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At least 145 records · Page 8

Remote sensing of sea surface temperature in the 3.7 micron CO2 band

The main sources of error in remote sensing of sea surface temperature are discussed. The interfering effects of reflected solar radiation, reflected thermal flux, clouds and haze and atmospheric attenuation are examined. The components of measured sea surface radiances, such as clear column radiance, surface emission, atmospheric emission, reflected thermal downward flux, and reflection of solar flux, are analytically presented. The use of the 3.7 micron region window to obtain the radiance to four percent accuracy is discussed. The advantages to be obtained by the use of narrow bandpass channels are assessed.

Chahine, M. T.↗

Geologic mapping using thermal images

Thermal radiance data from the Heat Capacity Mapping Mission (HCMM) satellite has been used to measure surface reflectance data and to provide additional material composition information through remote sensing. The primary goal was to investigate the utility of HCMM data for geologic applications. Three techniques were used for displaying and combining thermal and visible near infrared (VNIR) data for two desert areas in southern California (Trona and Pisgah): color additive composites (CAC) for day and night IR and day VNIR, principal components, and calculation of thermal inertia images. The HCMM thermal data were more effective than Landsat data in producing separation of compositionally different areas including volcanic and intrusive rocks. The satellite CAC data produced an image for a 1 x 2 degree area, and the color picture was enlarged to a scale of 1:250,000. Playa composition, moisture content, presence of standing water, and vegetation cover were displayed in a variety of colors according to physical characteristics. Areas such as sand dunes were not distinguishable because of the coarse 500-mm HCMM resolution. HCMM thermal data have shown a new dimension to geologic remote sensing, and future satellite missions should allow the continued development of the thermal infrared data for geology.

Abrams, M. J.↗

Imaging spectrometry: Aircraft and space program

Imaging spectrometry for the remote sensing of the Earth is introduced. Reflected solar energy from the surface is dispersed in a spectrometer and used to form up to 200 registered spectral images. Each pixel has associated with it sufficient information for the reconstruction of a complete reflectance spectrum. The technique allows the diagnostic narrow band spectral features that are characteristic of many surface materials to be used to identify those materials. These spectral features are typically 20 to 40 nm wide; spectral imaging systems which acquire data in contiguous 10 nm bands therefore have sufficient resolution for direct identification of those materials with diagnostic spectral bands.

Abrams, M. J.↗

Calibration of field reference panel and radiometers used in FIFE 1989

Remote sensing of the earth's surface features involves the measurement of reflected solar radiation and the interpretation of the data in biophysical terms. Reflected radiation is a function of the surface properties and incident solar irradiance. The amount of radiation reflected from a surface is compared to the amount of solar radiation received at the surface as a means of comparing information from different times of day as well as for different days of the year. Thus, it is imperative to calibrate the instruments used to measure the incoming and reflected radiation.

Blad, Blaine L.↗

Workshop on the Space Environment: The Effects on the Optical Properties of Airless Bodies

Reflectance spectrophotometry and polarimetry are major tools in remote sensing studies of surfaces of solar system bodies. The interpretations of such measurements are often based on laboratory studies of meteoritic, lunar, and terrestrial materials. However, the optical properties of regoliths are known to be affected by the space environment. Thus, some of the major questions addressed in the workshop include identity of the soil component responsible for alteration of the optical properties, the process that produced this component, and how reliably the effects of these processes could be extrapolated to other bodies of the solar system.

Hapke, B.↗

BOREAS RSS-20 POLDER C-130 Measurements of Surface BRDF

This Boreal Ecosystem-Atmosphere Study (BOREAS) Remote Sensing Science (RSS)-20 data set contains measurements of surface bidirectional reflectance distribution function (BRDF) made by the polarization and Directionality of Earth reflectances (POLDER) instrument over several surface types (pine, spruce, fen) of the BOREAS southern study area (SSA) during the 1994 intensive field campaigns (IFCs). Single-point BRDF values were acquired either from the NASA Ames Research Center (ARC) C-130 aircraft or from a NASA Wallops Flight Facility (WFF) helicopter. A related data set collected from the helicopter platform is available as is POLDER imagery acquired from the C-130. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Leroy, Marc↗

