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NASA NTRS2005

Impact of the Sun on Remote Sensing of Sea Surface Salinity from Space

The sun is a sufficiently strong source of radiation at L-band to be an important source of interference for radiometers on future satellite missions such as SMOS, Aquarius, and Hydros designed to monitor soil moisture and sea surface salinity. Radiation from the sun can impact passive remote sensing systems in several ways, including line-of-sight radiation that comes directly from the sun and enters through antenna side lobes and radiation that is reflected from the surface to the radiometer. Examples are presented in the case of Aquarius, a pushbroom radiometer with three beams designed to monitor sea surface salinity. Near solar minimum, solar contamination is not a problem unless the sun enters near the main beam. But near solar maximum, contamination from the sun equivalent to a change of salinity on the order of 0.1 psu can occur even when the signal enters in sidelobes far from the main beam.

COMPONENT REPORTS↗

NASA NTRS2001

Validation of Surface Bio-Optical Properties in the Gulf of Maine as a Means for Improving Satellite Primary Production Estimates

One of the greatest challenges in providing sea-truth data for various ocean color sensors is climatology. This is particularly true in the Gulf of Maine since it is cloudy and foggy more than it is clear; the climatology shows on average, about one in four to five days has clear skies with clear days slightly more frequent in the late summer and early fall. Our strategy has been to use a ship of opportunity where one has choice of the sampling days. This provides much better flexibility to sample during clear periods with good satellite coverage. Our Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) contract has been to use the M/S Scotia Prince ferry as a ship of opportunity, running between Portland, Maine and Yarmouth, NS. Measurements include continuous, surface, along-track fluorescence, two independent measures of backscattering, total light scattering, absorption, beam attenuation, above-water remote sensing reflectance, calcite-dependent light scattering, temperature, and salinity. Expendable bathythermography (XBT) drops allow acquisition of vertical temperature information, useful for defining isopycnal slope, which affects primary production. These data are comparable to a previous program from early 1982, where a ship of opportunity program (SOOP) was run on the truck ferry, M/V Marine Evangeline, which ran along the same transect. These surface data were combined with satellite-derived sea surface temperature fields to examine the Maine coastal current. Unfortunately, this program stopped in 1982. The ongoing SIMBIOS results will dovetail nicely with the previous work (which also had Coastal Zone Color Scanner (CZCS) coverage) for looking at any long-term changes in the Gulf of Maine hydrography, bio-optics, and biogeochemistry.

Balch, William M.↗

NASA NTRS1984

Atmospheric Effects on Remote Sensing of the Earth's Surface

The main causes and magnitude of the atmospheric effects on remote sensing of the Earth's surface are determined. Theoretical study as well as measurements are included. The knowledge gained from this study will be used to develop atmospheric correction algorithms and to test them with satellite data. In a theoretical investigation of the relative effects of the aerosol optical thickness, absorption, and size distribution on remote sensing, it was found that aerosol absorption has a significant effect on satellite measurements of surface reflectivity. The absorption effect is stronger for high than for low surface reflectances. The aerosol optical thickness is dominant for small surface reflectances. The accuracy of clustering algorithms depends on both parameters. The vegetation index, however, is affected by the optical thickness but only weakly affected by the absorption. A laboratory simulation of the atmospheric effect on the radiance of sunlight scattered from the Earth's surface-atmosphere system was performed. This experiment verified the existence of the adjacency effect (the effect of a bright field on the radiance detected above a dark field) and was used to test 3-D radiative transfer models. In a theoretical study it was found that atmospheric scattering resulting from the adjacency effect reduces the separability between surface classes.

Fraser, R. E.↗

NASA NTRS2023

Radiative interaction of atmosphere and surface: write up with elements of code

In passive satellite remote sensing of the Earth, separation of the path radiance (atmosphere-only contribution) from the surface reflection remains a “significant challenge”. Recent literature names it among the gaps in radiative transfer (RT) topics that “require continued research in the near future”. The challenge comes from multiple reflections (bouncing) between the atmosphere and surface – radiative interaction. In this paper we use a known RT technique, the matrix-operator method (MOM), and a new modification of the monochromatic vector RT (vRT) code IPOL (Intensity and POLarization) to simulate the interaction of a plane-parallel atmosphere and a few widely used surface reflection models. Following the idea of the Green’s function method, IPOL no longer takes the surface model parameters on input. Instead, it provides the path radiance, and the atmospheric reflection and transmission matrices as output. Despite many RT codes use the MOM formalism, this output does not seem common. The surface reflection matrix is computed externally. Therefore, this paper extends the Green’s function atmospheric correction technique to the case of polarized light. Aiming clarity rather than performance, we explain in Python the structure of the surface matrices for the isotropic (Lambertian), directional unpolarized, and polarized ocean reflection models. We then combine these surface matrices and the precomputed IPOL output to get numerically accurate signal at the top of atmosphere (TOA) and test it vs. published benchmarks. Then, for each benchmark scenario we show how to get the surface from the TOA signal, i.e. perform the RT-based atmospheric correction.

