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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2019

2018 NISAR Applications Workshop: Forest and Disturbance; Workshop Report

Forest lands cover the globe and are important sources for providing ecosystem services including: carbon sequestration, biodiversity, timber, air and water quality. As such, counties around the world have dedicated programs for managing them. Accurate and timely information concerning the status of these forests (moisture, biomass, disturbance type, etc.) is essential to those Nations’ human and ecological health as well as economy. The joint NASA/US Forest Service workshop focused on arming forest land managers with observations and remote sensing information from the upcoming NASA-ISRO (Indian Space Research Organization) SAR (Synthetic Aperture Radar) (NISAR) satellite mission (expected to launch early 2022). Participants included representatives from different US Federal Agencies, private sector, and non-governmental organizations (NGO) that are key players in facilitating integration of Earth Observations (EO) into forest management and decision support workflows. They included scientists, technicians, and program managers with a responsibility for data acquisition and exploitation such as product development, delivery, and use, and capacity building. Discussions were held over two days to convey the broader forest and disturbance community information needs for various representative participants and programs and to facilitate the delivery of NISAR mission geospatial products and observational capabilities. Case studies were presented to demonstrate the current state of practice in the use of SAR remote sensing for applications of direct importance to forest and disturbance land management community. Eleven organizations presented their information requirements in response to a set of questions provided by the NASA team, then the NASA team responded by describing the degree to which NISAR could meet these requirements. Discussion ensued about needed data product specifications to increase utility (e.g., projection, latency, etc.), tools and capacity building. The general findings of this workshop were that (a) NISAR observations will be particularly useful to the global forest carbon and disturbance monitoring applications, but that certain data product design decisions (projections and radiometric and terrain corrections) need to be considered to increase utility; b) the biomass and disturbance detection algorithms meet many of the community needs, however there are other information products of value (e.g., soil moisture or disturbance classification, not just detection) and all products should be compliant with existing community standards for reporting uncertainty; c) providing SAR education to the community will be key specifically thinking about putting the information first and the SAR theory second, providing a simple guide of standard data processing steps (e.g., dB (decibel) to power conversion and speckle filtering); d) the community needs a user-friendly interface for finding free, archived data over their geographic regions of interest; e) user-friendly tools that connect to open-sources GIS (Global Information System) software (e.g., QGIS (Quantum GIS)) that include a graphical user interface (GUI) for SAR processing that enables both download and cloud processing. To integrate these findings and prepare the community before NISAR launches, it was suggested that there be a dedicated NISAR Forest and Disturbance Applications Working Group (as per the specifications in the NISAR Utilization Plan). After launch, it was decided that the community continue capacity building activities.

Stavros, Natasha↗
NASA NTRS1981

Onboard utilization of ground control points for image correction. Volume 2: Analysis and simulation results

An approach to remote sensing that meets future mission requirements was investigated. The deterministic acquisition of data and the rapid correction of data for radiometric effects and image distortions are the most critical limitations of remote sensing. The following topics are discussed: onboard image correction systems, GCP navigation system simulation, GCP analysis, and image correction analysis measurement.

Source record↗
NASA NTRS1996

Correction of WindScat Scatterometric Measurements by Combining with AMSR Radiometric Data

The Seawinds scatterometer on the advanced Earth observing satellite-2 (ADEOS-2) will determine surface wind vectors by measuring the radar cross section. Multiple measurements will be made at different points in a wind-vector cell. When dense clouds and rain are present, the signal will be attenuated, thereby giving erroneous results for the wind. This report describes algorithms to use with the advanced mechanically scanned radiometer (AMSR) scanning radiometer on ADEOS-2 to correct for the attenuation. One can determine attenuation from a radiometer measurement based on the excess brightness temperature measured. This is the difference between the total measured brightness temperature and the contribution from surface emission. A major problem that the algorithm must address is determining the surface contribution. Two basic approaches were developed for this, one using the scattering coefficient measured along with the brightness temperature, and the other using the brightness temperature alone. For both methods, best results will occur if the wind from the preceding wind-vector cell can be used as an input to the algorithm. In the method based on the scattering coefficient, we need the wind direction from the preceding cell. In the method using brightness temperature alone, we need the wind speed from the preceding cell. If neither is available, the algorithm can work, but the corrections will be less accurate. Both correction methods require iterative solutions. Simulations show that the algorithms make significant improvements in the measured scattering coefficient and thus is the retrieved wind vector. For stratiform rains, the errors without correction can be quite large, so the correction makes a major improvement. For systems of separated convective cells, the initial error is smaller and the correction, although about the same percentage, has a smaller effect.