Chlorophyll- a dynamics in the lower Amazon River: insights from in situ and hyperspectral remote sensing using OCI-PACE

Chlorophyll-a concentration (Chla) is a key indicator of phytoplankton biomass and aquatic trophic status. However, satellite-derived Chla in sediment-rich waters, such as those found in the Lower Amazon River, remains challenging. The present study characterizes in situ Chla levels and their relationships with geographic, physical, and biogeochemical parameters in the Lower Amazon. Data collected between 2014 and 2017 across four hydrological seasons included measurements of Chla, remote sensing reflectance, and water quality parameters such as total suspended sediment, conductivity, water surface temperature, dissolved oxygen, pH, dissolved organic carbon and coloured dissolved organic matter. An empirical model was developed to estimate Chla using simulated hyperspectral bands from NASA’s PACE mission, achieving high performance (R 2 = 0.76; RMSE = 0.11 μg·L −1 ). Red bands proved particularly effective for Chla retrieval, while the addition of ultraviolet bands further enhanced model accuracy. The application of the developed model to satellite imagery yielded results consistent with in situ observations for the same hydrologic season. Seasonal variation and geographic location were major factors influencing Chla dynamics. This study provides a novel contribution to Chla estimation in optically complex, highly turbid waters and highlights the potential of the PACE mission to enhance global aquatic ecosystem monitoring. In conclusion, by offering freely available hyperspectral data with high radiometric resolution, PACE represents a significant advancement in the realm of remote sensing of aquatic environments.

Amazon River↗

A simple thermal model of the earth's surface for geologic mapping by remote sensing

Thermal inertia of the earth's surface can be used in geologic mapping as a complement to surface reflectance data as provided by Landsat. Thermal inertia cannot be determined directly but must be inferred from radiation temperature measurements (by thermal IR sensors) made at various times in the diurnal cycle, combined with a model of the surface heating processes. A model is developed which differs from those created previously for this purpose, because it includes sensible and latent heating. Tests of this model using field data indicate that it accurately determines the surface heating. When the model is used with field measurements of meteorological variables and is combined with remotely sensed temperature data, a thermal inertia image can be produced.

Kahle, A. B.↗

Remote sensing of vegetation at regional scales

Relations between spectroscopy and the concept of inferring surface cover type and condition from measurements of reflected or emitted radiation are examined, taking into account the observation of 'spectral signatures'. It has now become evident that the paradigm which had provided the basis for the spectroscopic identification of materials, is incomplete when applied to the inference of type and condition of materials in a natural environment. It was found that one could not collect a remote sensing signature from an unknown ground cover class at a particular time and place and match that signature with an a priori catalog value to infer the properties of the unknown cover class. The spectroscopy paradigm was, therefore, largely abandoned in favor of decision theoretic approaches. Attention is given to the temporal greenness profile feature space, the crop stage of development estimation using a temporal greenness profile, the temporal greenness profile for crop yield, and applications to regional scales.

Hall, F. G.↗

Thermal infrared emission spectroscopy of natural surfaces: Application to desert varnish coatings on rocks

Thermal infrared spectroscopy has become an increasingly important tool for remote compositional analysis and geologic mapping. Most published laboratory measurements have been obtained in bidirectional reflection or transmission, whereas remotely sensed thermal infrared data are obtained by measuring the emitted energy. Section 2 of this paper describes a laboratory technique for determining calibrated emissivities of natural surfaces. Equations are developed to account for the energy reflected from the environment and to determine directly the sample temperature from measurements of hot and cold blackbody targets. Two methods for determining emissivity are developed: one in which only a hot sample measurement is made and the reflected background energy is removed by modeling, and a second in which the sample is cooled and the reflected energy is measured directly. Relative emissivity can be obtained to approximately 1% and absolute emissivities can be obtained to 2-15%, depending on the validity of the assumption that the emissivity of the sample is unity at some wavelength. The emission data agree well within the hemispherically integrated reflection data but point out probelms associated with bidirectional reflectance measurements. Section 3 applies emissivity measurements to the study of layered surfaces consisting of desert varnish coatings on granite and granodiorite rock suites. Two linear models are developed: the first assumes linear mixing of independent emission from the substrate and varnish (checkerboard model); the second models tansmission through an absorbing/emitting medium. Regardless of whether the varnish is or is not relatively transparant and strongly absorptive, the spectral effect of varnish increases linearly with varnish thickness, indicating that thick patches of varnish dominate the spectral properties. As a result, medium varnish thickness can be determined from spectral measurements. In addition, the composition of a substrate can be estimated through varnish layers up to 40-50 micrometers in median thickness, and the composition of the varnish material can be determined if the substrate material is known. The varnishes studied are composed primarily of clay materials, consistent with previous studies of varnish composition.