radiative transfer↗

NASA NTRS2001

Estimating Expressed Temperature and Fractional Area of Hot Lava at the Kilauea Vent with AVIRIS Spectral Measurements

Imaging spectroscopy offers a framework based in physics and chemistry for scientific investigation of a wide range of phenomena of interest in the Earth environment. In the scientific discipline of volcanology knowledge of lava temperature and distribution at the surface provides insight into the volcano status and subsurface processes. A remote sensing strategy to measure surface lava temperatures and distribution would support volcanology research. Hot targets such as molten lava emit spectral radiance as a function of temperature. A figure shows a series of Planck functions calculated radiance spectra for hot targets at different temperatures. A maximum Lambertian solar reflected radiance spectrum is shown as well. While similar in form, each hot target spectrum has a unique spectral shape and is distinct from the solar reflected radiance spectrum. Based on this temperature-dependent signature, imaging spectroscopy provides an innovative approach for the remote-sensing-based measurement of lava temperature. A natural site for investigation of the measurement of lava temperature is the Big Island of Hawaii where molten lava from the Kilauea vent is present at the surface. In the past, Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data sets have been used for the analysis of hot volcanic targets and hot burning fires. The research presented here builds upon and extends this earlier work. The year 2000 Hawaii AVIRIS data set has been analyzed to derive lava temperatures taking into account factors of fractional fill, solar reflected radiance, and atmospheric attenuation of the surface emitted radiance. The measurements, analyses, and current results for this research are presented here.

Green, Robert O.↗

NASA NTRS1982

Calibration procedures for measurement of reflectance factor in remote sensing field research

A means by which measurements of the optical properties of crops and soils can be knowledgeably compared from site to site and instrument to instrument is presented in detail. The definition of bidirectional reflectance factor is reviewed and discussed. Procedures for field implementation are illustrated and discussed. Spectral and goniometric properties of laboratory and field reference surfaces are given. It is concluded that intelligent use of the bidirectional reflectance factor technique is an accurate and practical means to obtain the spectral, optical properties of crops and soils needed for advancements in agricultural remote sensing.

Robinson, B. F.↗

NASA NTRS1977

Characterization and Distribution of Lunar Mare Basalt Types Using Remote Sensing Techniques

The types of basal to be found on the moon were identified using reflectance spectra from a variety of lunar mare surfaces and craters as well as geochemical interpretations of laboratory measurements of reflectance from lunar, terrestrial, and meteoritic samples. Findings indicate that major basaltic units are not represented in lunar sample collections. The existence of late stage high titanium basalts is confirmed. All maria contain lateral variations of compositionally heterogenous basalts; some are vertically inhomogenous with distinctly different subsurface composition. Some basalt types are spectrally gradational, suggesting minor variations in composition. Mineral components of unsampled units can be defined if spectra are obtained with sufficient spectral coverage (.3 to 2.5 micron m) and spatial resolution (approximating .5 km).

Pieters, C.↗

NASA NTRS2018

Harmonized Landsat/Sentinel-2 Products for Land Monitoring

The Harmonized Landsat-8 and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a seamless, harmonized surface reflectance record from the Operational Land Imager (OLI) and Multi-Spectral Instrument (MSI) aboard Landsat-8 and Sentinel-2 remote sensing satellites, respectively. The HLS products are based on a set of algorithms to obtain seamless products from both sensors (OLI and MSI): atmospheric correction, cloud and cloud-shadow masking, geographic co-registration and common gridding, bidirectional reflectance distribution function normalization and bandpass adjustment. As of version 1.3, the HLS v1.3 data set covers 9.12 million km2 and spans from first Landsat-8 data (2013) to present. HLS products provide near-daily surface reflectance information with a common geometric framework, and are suitable for a variety of agricultural and vegetation monitoring tasks, including analysis of crop type, condition, and phenology.