Song, S.↗
NASA NTRS2020

Landsat-8 TIRS Thermal Radiometric Calibration Status

The Landsat-8 Thermal Infrared Sensor (TIRS) has been acquiring two-band thermal infrared images of the Earth’s surface since 2013. The calibration of the two-band system has been monitored using the on-board calibrator and validated with vicarious calibration performed by NASA/JPL and RIT since launch. Soon after launch, it was discovered that the instrument had a significant stray light effect that was affecting the radiometric calibration. The stray light was corrected in the processing system in 2017. Since then, it has become apparent that there was an additional radiometric error, based on the vicarious calibration results. With a failure within the primary electronic system and subsequent switch to the redundant electronic system, the TIRS instrument effectively has two separate calibration regimes. The vicarious calibration found a statistically significant calibration error, primarily a constant over time, in Band 11 on the primary electronics (Feb 11,2013 through March 5,2015) of about -0.6K at 300K. The calibration error in Band 10 was smaller though still statistically significant at about 0.2K at 300K. On the redundant side(March 5,2015 to present), the calibration error is more signal dependent than time dependent. Both bands are affected, with Band 10 having an error between 1K and -0.4K (between 273-320K) and Band 11 having an error between 0.8K and -1.44K (between 273-320K).This calibration error will be corrected within the USGS Landsat Product Generation System with the release of Landsat Collection-2 products. The Collection-2 release also includes a correction to the relative radiometric calibration of TIRS data. Striping as a result of poor detector-to-detector normalization has been increasing in the imagery since launch. The TIRS relative radiometric calibration will be updated based on internal calibrator data to remove the stripes on a quarterly basis. The visible stripes are generally at 0.1-0.2% level, though there are some detectors in each band that have changed by 1% or more. The Collection-2 release will result in much more uniform TIRS images.

Julia A Barsi↗
NASA NTRS1991

Synergic inversion technique for active and passive microwave remote sensing of the ocean

A unified approach for combining active and passive microwave measurements for remote sensing applications is described. A synergic inversion technique has been developed and applied to the retrieval of geophysical parameters of the ocean surface and of the atmosphere. It is based on the combination of radiometric and radar measurements at the electromagnetic and cell level and not only on the correction of radar measurements by radiometric measurements, or conversely. Such a combination is performed through a common quantity: the bistatic scattering coefficient of the observed surface. This is used in a direct model to simulate combined measurements from active and passive sensors. It requires a rather complete and accurate calculation of the scattering of microwaves by the rough sea surface. Comparisons with experimental models derived for scatterometers and radar altimeters or with data derived from radiometric measurements show that the results of this unified approach are consistent with those from separate microwave sensors, at least for a foam-free sea surface.

Sobieski, Piotr↗
NASA NTRS2021

Atmospheric Correction Over Ocean for Hyperspectral Radiometers Using Multi-Angle Polarimetric Retrievals

We developed a fast and accurate POLYnomial based Atmospheric Correction (POLYAC) algorithm for hyperspectral radiometric measurements, which parameterizes the atmospheric path radiances using aerosol properties retrieved from co-located multi-wavelength Multi-Angle Polarimeter (MAP) measurements. This algorithm has been applied to co-located Spectrometer for Planetary Exploration (SPEX) airborne and Research Scanning Polarimeter (RSP) measurements, where SPEX airborne was used as a proxy of hyperspectral radiometers, and RSP as the MAP. The hyperspectral remote sensing reflectance obtained from POLYAC is accurate when compared to Aerosol Robotic Network (AERONET), and Visible Infrared Imaging Radiometer Suite (VIIRS) ocean color products. POLYAC provides a robust alternative atmospheric correction algorithm for hyperspectral or multi-spectral radiometric measurements for scenes involving coastal oceans and/or absorbing aerosols, where traditional atmospheric correction algorithms are less reliable.

ocean color↗
NASA NTRS2023

Comparative Analysis of Empirical and Machine Learning Models for Chla Extraction Using Sentinel-2 and Landsat OLI Data: Opportunities, Limitations, and Challenges