Christensen, Philip R.↗

Remote sensing of sea state by laser altimeters

The reflection of short laser pulses from the ocean surface was analyzed based on the specular point theory of scattering. The expressions for the averaged received signal, shot noise and speckle induced noise were derived for a direct detection system. It is found that the reflected laser pulses have an average shape closely related to the probability density function associated with the surface profile. This result is applied to estimate the mean sea level and significant wave height from the receiver output of the laser altimeter.

Tsai, B.↗

Overview of atmospheric correction and radiometric calibration efforts during FIFE

The primary responsibility within the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) for understanding the radiometric properties of the remote sensing instrumentation and the atmospheric optical properties affecting measurements with these instruments rested within the atmospheric corrections and radiometric calibration subgroup of FIFE, called the correction/calibration group for short. Specific activities included (1) calibration of remote sensing instrumentation used on aircraft and surface platforms, (2) formulation of recommendations for calibrating data from satellite sensors, (3) measurement and analysis of atmospheric properties, (4) development and evaluation of radiative transfer algorithms which perform the atmospheric correction of remotely sensed data, and (5) derivation and evaluation of surface properties such as reflectances and temperatures. A review of the activities performed by this group and a discussion of the importance of these activities in retrieving surface parameters is presented here.

Halthore, Rangasayi N.↗

Microwave remote sensing of soil moisture

Knowledge of soil moisture is important to many disciplines, such as agriculture, hydrology, and meteorology. Soil moisture distribution of vast regions can be measured efficiently only with remote sensing techniques from airborne or satellite platforms. At low microwave frequencies, water has a much larger dielectric constant than dry soil. This difference manifests itself in surface emissivity (or reflectivity) change between dry and wet soils, and can be measured by a microwave radiometer or radar. The Microwave Sensors and Data Communications Branch is developing microwave remote sensing techniques using both radar and radiometry, but primarily with microwave radiometry. The efforts in these areas range from developing algorithms for data interpretation to conducting feasibility studies for space systems, with a primary goal of developing a microwave radiometer for soil moisture measurement from satellites, such as EOS or the Space Station. These efforts are listed.

Shiue, J. C.↗

EcoSpec: Highly Equipped Tower-Based Hyperspectral and Thermal Infrared Automatic Remote Sensing System for Investigating Plant Responses to Environmental Changes

Despite an advanced ability to forecast ecosystem functions and climate at regional and global scales, little is known about relationships between local variations in water and carbon fluxes and large-scale phenomena. To enable data collection of local-scale ecosystem functions to support such investigations, we developed the EcoSpec system, a highly equipped remote sensing system that houses a hyperspectral radiometer (350–2500 nm) and five optical and infrared sensors in a compact tower. Its custom software controls the sequence and timing of movement of the sensors and system components and collects measurements at 12 locations around the tower. The data collected using the system was processed to remove sun-angle effects, and spectral vegetation indices computed from the data (i.e., the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Photochemical Reflectance Index (PRI), and Moisture Stress Index (MSI)) were compared with the fraction of photochemically active radiation (fPAR) and canopy temperature. The results showed that the NDVI, NDWI, and PRI were strongly correlated with fPAR; the MSI was correlated with canopy temperature at the diurnal scale. These correlations suggest that this type of near-surface remote sensing system would complement existing observatories to validate satellite remote sensing observations and link local and large-scale phenomena to improve our ability to forecast ecosystem functions and climate. The system is also relevant for precision agriculture to study crop growth, detect disease and pests, and compare traits of cultivars.