Masek, Jeffrey↗

NASA NTRS2024

A new spectrally-invariant approach to the remote sensing of inhomogeneous clouds

Current operational satellite retrievals of cloud optical and microphysical properties go back to the Nakajima-King technique developed at the end of the 1980s. This technique is based on library calculations for plane-parallel homogeneous clouds. It often works well for overcast skies but leads to substantial errors for inhomogeneous and broken cloud fields where the plane-parallel-geometry assumption is no longer valid. The basic concept of a new technique was first introduced in nuclear physics to quantify the critical conditions of reactors. Based on the eigenvalues of the radiative transfer equation, their approach provides a powerful means to parameterize the structure of 3D media. This parameterization was later successfully applied to relate surface reflectance spectra to 3D canopy structure and is known as the spectrally-invariant approximation. The proposed approach adapts this technique to the remote sensing of cloud properties such as droplet single scattering albedo and the average number of scatterings (which are the fundamental parameters in radiative transfer theory), with an emphasis on quantifying the associated errors and uncertainties. This retrieval is free from the plane-parallel homogeneous cloud assumption.

clouds↗

NASA NTRS2010

Satellite Gravimetry Applied to Drought Monitoring

Near-surface wetness conditions change rapidly with the weather, which limits their usefulness as drought indicators. Deeper stores of water, including root-zone soil wetness and groundwater, portend longer-term weather trends and climate variations, thus they are well suited for quantifying droughts. However, the existing in situ networks for monitoring these variables suffer from significant discontinuities (short records and spatial undersampling), as well as the inherent human and mechanical errors associated with the soil moisture and groundwater observation. Remote sensing is a promising alternative, but standard remote sensors, which measure various wavelengths of light emitted or reflected from Earth's surface and atmosphere, can only directly detect wetness conditions within the first few centimeters of the land s surface. Such sensors include the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) C-band passive microwave measurement system on the National Aeronautic and Space Administration's (NASA) Aqua satellite, and the combined active and passive L-band microwave system currently under development for NASA's planned Soil Moisture Active Passive (SMAP) satellite mission. These instruments are sensitive to water as deep as the top 2 cm and 5 cm of the soil column, respectively, with the specific depth depending on vegetation cover. Thermal infrared (TIR) imaging has been used to infer water stored in the full root zone, with limitations: auxiliary information including soil grain size is required, the TIR temperature versus soil water content curve becomes flat as wetness increases, and dense vegetation and cloud cover impede measurement. Numerical models of land surface hydrology are another potential solution, but the quality of output from such models is limited by errors in the input data and tradeoffs between model realism and computational efficiency. This chapter is divided into eight sections, the next of which describes the theory behind satellite gravimetry. Following that is a summary of the GRACE mission and how hydrological information is gleaned from its gravity products. The fourth section provides examples of hydrological science enabled by GRACE. The fifth and sixth sections list the challenging aspects of GRACE derived hydrology data and how they are being overcome, including the use of data assimilation. The seventh section describes recent progress in applying GRACE for drought monitoring, including the development of new soil moisture and drought indicator products, and that is followed by a discussion of future prospects in satellite gravimetry based drought monitoring.

Rodell, Matthew↗

NASA NTRS1992

The influence of grazing on surface climatological variables of tallgrass prairie

Mass and energy exchange between most grassland canopies and the atmosphere are mediated by grazing activities. Ambient temperatures can be increased or decreased by grazers. Data have been assembled from simulated grazing experiments on Konza Prairie Research Natural Area and observations on adjacent pastures grazed by cattle show significant changes in primary production, nutrient content, and bidirectional reflectance characteristics as a function of grazing intensity. The purpose of this research was to provide algorithms that would allow incorporation of grazing effects into models of energy budgets using remote sensing procedures. The approach involved: (1) linking empirical measurements of plant biomass and grazing intensities to remotely sensed canopy reflectance, and (2) using a higher resolution, mechanistic grazing model to derive plant ecophysiological parameters that influence reflectance and other surface climatological variables.