Remote retrieval of near-surface chlorophyll-a (Chla) concentration in small inland waters is challenging due to substantial optical interferences of various water constituents and uncertainties in the atmospheric correction (AC) process. Although various algorithms have been developed to estimate Chla from moderate-resolution terrestrial missions (∼10–60 m), the production of both accurate distribution maps and time series of Chla has proven challenging, limiting the use of remote analyses for lake monitoring. Here, we develop a support vector regression (SVR) model, which uses satellite-derived remote-sensing reflectance spectra () from Sentinel-2 and Landsat-8 images as input for Chla retrieval in a representative eutrophic prairie lake, Buffalo Pound Lake (BPL), Saskatchewan, Canada. Validated against in situ Chla from seven ice-free seasons (N ∼ 200; 2014–2020), the SVR model outperformed both locally tuned, -fed empirical models (Normalized Difference Chlorophyll Index, 2- and 3-band, and OC3) and Mixture Density Networks (MDNs) by 15–65%, while exhibiting comparable performance to a locally trained MDN, with an error of ∼35%. Comparison of Chla retrieval models, AC processors (iCOR, ACOLITE), and radiometric products (Rayleigh-corrected, surface, and top-of-atmosphere reflectance) showed that the best Chla maps and optimal time series (up to 100 mg m−3) were produced using a coupled SVR-iCOR system.

algal blooms↗
NASA NTRS1972

Digital image processing for the earth resources technology satellite data.

This paper discusses the problems of digital processing of the large volumes of multispectral image data that are expected to be received from the ERTS program. Correction of geometric and radiometric distortions are discussed and a byte oriented implementation is proposed. CPU timing estimates are given for a System/360 Model 67, and show that a processing throughput of 1000 image sets per week is feasible.

Will, P. M.↗
NASA NTRS1973

Navigation system design for the Mariner Jupiter/Saturn Mission.

The Mariner Jupiter/Saturn Mission is described with emphasis on the navigation problems arising in attempting a Jupiter/Saturn swingby mission which includes close encounters with one or more of the natural satellites of each planet. The navigation system being designed to solve these problems is described. This system includes sub-systems for precision trajectory correction. Earth-based radiometric data, and onboard star/satellite measurements via employment of the science-imaging TV sub-system. Total system performance is discussed as measured against the mission's inherent navigation goals.

Curkendall, D. W.↗
NASA NTRS1979

Landsat-D data acquisition and processing

The Landsat-D system, in which S-band and X-band data links will provide real-time direct transmission of sensor data, is described. System performance objectives include input data quantity of 200 MSS scenes/day and 100 TM scenes/day by the Domestic Communication Satellite, and processing capability, in a pipeline mode, of 2.6 x 10 to the 11th input bits of sensor data per 16-hour day. Data processing techniques, including automated cloudcover assessment, control point library build system, radiometric calibration, and geometric correction are discussed.

Smith, P. L., Jr.↗
NASA NTRS2004

Laboratory Measurement of Bidirectional Reflectance of Radiometric Tarps

This experiment measured the reflectance of tarps with ground instruments in order to check radiometric calibration, validate atmospheric correction, and predict at-sensor radiance for satellite instruments. The procedure of this experiment is as follows: 1) Assemble laboratory apparatus to duplicate ground reference measurement geometry and satellite measurement geometry; 2) Measure spectral radiance with Optronics OL 750 double monochromator/spectroradiometer; 3) Measure radiance of NIST-calibrated Spectralon panel irradiated by collimated light at incidence angle of calibrated reflectance (20 deg, 30 deg, 40 deg, or 50 deg), viewing normal to panel surface; 4) Measure radiance of Spectralon panel irradiated at incidence angle equal to solar zenith angle at time of overpass; 5) Calculate reflectance of Spectralon panel irradiated at solar zenith angle, viewing normal to panel surface (ground geometry).

Knowlton, Kelly↗
NASA NTRS2017

Evaluation of Sentinel-1A Data For Above Ground Biomass Estimation in Different Forests in India

Use of remote sensing data for mapping and monitoring of forest biomass across large spatial scales can aid in addressing uncertainties in carbon cycle. Earlier, several researchers reported on the use of Synthetic Aperture Radar (SAR) data for characterizing forest structural parameters and the above ground biomass estimation. However, these studies cannot be generalized and the algorithms cannot be applied to all types of forests without additional information on the forest physiognomy, stand structure and biomass characteristics. The radar backscatter signal also saturates as forest parameters such as biomass and the tree height increase. It is also not clear how different polarizations (VV versus VH) impact the backscatter retrievals in different forested regions. Thus, it is important to evaluate the potential of SAR data in different landscapes for characterizing forest structural parameters. In this study, the SAR data from Sentinel-1A has been used to characterize forest structural parameters including the above ground biomass from tropical forests of India. Ground based data on tree density, basal area and above ground biomass data from thirty-eight different forested sites has been collected to relate to SAR data. After the pre-processing of Sentinel 1-A data for radiometric calibration, geo-correction, terrain correction and speckle filtering, the variability in the backscatter signal in relation tree density, basal area and above biomass density has been investigated. Results from the curve fitting approach suggested exponential model between the Sentinel-1A backscatter versus tree density and above ground biomass whereas the relationship was almost linear with the basal area in the VV polarization mode. Of the different parameters, tree density could explain most of the variations in backscatter. Both VV and VH backscatter signals could explain only thirty and thirty three percent of variation in above biomass in different forest sites of India. Results also suggested saturation of the Sentinel-1A backscatter signal around hundred tonnes per hectare for VV polarization and one hundred and forty five tonnes per hectare for VH polarization. The presentation will highlight the above results in addition to potentials and limitations of Sentinel-1A data for retrieving forest structural parameters. Also, background information on different forest types of India, biomass variations and forest type mapping efforts in the region will be presented.

