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A method for simultaneous integration of synthetic aperture radar (SAR) and optical remote sensing data in an estimation algorithm is presented which results in estimates of foliage mass over a larger range of values and more accurately than would be possible with either data type alone.
A technique for evaluating the construction of spectral reflectance curves from multispectral data obtained with the Viking lander cameras is presented. The multispectral data is limited to 6 channels in the wave-length range 0.4 to 1.1 microns, and several of the channels suffer from appreciable out-of-band response. The technique represents the estimated reflectance curves as a linear combination of known basic functions with coefficients determined to minimize the error in the representation, and it permits all channels, with and without out-of-band response, to contribute equally valid information. The technique is evaluated for known spectral reflectance curves of 8 materials felt likely to be present on the Martian surface. The technique provides an essentially exact fit if the the reflectance curve has no pronounced maxima and minima. Even if the curve has pronounced maxima and minima, the fit is good and reveals the most dominant features. Since only 6 samples are available some short period features are lost. This loss is almost certainly due to undersampling rather than out-of-band channel response.
As part of a multiyear project that monitored illness-related school closures, we conducted systematic daily online searches during July 27, 2020–June 30, 2022, to identify public announcements of COVID-19–related school closures (COVID-SCs) in the United States lasting ≥1 day. We explored the temporospatial patterns of COVID-SCs and analyzed associations between COVID-SCs and national COVID-19 surveillance data. COVID-SCs reflected national surveillance data: correlation was highest between COVID-SCs and both new PCR test positivity (correlation coefficient [r] = 0.73, 95% CI 0.56–0.84) and new cases (r = 0.72, 95% CI 0.54–0.83) during 2020–21 and with hospitalization rates among all ages (r = 0.81, 95% CI 0.67–0.89) during 2021–22. The numbers of reactive COVID-SCs during 2020–21 and 2021–22 greatly exceeded previously observed numbers of illness-related reactive school closures in the United States, notably being nearly 5-fold greater than reactive closures observed during the 2009 influenza (H1N1) pandemic.
Detailed synoptic views of the column ozone field can be obtained by the Spin-Scan Ozone Imager (SOI) (Keating et al., 1981) aboard the Dynamics Explorer I satellite. The eccentric polar orbit with an apogee altitude of 23,000 km allows high resolution global-scale images to be obtained within 12 minutes, and allows regions to be viewed for long periods of time. At perigee, a pixel size of nadir measurements of 3 km is possible, and measurements are determined using the backscattered ultraviolet technique. A wavelength measurement of 317.5 nm is used as there are limitations in filter locations and it allows comparison with Nimbus 7 SBUV/TOMS data. Consideration of the reflectivities of this data aids in checking the SOI data reduction algorithm. SOI data show short-term (less than one day) variations in the observed ozone field, and a negative correlation (greater than 0.9) between ozone and tropopause heights. It is expected, due to this correlation, that SOI data will aid in understanding the time evolution of dynamics near the tropopause.
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.
Using spatial-spectral data cubes of reflection nebulae obtained by ISOCAM, we have observed a shift in the central wavelength of the 7.7 micron band within several reflection nebulae. The band shifts progressively from approx. 7.8 microns near the edge of the nebulae to approx. 7.6 microns towards the center of the nebulae. The ratio of the 11.3/7.7 micron bands also changes with distance from the central star, first rising from the center towards the edge of the nebula, then falling at the largest distances from the star, consistent with the 11.3/7.7 micron band ratio being controlled by the PAH ionization state. The behavior of the 7.7 micron band center can be explained either by assuming that anions are the origin of the 7.85 micron band and cations the 7.65 micron band, or that the band center wavelength depends on the chemical nature of the PAHs.
Wavelength and angular dependence of reflectances and depolarization in the 9-11 micron region are reported for four standard targets: flowers of sulfur, flame-sprayed aluminum, 20-grit sandblasted aluminum, and 400-grit silicon carbon sandpaper. Measurements are presented and compared using a CW CO2 grating-tunable laser in a laboratory backscatter apparatus, an integrating sphere, and a coherent pulsed TEA-CO2 lidar system operating in the 9-11 micron region. Reflectance theory related to the use of hard targets to calibrate lidar atmospheric backscatter data is discussed.
Spectroradiometric data on the bidirectional reflectance function was collected for a cotton canopy as a function of observer zenith angle, observer angle, and solar zenith angle. The area under study was about 40 miles from the Gulf of Mexico and the prevailing winds blew inland such that cloud formation increased during the day. The standard reflectance panel was constructed of plywood that had been spray painted with a flat white latex paint. Physical and optical plant parameters were measured. A time lapse mechanism was constructed to operate a 16 mm movie camera such that single frames could be exposed at intervals of one per second up to one per hour. Data were digitized from a strip chart recorder and reflectance panel measurements.
