Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “remote sensing surface reflectance”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

Inferring hemispherical reflectance of the earth's surface for global energy budgets from remotely sensed nadir or directional radiance values

The relationship between directional reflectances spanning the entire reflecting hemisphere and hemispherical reflectance (albedo) and the effect of solar zenith angle and cover type on these relationships were investigated, using the results obtained from NOAA's 7/8 AVHRR ground-level reflectance measurements. Bands 1 (0.58-0.6B microns) and 2 (0.73-1. 1 microns) were used for reflectance measurements of 11 natural vegetation surfaces ranging from bare soils to dense vegetation canopies. The results show that errors in inferring hemispherical reflectance from nadir reflectance can be between 11 and 45 percent for all cover types and solar angles, depending on the viewing angles. A technique is described in which a choice of two specific view angles reduces this error to less than 6 percent for both bands and for all sun angles and cover types.

Kimes, D. S.↗

Analysis of Vegetation and Atmospheric Correction Indices for Landsat Images

Vegetation and Atmospheric Indices are mathematical combinations of remote sensing bands which are useful in distinguishing the various values of the spectral reflectance. In this paper we study how the applications of various atmospherically corrected indices and vegetation indices can aide in retrieving the amount of surface reflectance from a remotely sensed image. Specifically, this paper studies and compares three vegetation indices and one atmospherically resistant index. These indices include the Normalized Difference Vegetation Index (NDVI), the Soil Adjusted Vegetation Index (SAVI), the Green Vegetation Index (GVI), and the Atmospherically Resistant Vegetation Index (ARVI), respectively. The algorithms attempt to estimate the optical characteristics of Thematic Mapper (TM) imagery. It will be shown that the NDVI algorithm followed by the ARVI correcting algorithm provided significant improvements in the tonal qualities of the retrieved images. The results are presented on 1987 TM images over the Kennedy Space Center (KSC) and are compared with a set of United States Geological Survey (U.S.G.S) maps.

Bush, Tasha R.↗

Atmosphere-biosphere exchange flux of carbon dioxide in a tallgrass prairie modeled with satellite spectral data

The estimation of the rate of net CO2 uptake of vegetated land surfaces is essential for studies of global carbon cycle. The present paper demonstrates the use of spectral reflectance data from satellite remote sensing to model net CO2 flux (NCF) of a tallgrass canopy at the Konza prairie, Kansas. A bidirectional reflectance canopy model was used to estimate seasonal changes in canopy leaf area index (LAI) from surface reflectances remotely sensed by SPOT 1 and Landsat 5 satellites. The radiation model was also coupled with leaf conductance-photosynthesis models to scale up stomatal conductance and NCF from individual leaves to canopy level according to radiation distribution inside the canopy. The satellite-data-driven model was able to closely simulate the seasonal change in LAI as well as the short-term variation of canopy LAI caused by the dry period during late July and early August in the area. Modeled canopy stomatal conductance (g(sub c)) and NCF agree with measurements within 0.16 cm/s and 0.28 mg m(exp -2)/s, respectively, during the growth season from late May to late August. In October both measured and modeled NCF turned to small negative values as canopy photosynthesis diminished and predicted LAI approached zero. In addition to data scatter, some of the differences between modeled and measured g(sub c) and NCF may be attributed to uncertainties in seasonal changes of plant physiological status that were not detected by satellite data; some of the differences were caused by inadequate description of the dependence of nighttime CO2 flux of soil respiration on near-surface turbulent mixing.

Gao, W.↗

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗

Identification of Terrestrial Reflectance From Remote Sensing

Correcting for atmospheric effects is an essential part of surface-reflectance recovery from radiance measurements. Model-based atmospheric correction techniques enable an accurate identification and classification of terrestrial reflectances from multi-spectral imagery. Successful and efficient removal of atmospheric effects from remote-sensing data is a key factor in the success of Earth observation missions. This report assesses the performance, robustness and sensitivity of two atmospheric-correction and reflectance-recovery techniques as part of an end-to-end simulation of hyper-spectral acquisition, identification and classification.