47 OTHER INSTRUMENTATION↗

Influence of atmospheric aerosols and desert reflectance properties on satellite radiance measurements

The influence of surface bidirectional reflectance factors, including shadowing, and of atmospheric aerosol variability are modeled for their effects on the remote sensing of desert targets from space in the 0.7-micron region at high spatial resolution. The white sand reflectance data of Salomonson (1968) are used as the basis for the simulation. The effects of the surface bi-directional reflectance and atmospheric aerosol on the nadir-normalized reflectance measured at the satellite are discussed individually and jointly. The net influence of these two factors is shown to depend on the magnitude of other parameters, such as the surface reflectance and solar zenith angle.

Bowker, D. E.↗

Imaging Systems Provide Maps for U.S. Soldiers

Spanning nearly four decades, the remarkable Landsat program has continuously provided data about the Earth s surface, including detailed maps of vegetation, land use, forest extent and health, surface water, population distribution, as well as how these features have changed over time. Managed by NASA and the U.S. Geological Survey, Landsat s series of satellites obtain data through passive remote sensing, or the use of sensors to read the energy reflected or emitted from the Earth s surface. After the data from the sensors is processed and analyzed, it can be applied to create information-rich images of the planet. While the Landsat program has launched seven satellites since 1972, only Landsat 5 and 7 are currently operating. The next spacecraft in line to ensure continuity of data for years to come is the Landsat Data Continuity Mission (LDCM). Planned for launch in 2012, LDCM will take measurements of the Earth in visible, nearinfrared, shortwave infrared, and thermal infrared bands. In addition to widespread use for land use planning and monitoring on local to regional scales, support for disaster response and evaluations, as well as water use monitoring, LDCM measurements will directly serve NASA s research in the areas of climate, the carbon cycle, ecosystems, the water cycle, biogeochemistry, and Earth s surface and interior.

Source record↗

The Effect of Incident Light Polarization on Vegetation Bidirectional Reflectance Factor

The Laboratory-based Bidirectional Reflectance Factor (BRF) polarization study of vegetation is presented in this paper. The BRF was measured using a short-arc Xenon lamp/monochromator assembly producing an incoherent, tunable light source with a well-defined spectral bandpass at visible and near-infrared wavelengths of interest at 470 nm and 870 nm and coherent light source at 1.656 microns. All vegetation samples were measured using P and S linearly polarized incident light over a range of incident and scatter angles. By comparing these results, we quantitatively examine how the BRF of the samples depends on the polarization of the incident light. The differences are significant, depend strongly on the incident and scatter angles, and can be as high as 120% at 67 deg incident and 470nm. The global nature of Earth's processes requires consistent long-term calibration of all instruments involved in data retrieval. The BRF defines the reflection characteristics of Earth surface. It provides the reflectance of a target in a specific direction as a function of illumination and viewing geometry. The BRF is a function of wavelength and reflects the structural and optical properties of the surface. Various space and airborne radiometric and imaging remote sensing instruments are used in the remote sensing characterization of vegetation canopies and soils, oceans, or especially large pollution sources. The satellite data is validated through comparison with airborne, ground-based and laboratory-based data in an effort to fully understand the vegetation canopy reflectance, The Sun's light is assumed to be unpolarized at the top of the atmosphere; however it becomes polarized to some degree due to atmospheric effects by the time it reaches the vegetation canopy. Although there are numerous atmospheric correction models, laboratory data is needed for model verification and improvement.

Georgiev, Georgi T.↗

Distinguishing among tallgrass prairie cover types from measurements of multispectral reflectance

The heterogeneity in surface cover caused by management practices or natural events complicates monitoring the conditions of grasslands and assessing their productivity by remote sensing techniques. Statistical procedures were sought that would allow different grassland surface cover types (bare soil, senescent vegetation, and green vegetation) to be distinguished by using measurements of grassland multispectral reflectance. Two procedures, discriminant analysis and canonical discriminant analysis, were found suitable for achieving this objective. Linear classification functions and canonical variables were derived, which distinguish between the three cover types. A comparison between two sensor systems, a Barnes multiband radiometer and an Exotech radiometer that simulates the Landsat thematic mapper (TM) and multispectral scanner (MSS) bands, respectively, showed that the separability among the three cover types was substantially improved by the additional and improved spectral features of the Barnes radiometer.

Asrar, G.↗