Seastedt, T. R.↗

NASA NTRS2019

Modeling Atmosphere-Ocean Radiative Transfer: A PACE Mission Perspective

The research frontiers of radiative transfer (RT) in coupled atmosphere-ocean systems are explored to enable new science and specifically to support the upcoming Plankton, Aerosol, Cloud ocean Ecosystem (PACE) satellite mission. Given (i) the multitude of atmospheric and oceanic constituents at any given moment that each exhibits a large variety of physical and chemical properties and (ii) the diversity of light-matter interactions (scattering, absorption, and emission), tackling all outstanding RT aspects related to interpreting and/or simulating light reflected by atmosphere-ocean systems becomes impossible. Instead, we focus on both theoretical and experimental studies of RT topics important to the science threshold and goal questions of the PACE mission and the measurement capabilities of its instruments. We differentiate between (a) forward (FWD) RT studies that focus mainly on sensitivity to influencing variables and/or simulating data sets, and (b) inverse (INV) RT studies that also involve the retrieval of atmosphere and ocean parameters. Our topics cover (1) the ocean (i.e., water body): absorption and elastic/inelastic scattering by pure water (FWD RT) and models for scattering and absorption by particulates (FWD RT and INV RT); (2) the air-water interface: variations in ocean surface refractive index (INV RT) and in whitecap reflectance (INV RT); (3) the atmosphere: polarimetric and/or hyperspectral remote sensing of aerosols (INV RT) and of gases (FWD RT); and (4) atmosphere-ocean systems: benchmark comparisons, impact of the Earth's sphericity and adjacency effects on space-borne observations, and scattering in the ultraviolet regime (FWD RT). We provide for each topic a summary of past relevant (heritage) work, followed by a discussion (for unresolved questions) and RT updates.

Chowdhary, Jacek↗

NASA NTRS1989

Simple models for complex natural surfaces - A strategy for the hyperspectral era of remote sensing

A two-step strategy for analyzing multispectral images is described. In the first step, the analyst decomposes the signal from each pixel (as expressed by the radiance or reflectance values in each channel) into components that are contributed by spectrally distinct materials on the ground, and those that are due to atmospheric effects, instrumental effects, and other factors, such as illumination. In the second step, the isolated signals from the materials on the ground are selectively edited, and recombined to form various unit maps that are interpretable within the framework of field units. The approach has been tested on multispectral images of a variety of natural land surfaces ranging from hyperarid deserts to tropical rain forests. Data were analyzed from Landsat MSS (multispectral scanner) and TM (Thematic Mapper), the airborne NS001 TM simulator, Viking Lander and Orbiter, AIS, and AVRIS (Airborne Visible and Infrared Imaging Spectrometer).

Adams, John B.↗

NASA NTRS1985

Characterizing terrestrial ecosystems and productivity from remote sensing data

Predictive relationships were studied between the leaf area index (LAI) of temperate coniferous forests and the canopy of reflective properties as sensed by satellites. Also, the relationship was examined between this sensible variable, LAI, and functional properties such as net primary productivity (NPP) and nitrogen mineralization. Leaf surface area is a locus of many important material and energy exchanges. If LAI can be reasonably estimated from remote sensing measurements, then it could be used with models to predict evapotranspiration, radiation interception, precipitation interception, and other ecosystem processes over large areas. Nineteen mature closed canopy forest stands were measured for leaf area index distributed along a temperature moisture gradient across Oregon. The LAI varies from 15.4 to 0.6. Infrared radiation is strongly scattered by leaves so that it penetrates deeply and its reflectance is proportional to LAI. Red radiation is strongly absorbed by chlorophyll and its reflectance is inversely related to LAI, becoming asymptotic at LAI values of about 3. The ratio of infrared to red radiation compensates for irradiance variations across this transect.

Peterson, David L.↗

NASA NTRS1984

Active airborne infrared laser system for identification of surface rock and minerals

Emissivity and reflectivity in the thermal infrared spectral region (8-13 microns) may be used to discriminate among rocks and minerals. Although considerable success has been achieved in remote sensing classification of rock types based on emissivity measurements made with NASA's Thermal Infreared Multispectral Scanner (TIMS), classification based on reflectivity offers several advantages: much narrower bandwidths are used, higher signal to noise ratios are possible, and measurements are little affected by surface temperature. As a demonstration, an airborne CO2 laser instrument was flown along the margin of Death Valley, California. Measurements of spectral reflectance collected with this device were compared with emissivity measurements made with the TIMS. Data from either instrument provided the means for recognizing boundaries between geologic units including different rock types and fan surfaces of different ages.

Kahle, A. B.↗

NASA NTRS1990

Use of high-dimensional spectral data to evaluate organic matter, reflectance relationships in soils