Alter-Gartenberg, Rachel↗

Thermal inertia imaging - A new geologic mapping tool

A thermal model of the earth's surface has been developed and used to determine the thermal inertia of a test site in the Mojave Desert, California. The model, which includes meteorological heating terms as well as radiation and conduction heating terms, is used with remotely sensed surface temperature and reflectance data to determine the thermal inertia of the surface materials at the test site. The thermal inertia is displayed in image form, and can aid in the differentiation of the various lithologic materials in the test site. Since this thermal property is representative of the upper several cm of the surface, it complements visible and reflected near-IR image data.

Kahle, A. B.↗

Optical polarimetry of particulate surfaces

Reflection polarimetry is a remote-sensing tool sensitive to the refractive index and microtexture of solid surfaces. Mechanisms producing linear polarization within a rough, porous, or particulate surface are discussed, and laboratory techniques for precise measurements are described in some detail. Polarimetry of atmosphereless solar-system bodies provides valuable indications of albedo for objects too small and distant for direct diameter determinations, and reveals that even quite small asteroids and satellites have particulate surfaces

Zellner, B.↗

Aerosol Models from the AERONET Database: Application to Surface Reflectance Validation Satellite Data

Aerosols play a critical role in radiative transfer within the atmosphere, and they have a significant impact on climate change. In this paper, we propose and implement a framework for developing an aerosol model using their microphysical properties. Such microphysical properties as the size distribution, the complex refractive index, and the percentage of sphericity are derived from the global AERosol RObotic NETwork (AERONET). These measurements, however, are typically retrieved when almucantar measurement procedures are performed (i.e., early mornings and late afternoons with clear sky) and might not have a temporal correspondence to a satellite overpass time, so a valid validation of satellite-derived products cannot be carried out. To address this problem of temporal inconsistency of satellite and ground-based measurements, we developed an approach to retrieve these microphysical properties (and the corresponding aerosol model) using the optical thickness at 440 nm, τ440, and the Ångström coefficient between 440 and 870 nm, α440–870. Such aerosol models were developed for 851 AERONET sites within the last 28 years. Obtained results suggest that empirically microphysical properties can be retrieved with uncertainties of up to 23 %. An exception is the imaginary part of the refractive index ni, for which the derived uncertainties reach up to 38 %. These specific parametric models of aerosol can be used for the studies when retrieval of microphysical properties is required as well as validation of satellite-derived products over land. Specifically, we demonstrate the usefulness of the aerosol models to validate surface reflectance records over land derived from optical remote sensing sensors. We then quantify the propagation of uncertainties in the surface reflectance due to uncertainties with the aerosol model retrieval that is used as a reference from radiative transfer simulations. Results indicate that individual aerosol microphysical properties can impact uncertainties in surface reflectance retrievals between 3.5 × 10(exp -5) to 1 × 10(exp -3) (in reflectance units). The overall impact of microphysical properties combined yields an overall uncertainty in surface reflectance <0.004 (in reflectance units). That corresponds, for example, to 1 to 3 % of the retrieved surface reflectance in the red spectral band (620–670 nm) by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. These uncertainty values are well below the specification (0.005 + 0.05ρ; ρ is the retrieved surface reflectance) used for the MODIS atmospheric correction.

Jean-Claude Roger↗

AVIRIS calibration using the cloud-shadow method

More than 90 percent of the signal at an ocean-viewing, satellite sensor is due to the atmosphere, so a 5 percent sensor-calibration error viewing a target that contributes but 10 percent of the signal received at the sensor may result in a target-reflectance error of more than 50 percent. Since prelaunch calibration accuracies of 5 percent are typical of space-sensor requirements, recalibration of the sensor using ground-base methods is required for low-signal target. Known target reflectance or water-leaving radiance spectra and atmospheric correction parameters are required. In this article we describe an atmospheric-correction method that uses cloud shadowed pixels in combination with pixels in a neighborhood region of similar optical properties to remove atmospheric effects from ocean scenes. These neighboring pixels can then be used as known reflectance targets for validation of the sensor calibration and atmospheric correction. The method uses the difference between water-leaving radiance values for these two regions. This allows nearly identical optical contributions to the two signals (e.g., path radiance and Fresnel-reflected skylight) to be removed, leaving mostly solar photons backscattered from beneath the sea to dominate the residual signal. Normalization by incident solar irradiance reaching the sea surface provides the remote-sensing reflectance of the ocean at the location of the neighbor region.