Dataset revised on October 15, 2021. This revision adds sulfur and iron X-ray absorption near-edge structure spectra for the wetland soils and stream sediments from the field areas. It also renames the sample locations in a way that is more intuitive to readers of the companion paper that is under review. Finally, the data filenames and organization have been updated in their labeling to parallel the data sources in the associated paper. The abstract text and methods were also revised to reflect the data that was added to the dataset.Trace metals are essential for microbially-mediated biogeochemical processes occurring in anoxic wetland soils and stream bed sediments, such as denitrification, methanogenesis, and mercury methylation. Low availability of these elements may potentially inhibit key components of anaerobic carbon and nitrogen cycling and contaminant transformation. The solid-phase speciation of trace metals likely plays an important role in controlling their bioavailability. Metal speciation is well studied in contaminated soils and sediments as well as those naturally elevated in trace metals. However, less is known regarding the chemical forms of trace metals in systems having concentrations similar to geological background levels, the very settings where metal limitations may be most prevalent. We have investigated trace metal concentrations, extractability, and solid-phase speciation in three freshwater subsurface aquatic systems: marsh wetland soils, riparian wetland soils, and the sediments of a streambed.Data are provided for marsh wetland soils at Argonne National Laboratory, riparian wetland soils in the Tims Branch watershed at Savannah River National Laboratory, and stream bed sediments from East Fork Poplar Creek near Oak Ridge National Laboratory. Soil and sediment elemental abundances, mineralogy, and extractable nutrients as well as dissolved major elements, anions, trace metals, and nutrients in the overlying surface waters are provided. In addition, the results of sequential chemical extraction for the trace metals cobalt, nickel, copper, and zinc from the soils and sediment are reported as well as X-ray absorption near-edge structure (XANES) spectra in these materials are reported. To aid interpretation of these data, XANES spectra of sulfur in the soils and sediments as well as both XANES and extended X-ray absorption fine structure (EXAFS) spectra of iron in these materials are reported. The data package also includes the XANES spectra of reference standards and a potential interferent in the measurements. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units. Note that "u" is used in place of Greek lower case mu to indicate the micro prefix on units.
As of May 12, 2026 this dataset is currently being versioned to include data up to April 2026. Once the versioning process is complete, new data files will be available for access. The dataset metadata will also be updated to reflect the data availability of the new data being versioned. This dataset was collected at the UIC Plant Research Laboratory in Chicago, Illinois, as part of the Community Research on Climate and Urban Science (CROCUS) Urban Integrated Field Laboratory (UIFL) project, led by Argonne National Laboratory. The site provides continuous atmospheric flux measurements, focusing on CO₂, H₂O, and heat and momentum transport in an urban setting. The data is processed at 30 minutes interval using the Eddy Covariance method and includes quality control and diagnostic data generated by EddyPro software. The data is stored in the netCDF files following CF conventions. The UIC Plant Research Laboratory is located near major highways and urban infrastructure, including buildings and parking areas. The surrounding landscape consists of a mix of turf, plants, trees, and impervious surfaces such as concrete and asphalt, making it ideal for studying urban at for studies on urban sustainability, air quality, and the effects of urbanization on atmospheric processes on urban climate dynamics, air quality, and surface-atmosphere exchanges within the city of Chicago. This dataset is funded by the U.S. Department of Energy’s Office of Science, Biological and Environmental Research (BER) program.
As of April 9, 2026: this dataset is currently being versioned to include data up to March 31, 2026. Once the versioning process is complete, new data files will be available for access. The dataset metadata will also be updated to reflect the data availability of the new data being versioned. Raw atmospheric measurements collected at the University of Illinois Chicago (UIC) as part of the Community Research on Climate and Urban Science (CROCUS) project. The data includes high-frequency measurements of carbon dioxide (CO₂) concentration, water vapor (H₂O) concentration, wind speed (U, V, W components), temperature, and atmospheric pressure. These raw data are recorded by the LI-7500DS Open Path CO₂/H₂O Analyzer and a sonic anemometer at a 10 Hz acquisition frequency, providing the necessary inputs for calculating fluxes of CO₂, H₂O, heat, and momentum. In addition to gas concentration measurements, the dataset includes diagnostic information from the instruments, including absorptance, sample and reference signals, and diagnostic values. The data were collected to study urban atmospheric conditions and contribute to flux calculations for urban climate research. These measurements form the basis for calculating 30-minute average fluxes of key atmospheric variables using the eddy covariance method. This dataset provides critical raw input data for researchers interested in atmospheric fluxes, urban air quality, and the interaction between the urban environment and atmospheric processes. The data is part of the U.S. Department of Energy’s Biological and Environmental Research (BER) program, under the CROCUS Urban Integrated Field Laboratory (UIFL) project.
