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The dependence of sea surface directional reflectance on surface wind speed from space-based lidar measurements of sea surface backscatter. In particular lidar measurements in the nidir angle range from 10-30 degrees appear to be most sensitive to surface wind speed variability in the regime below 10m/s.
Reflected solar radiation polarization over land, sea and cloud surfaces to determine atmospheric pollution
Recent attempts to match shortwave albedo of snow for clear skies using approximate spectral solar fluxes and solutions of the radiative transfer equation for snow were unsuccessful until a separate surface reflection term was introduced. A separate consideration of specular reflection from surface snow grains has been objected to as being ad hoc. Results based on a new parameterization of shortwave radiation are discussed. Compared to the previous radiation models, new model gives higher diffuse insolation and predicts higher albedos. The difference between observed and predicted albedos is substantially reduced without invoking surface reflection.
The new generation geostationary (GEO) remote sensors (GOES-R ABI, Himawari AHI, and FY4 AGRI) provide high frequency (5-15 minute) observations spatially/spectrally similar to MODIS/VIIRS for land monitoring. These new features of GEO satellite sensors make producing MODIS like land products for terrestrial monitoring possible. The NASA Earth Exchange (NEX) team developed the GEONEX pipeline that is containerized, deployable on NASA Pleiades supercomputer as well as public cloud platforms (e.g. AWS). The processing pipeline is designed to take Himawari Standard Data (HSD) and GOES-16 L1b to generate surface reflectance (SR) and other high-level land remote sensing products. In order to produce low-Earth-orbiting (LEO) remote sensing compatible land products, inter-comparison between Himawari AHI and MODIS Terra/Aqua has been conducted in this research work. Comparisons of TOA reflectance and surface reflectance between AHI and Terra/Aqua are presented. Ray-Matching method was used to locate the co-located pixels, where GEO and LEO sensors look at the land target with similar Viewing Zenith Angle (VZA) and Viewing Azimuth Angle (VAA) simultaneously. Here, we address challenges associated with the selection of qualified pixels of similar solar illumination condition and atmosphere path. We used strict criterion to constrain the pixel selection: the time difference between GEO and LEO observations is less than +-2.5 mins, the cosine of VZA difference is less than 1%, and the VAA difference is less than 10 deg. We also discuss the strong radiometric consistency that the new generation GEO sensors along with the popular LEO sensors would benefit the environmental remote sensing community.
Knowledge of the directional reflectance properties of natural surfaces such as soils and vegetation canopies is essential for classification studies and canopy model inversion. Atmospheric correction schemes, using various levels of approximation, are described to retrieve surface bidirectional reflectance factors (BRFs) and directional-hemispherical reftectances (albedos)from multiangle radiance measurements taken at ground level. The retrieval schemes are tested on simulated data incorporating realistic surface BRFs and atmospheric models containing aerosols. Sensitivity of the atmospherically corrected BRFs and associated directional-hemispherical reflectances to various aerosol properties and the sun-view geometry is illustrated. A measurement strategy for obtaining highly accurate surface reflectance properties also is examined in the context of instrument radiametric calibration, knowledge of the atmospheric properties, and sun-view angular coverage.
Reflection of modulated helium and deuterium molecular beams from platinum surface
Reflection and focusing of sonic booms by two dimensional curved surfaces
Reflection characteristics of different surfaces used to determine properties essential for lunar type scattering
We study the Earth surface polarized reflectance using data collected by a space-based lidar. Accurate modelling of the surface reflectance supports retrieval algorithm development for the current and future Earth Science missions. Strong polarization of the laser light from Cloud-Aerosol Transport System (CATS) instrument, operated in 2015-2017, and nighttime measurements yield higher signal-to-noise ratio for polarization compared to the previous analysis of reflected, initially unpolarized, solar light.
An algorithm has been developed for estimating the surface reflectance functions of objects in a scene with incomplete knowledge of the spectral power distribution of the ambient light. An image processing system employing this algorithm can assign colors that are constant despite changes in the lighting of the scene; this capability is essential to correct color rendering in photography, TV, and in the construction of artificial visual systems for robotics. Attention is given to the way in which constraints on lights and surfaces in the environment make color-constancy possible for a visual system, and the algorithm's implications for human color vision are discussed.
Observations of the surface of Venus, carried out by the Pioneer Venus radar mapper at a wavelength of 17 centimeters, reveal a global mean reflectivity at normal incidence of 0.13 + or - 0.03. Over the surface, variations from a low of 0.03 + or - 0.01 to a high of 0.4 + or - 0.1 are found, with Theia Mons, previously identified as possibly volcanic, showing a value of 0.28 + or - 0.07. Regions of high reflectivity may consist of rocks with substantial inclusions of highly conductive sulfides.