Recent breakthroughs in remote sensing technology have led to the development of a spaceborne high spectral resolution imaging sensor, HIRIS, to be launched in the mid-1990s for observation of earth surface features. The effects of organic carbon content on soil reflectance over the spectral range of HIRIS, and to examine the contributions of humic and fulvic acid fractions to soil reflectance was evaluated. Organic matter from four Indiana agricultural soils was extracted, fractionated, and purified, and six individual components of each soil were isolated and prepared for spectral analysis. The four soils, ranging in organic carbon content from 0.99 percent, represented various combinations of genetic parameters such as parent material, age, drainage, and native vegetation. An experimental procedure was developed to measure reflectance of very small soil and organic component samples in the laboratory, simulating the spectral coverage and resolution of the HIRIS sensor. Reflectance in 210 narrow (10 nm) bands was measured using the CARY 17D spectrophotometer over the 400 to 2500 nm wavelength range. Reflectance data were analyzed statistically to determine the regions of the reflective spectrum which provided useful information about soil organic matter content and composition. Wavebands providing significant information about soil organic carbon content were located in all three major regions of the reflective spectrum: visible, near infrared, and middle infrared. The purified humic acid fractions of the four soils were separable in six bands in the 1600 to 2400 nm range, suggesting that longwave middle infrared reflectance may be useful as a non-destructive laboratory technique for humic acid characterization.

Henderson, T. L.↗

NASA NTRS2000

Fusion of AIRSAR and TM Data for Parameter Classification and Estimation in Dense and Hilly Forests

The expanded remotely sensed data space consisting of coincident radar backscatter and optical reflectance data provides for a more complete description of the Earth surface. This is especially useful where many parameters are needed to describe a certain scene, such as in the presence of dense and complex-structured vegetation or where there is considerable underlying topography. The goal of this paper is to use a combination of radar and optical data to develop a methodology for parameter classification for dense and hilly forests, and further, class-specific parameter estimation. The area to be used in this study is the H. J. Andrews Forest in Oregon, one of the Long-Term Ecological Research (LTER) sites in the US. This area consists of various dense old-growth conifer stands, and contains significant topographic relief. The Andrews forest has been the subject of many ecological studies over several decades, resulting in an abundance of ground measurements. Recently, biomass and leaf-area index (LAI) values for approximately 30 reference stands have also become available which span a large range of those parameters. The remote sensing data types to be used are the C-, L-, and P-band polarimetric radar data from the JPL airborne SAR (AIRSAR), the C-band single-polarization data from the JPL topographic SAR (TOPSAR), and the Thematic Mapper (TM) data from Landsat, all acquired in late April 1998. The total number of useful independent data channels from the AIRSAR is 15 (three frequencies, each with three unique polarizations and amplitude and phase of the like-polarized correlation), from the TOPSAR is 2 (amplitude and phase of the interferometric correlation), and from the TM is 6 (the thermal band is not used). The range pixel spacing of the AIRSAR is 3.3m for C- and L-bands and 6.6m for P-band. The TOPSAR pixel spacing is 10m, and the TM pixel size is 30m. To achieve parameter classification, first a number of parameters are defined which are of interest to ecologists for forest process modeling. These parameters include total biomass, leaf biomass, LAI, and tree height. The remote sensing data from radar and TM are used to formulate a multivariate analysis problem given the ground measurements of the parameters. Each class of each parameter is defined by a probability density function (pdf), the spread of which defines the range of that class. High classification accuracy results from situations in which little overlap occurs between pdfs. Classification results provide the basis for the future work of class-specific parameter estimation using radar and optical data. This work was performed in part by the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, and in part by the NASA Ames Research Center, Moffett Field, CA, both under contract from the National Aeronautics and Space Administration.

Moghaddam, Mahta↗

NASA NTRS1991

Surface scattering properties estimated from modeling airborne multiple emission angle reflectance data

Here, researchers apply the Hapke function to airborne bidirectional reflectance data collected over three terrestrial surfaces. The objectives of the study were to test the range of natural surfaces that the Hapke model fits and to evaluate model parameters in terms of known surface properties. The data used are multispectral and multiple emission angle data collected during the Geologic Remote Sensing Field Experiment (GRSFE) over a mud-cracked playa, an artificially roughened playa, and a basalt cobble strewn playa at Lunar Lake Playa in Nevada. Airborne remote sensing data and associated field measurements were acquired at the same time. The airborne data were acquired by the Advanced Solid State Array Spectroradiometer (ASAS) instrument, a 29-spectral band imaging system. ASAS reflectance data for a cobble-strewn surface and an artificially rough playa surface on Lunar Lake Playa can be explained with the Hanke model. The cobble and rough playa sites are distinguishable by a single scattering albedo, which is controlled by material composition; by the roughness parameter, which appears to be controlled by the surface texture and particle size; and the symmetry factor of the single particle phase function, which is controlled by particle size and shape. A smooth playa surface consisting of compacted, fine-grained particles has reflectance variations that are also distinct from either the cobble site or rough playa site. The smooth playa appears to behave more like a Lambertian surface that cannot be modeled with the Hapke function.

Guinness, Edward A.↗