Carder, K. L.↗

The Application of Reflected GPS Signals to Ocean Remote Sensing

The L-band broadcast signal from the Global Positioning System (GPS) which has reflected off of the sea surface is under study for use as a ocean, coastal and wetlands remote sensing tool. The reflected signal from a given GPS satellite is cross-correlated with the pseudorandom noise code uniquely identifying that satellite. The shape of this cross-correlation, ordinarily a very sharp triangle when tracking a direct line of sight signal, becomes wider and smoother as the mean square slope of the reflecting surface increases. It is proposed that the surface wind speed can be determined by matching the recorded shape of this cross-correlation to that predicted by theoretical models as a function of wind speed and direction. The significance of these effects increases with altitude of the receiver. Experimental data have been collected using a specially modified GPS receiver on aircraft and on a balloon at altitudes of up to 25 km. These data compare favorably with predictions of analytical models and demonstrate the dependence of the waveform shape on surface wind speed and receiver altitude. The advantages that this measurement technique has over conventional scatterometers is the small size, low cost and simplicity of the receiver hardware, no requirement for a transmitter, and the ability to simultaneously collect data from usually 10 or more points (from a low earth orbiting satellite). This number could if the Russian GLONASS (Global Navigation Satellite System) satellites are also considered as additional sources of radiation. Furthermore, the bistatic scattering geometry is complementary to the backscatter used by conventional scatterometers.

Garrison, James L.↗

Remote sensing of soil moisture

The surface emissivity and reflectivity of soil are strong functions of its moisture content. Changes in emissivity, observed by passive microwave techniques (radiometry), and changes in reflectivity, observed by active microwave techniques (radar), can provide information on the moisture content of the 0 to 5 cm surface layer. In addition, the thermal inertia of the surface layer, which can be remotely sensed by observing the diurnal range of surface temperature, is an indicator of soil moisture content. The thermal infrared approach to remote sensing of soil moisture has little utility in the presence of cloud cover, but provides soil moisture data at high spatial resolutions and thermal data which are a potentially useful indicator of crop status. Microwave techniques can penetrate cloud covers. The passive technique has been demonstrated by both aircraft and spacecraft instruments, but spatial resolution is limited by the size of the antenna which can be flown. Active microwave systems offer the possibility of better spatial resolution, but have yet to be demonstrated from aircraft or spacecraft platforms.

Schmugge, T.↗

Polarbrdf: A General Purpose Python Package for Visualization Quantitative Analysis of Multi-Angular Remote Sensing Measurements

The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR). Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wild fire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

CAR↗

Remote detection of ocean features in the Lesser Antilles using ERTS-1 data

The author has identified the following significant results. Photographic data received from the ERTS-1 satellite over the Lesser Antilles Islands shows distinct ocean features on the leeward side of each island. Attempts to relate these features to ocean eddy formations with the aid of ground truth data proved unsuccessful. However, analysis of surface and upper air wind data correlate extremely well with the size, shape, and downwind extent of the ocean features. Studies to date indicate strongly that these features result from horizontal differences in sea surface roughness due to the wind shadow effect of the islands. The results suggest that horizontal variations in the reflectance of the sea surface will make remote sensing of the ocean mixed layer more difficult than previously anticipated. The surface reflection seems to be large enough to mask the smaller variations in backscattered energy from the mixed layer. Efforts to limit the effect of surface reflectance by photographic differencing of two MSS bands were unsuccessful. A supplementary study to enhance the energy reflected from the mixed layer through numerical differencing of ERTS-1 digital data is planned.

