducing the Requirement for Radiometric Calibration Accuracy

Radiometric calibration is the foundation upon which ocean color remote sensing is built. Quality derived geophysical products, such as chlorophyll, are assumed to be critically dependent upon the quality of the radiometric calibration. Unfortunately, the goals of radiometric calibration are not typically met in global and large-scale regional analyses, and are especially deficient in coastal regions. The consequences of the uncertainty in calibration are very large in terms of global and regional ocean chlorophyll estimates. In fact, stability in global chlorophyll requires calibration uncertainty much greater than the goals, and outside of modern capabilities. Using a purely empirical approach, we show that stable and consistent global chlorophyll values can be achieved over very wide ranges of uncertainty. Furthermore, the approach yields statistically improved comparisons with in situ data, suggesting improved quality. The results suggest that accuracy requirements for radiometric calibration cab be reduced if alternative empirical approaches are used.

Gregg, Watson↗