Data↗
NASA NTRS1996

(abstract) Radiometric Calibration of the Multi-angle Imaging Spectro-Radiometer

The EOS/MISR instrument has completed preflight calibration and characterization of its nine cameras. The radiometric calibration requirements includes absolute radiometric accuracy to 3 percent. To meet this challenging requirement MISR has employed detector based calibration methodology. The source, a 1.65 m integrating sphere, is spatially and spectrally featureless. Thus, when viewing scenes that are likewise homogeneous, the sensor incident radiance is easily retrieved to high accuracy. To enhance the radiance product for arbitrary scene types, however, MISR is planning to incorporate spectral out-of-band, point-spread function deconvolution, and pixel nonuniformity of response corrections. A summary of the preflight calibration is presented in this paper, as well as the error uncertainties for specific scene types with and without these processing corrections.

radiometric calibration EOS MISR↗
NASA NTRS1990

Optical depth measurements and atmospheric correction of remotely sensed data for FIFE

Data derived from an airborne tracking-sun photometer are used to provide quantitative corrections for atmospheric effects in remotely sensed data. The atmospheric correction involves the validation of radiometric and atmospheric measurements and the application of single scattering approximation which permits the separation of Rayleigh scattering from aerosol scattering. Sun-photometer data are used to generate plots of spectral optical depths, aerosol size distributions, aerosol phase functions, and aerosol single-scattering albedos. The atmospheric correction model and the atmospheric optical properties are incorporated into a program which is applied to two flightlines of data. Atmospheric corrections tested on remotely sensed data permitted the removal of limb brightening, although the results require verification by means of ground measurements.

Wrigley, R. C.↗
NASA NTRS1978

Development of a drift-correction procedure for a photoelectric spectrometer

A technique has been developed to automatically correct for drifts in the radiometric sensitivity of the detector channels in a direct-reading emission spectrometer. The method utilizes a 1000 W tungsten-halogen reference lamp to illuminate the detectors through the same optical path as that traversed during the analysis of the sample. Detector channel responses to the light are compared to those for the same light intensity at the time of analytical calibration. This corrects for the drift. It is noted that with the exception of positioning the lamp, the procedure is fully automatic.

Chapman, G. B., II↗
NASA NTRS1972

The image-processing system for the Earth Resources Technology Satellite.

Description of the image-processing system for the Earth Resources Technology Satellite (ERTS), which will process video-tape recordings received from the satellite into imagery and digitized video data suitable for earth-resource study and analysis. The system is made up of three subsystems. The bulk processor produces 70-mm images and digitized records, corrected for systematic geometric and radiometric errors as well as for sensor-calibration and other errors. The precision processor modifies the bulk images to significantly increase geometric precision. The special processor transfers either bulk or precision data to computer-compatible tape.

Johnson, R. H.↗
NASA NTRS1981

Evaluation of HCMM data for assessing soil moisture and water table depth

Soil moisture in the 0-cm to 4-cm layer could be estimated with 1-mm soil temperatures throughout the growing season of a rainfed barley crop in eastern South Dakota. Empirical equations were developed to reduce the effect of canopy cover when radiometrically estimating the soil temperature. Corrective equations were applied to an aircraft simulation of HCMM data for a diversity of crop types and land cover conditions to estimate the soil moisture. The average difference between observed and measured soil moisture was 1.6% of field capacity. Shallow alluvial aquifers were located with HCMM predawn data. After correcting the data for vegetation differences, equations were developed for predicting water table depths within the aquifer. A finite difference code simulating soil moisture and soil temperature shows that soils with different moisture profiles differed in soil temperatures in a well defined functional manner. A significant surface thermal anomaly was found to be associated with shallow water tables.

Moore, D. G.↗