Earth surfaces reflecting and polarizing properties in aerial reconnaissance
Preliminary results are discussed from an investigation into the effects of the solar zenith angle on the surface reflectances of cloud types being categorized in the International Satellite Cloud Climatology Project. The analysis is based on AVHRR channel one data at 0.6 micron over the period July 1983-July 1984. Subsatellite scenes of eight geographically separated targets distinguished by their predominant vegetation type were examined pixel-by-pixel. Attempts were made to discover any spatial variability index in each pixel to classify pixels representing clouds by the recorded brightness temperature.
Knowledge of the directional reflectance properties of natural surfaces such as soils and vegetation canopies is essential for classification studies and canopy model inversions. Atmospheric correction schemes, using various levels of approximation, are described to retrieve surface bidirectional reflectance factors (BRFs) and directional-hemispherical reflectances (albedos) from multi-angle radiance measurements taken at ground level.
The National Aeronautics and Space Administration (NASA) at Goddard Space Flight Center (GSFC) has developed a laser ranging device (LIDAR) which provides accurate and timely data of earth features. NASA/GSFC recently modified the sensor to include a scanning capability to produce LIDAR swaths. They have also integrated a Global Positioning System (GPS) and an Inertial Navigation System (INS) to accurately determine the absolute aircraft location and aircraft attitude (pitch, yaw, and roll), respectively. The sensor has been flown in research mode by NASA for many years. The LIDAR has been used in different configurations or modes to acquire such data as altimetry (topography), bathymetry (water depth), laser-induced fluorosensing (tracer dye movements, oil spills and oil thickness, chlorophyll and plant stress identification), forestry, and wetland discrimination studies. NASA and HARC are developing a commercial version of the instrument for topographic mapping applications. The next phase of the commercialization project will be to investigate other applications such as wetlands mapping and coastal bathymetry. In this paper we report on preliminary laboratory measurements to determine the feasibility of making accurate depth measurements in relatively shallow water (approximately 2 to 6 feet deep) using a LIDAR system. The LIDAR bathymetry measurements are relatively simple in theory. The water depth is determined by measuring the time interval between the water surface reflection and the bottom surface reflection signals. Depth is then calculated by dividing by the index of refraction of water. However, the measurements are somewhat complicated due to the convolution of the water surface return signal with the bottom surface return signal. Therefore in addition to the laboratory experiments, computer simulations of the data were made to show these convolution effects in the return pulse waveform due to: (1) water depth, and (2) changes in bottom surface reflectivity.
Disclosed herein is a method of determining the near angle scattering of a sample reflective surface comprising the steps of: a) splitting a beam of light having a coherence length of greater than or equal to about 2 meters into a sample beam and a reference beam; b) frequency shifting both the sample beam and the reference beam to produce a fixed beat frequency between the sample beam and the reference beam; c) directing the sample beam through a focusing lens and onto the sample reflective surface, d) reflecting the sample beam from the sample reflective surface through a detection restriction disposed on a movable stage; e) recombining the sample beam with the reference beam to form a recombined beam, followed by f) directing the recombined beam to a detector and performing heterodyne analysis on the recombined beam to measure the near-angle scattering of the sample reflective surface, wherein the position of the detection restriction relative to the sample beam is varied to occlude at least a portion of the sample beam to measure the near-angle scattering of the sample reflective surface. An apparatus according to the above method is also disclosed.
Spectral aerosol optical depths, surface hemispherical-directional reflectance factors, and bihemispherical reflectances (albedos) are retrieved for an area of Glacier National Park using spectral, multiangle imagery obtained with the airborne advanced solid state array spectroradiometer (ASAS). The retrieval algorithms are described and are identical in principle to those being devised for use by the multiangle imaging spectroradiometer (MISR) which will fly on the EOS-AMI spacecraft in 1998. As part of its science mission, MISR will produce global coverage of both aerosol amounts an an surface reflection properties. The results in this paper represent the initial effort in applying the MISR algorithms to real data. These algorithms will undergo additional testing and validation as more multiangle data become available.
This study introduces the Ames Global Hyperspectral Synthetic Data set (AGHSD), in particular the surface bidirectional reflectance distribution function (BRDF) product, to support the NASA Surface Biology and Geology (SBG) mission development. The data set is generated based on the corresponding multispectral BRDF products from NASA's MODIS satellite sensor. Based on theories of radiative transfer in vegetation canopies, we derive a simple but robust relationship that indicates that the hyperspectral surface BRDF can be accurately approximated as a weighted sum of the soil surface reflectance, the leaf single albedo, and the canopy scattering coefficient, where the weights or coefficients are spectrally invariant and thus readily estimated from the multispectral MODIS products. We validate the algorithm with simulations by a Monte Carlo Ray Tracing model and find the results highly consistent with the theoretic derivation. Using reflectance spectra of soil and vegetation derived from existing spectral libraries, we apply the algorithm to generate the AGHSD BRDF product at 1 km and 8-day resolutions for the year of 2019. The data set is biogeochemically and biogeophysically coherent and consistent, and serves the goal to support the SBG community in developing sciences and applications for the future global imaging spectroscopy mission.