Hanson, K. J.↗

Remote detection of ocean features in the Lesser Antilles using ERTS-1 data

The author has identified the following significant results. Photographic data received from the ERTS-1 satellite over the Lesser Antilles Islands show distinct ocean features on the leeward side of each island. Attempts to relate these features to ocean eddy formations with the aid of ground truth data proved unsuccessful. However, surface and upper air wind data indicate a good correlation with the size, shape, and downwind extent of the ocean features. Studies to date indicate strongly that these features result from horizontal differences in sea surface roughness due to the wind shadow effect of the islands. The results suggest that horizontal variations in the reflectance of the sea surface will make remote sensing of the ocean mixed layer more difficult than previously anticipated. The surface reflection seems to be large enough to mask the smaller horizontal variations in backscattered energy from the mixed layer.

Hanson, K. J.↗

The detection by ERTS-1 of wind-induced ocean surface features in the lee of the Antilles Islands

Photographic data received from the ERTS-1 satellite over the Lesser Antilles Islands show distinct ocean features on the leeward side of each island. Attempts to relate these features to ocean eddy formations with the aid of ground truth data proved unsuccessful. However, surface and upper air wind data indicate a good correlation with the size, shape, and downwind extent of the ocean features. Studies to date indicate strongly that these features result from horizontal differences in a sea surface roughness due to the wind-shadow effect of the islands. The results suggest that horizontal variations in the reflectance of the sea surface will make remote sensing of the ocean mixed layer more difficult than previously anticipated. The surface reflection seems to be large enough to mask the smaller variations in backscattered energy from the mixed layer. Efforts to limit the effect of surface reflectance by photographic differencing of two multi-spectral scanner bands were unsuccessful.

Cram, R.↗

Clouds and Aerosols in the Climate System

Remote sensing of cloud and aerosol properties from space is reviewed for present and planned international satellite sensors. Techniques that are being used to enhance our ability to characterize the global distribution of cloud and aerosol properties include well-calibrated multispectral radiometers that rely on visible, near-infrared, and thermal infrared channels, sometimes including polarization as well. The availability of thermal channels to aid in cloud screening for aerosol properties is an important additional piece of information that has not always been incorporated into sensor designs. In this paper, we describe the radiative properties of clouds as currently determined from satellites (cloud fraction, optical thickness, cloud top pressure, and cloud effective radius), and highlight the global and regional cloud microphysical properties currently available for assessing climate variability and forcing. In addition, we will frustrate the radiative and microphysical properties of aerosol particles that are currently available from space-based observations, as well as enhancements to aerosol remote sensing over bright-reflecting surfaces that is anticipated in the next couple of years. Finally, we will describe the aerosol optical and radiative properties available from the globally distributed AERONET network of ground-based sun-sky radiometers.

King, Michael D.↗

Satellite Remote Sensing Studies of Biological and Biogeochemical Processing in the Ocean

The remote sensing of phycoerythrin-containing phytoplankton by ocean color was evaluated. Phycoerythrin (PE) can be remotely sensed by three methods: surface reflectance (Sathyendranath et al. 1994), by laser-activated fluorescence (Hoge and Swift 1986) and by passive fluorescence (Letelier et al. 1996). In collaboration with Dr. Frank Hoge and Robert Swift during Dr. Maria Vernet's tenure as Senior Visiting Scientist at Wallops Island, the active and passive methods were studied, in particular the detection of PE fluorescence and spectral reflectance from airborne LIDAR (AOL). Airborne instrumentation allows for more detailed and flexible sampling of the ocean surface than satellites thus providing the ideal platform to test model and develop algorithms than can later be applied to ocean color by satellites such as TERRA and AQUA. Dr. Vernet's contribution to the Wallops team included determination of PE in the water column, in conjunction with AOL flights in the North Atlantic Bight. In addition, a new flow-through fluorometer for PE determination by fluorescence was tested and calibrated. Results: several goals were achieved during this period. Cruises to the California Current, North Atlantic Bight, Gulf of Maine and Chesapeake Bay provided sampling under different oceanographic and optical conditions. The ships carried the flow-through fluorometer and samples for the determination of PE were obtained from the flow-through flow. The AOL was flown over the ship's track, usually several flights during the cruise, weather permitting.

Vernet, Maria↗