A technique was formulated for constructing spectral reflectance estimates from multispectral data obtained with the Viking lander cameras. The output of each channel was expressed as a linear function of the unknown spectral reflectance producing a set of linear equations which were used to determine the coefficients in a representation of the spectral reflectance estimate as a natural cubic spline. The technique was used to produce spectral reflectance estimates for a variety of actual and hypothetical spectral reflectances.
It is estimated that approximately 4-5% of national energy consumption can be saved through corrections to existing commercial building controls infrastructure and resulting improvements to efficiency. Correspondingly, automated fault detection and diagnostics (FDD) algorithms are designed to identify the presence of operational faults and their root causes. A diversity of techniques is used for FDD spanning physical models, black box, and rule-based approaches. A persistent challenge has been the lack of common datasets and test methods to benchmark their performance accuracy. This article presents a first of its kind public dataset with ground-truth data on the presence and absence of building faults. This dataset spans a range of seasons and operational conditions and encompasses multiple building system types. It contains information on fault severity, as well as data points reflective of the measurements in building control systems that FDD algorithms typically have access to. The data were created using simulation models as well as experimental test facilities, and will be expanded over time.
An effective, in-service health monitoring system is needed to track water condensation in real time through the walls of steam pipes. The system is required to measure the height of the condensed water from outside the pipe, while operating at temperatures that are as high as 250 C. The system needs to account for the effects of water flow and cavitation. In addition, it is desired that the system does not require perforating the pipes and thereby reducing the structural integrity. Generally, steam pipes are used as part of the district heating system carrying steam from central power stations under the streets to heat, cool, or supply power to high-rise buildings and businesses. This system uses ultrasonic waves in pulse-echo and acquires reflected signal data. Via autocorrelation, it determines the water height while eliminating the effect of noise and multiple reflections from the wall of the pipe. The system performs nondestructive monitoring through the walls of steam pipes, and automatically measures the height of condensed water while operating at the high-temperature conditions of 250 C. For this purpose, the ultrasonic pulse-echo method is used where the time-of-flight of the wave reflections inside the water are measured, and it is multiplied by the wave velocity to determine the height. The pulse-echo test consists of emitting ultrasonic wave pulses from a piezoelectric transducer and receiving the reflections from the top and bottom of the condensed water. A single transducer is used as a transmitter as well as the receiver of the ultrasonic waves. To obtain high resolution, a broadband transducer is used and the frequency can be in the range of 2.25 to 10 MHz, providing sharp pulses in the time domain allowing for higher resolution in identifying the individual reflections.
Surface reflectance retrieval from imaging spectrometer data as acquired with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has become important for quantitative analysis. In order to calculate surface reflectance from remotely measured radiance, radiative transfer codes such as 5S and MODTRAN2 play an increasing role for removal of scattering and absorption effects of the atmosphere. Accurate knowledge of the exo-atmospheric solar irradiance (E(sub 0)) spectrum at the spectral resolution of the sensor is important for this purpose. The present study investigates the impact of differences in the solar irradiance function, as implemented in a modified version of 5S (M5S), 6S, and MODTRAN2, and as proposed by Green and Gao, on the surface reflectance retrieved from AVIRIS data. Reflectance measured in situ is used as a basis of comparison.
Infrastructure of all types is fundamental to modern work and life. Computing for scientific work, especially, extends from distributed local research sites, often at the edges of other major systems, outward into globally connected high-performance facilities and infrastructures. This commentary reviews longstanding research on the social characteristics of infrastructure. We reflect on social concerns that affect the ongoing development, use, and maintenance of a wide range of scientific computing and data resources. Reflecting on the social nature of infrastructure is timely for Computing in Science & Engineering readers, given continued emphasis on developing even more expansive platforms for data and artificial intelligence work in science (e.g., the United States’ Genesis Mission). We assert that, regardless of technological advances, the complex nature of scientific research and data will require continued understanding of longstanding and nascent social practices across varied communities. This is fundamentally necessary to build and sustain usable infrastructure or platforms that can productively advance scientific research.
Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (approx. 2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified archive of the National Geospatial Intelligence Agency (NGA). For each continental area several million training pixels are derived by analysts using image segmentation algorithms and tools and then aggregated to the 30m resolution of Landsat. Here we will discuss the production/testing of this massive data set for Europe, North and South America and Africa, including assessments of the 2010 surface reflectance data. This type of analysis is only possible because of the availability of long term 30m data sets from GLS and shows much promise for integration of Landsat 8 data in the future.
The present model for soil bidirectional reflectance distribution functions in the visible and reflective IR ranges is based on a representation of soil surfaces by a collection of opaque spheres atop a Lambertian horizontal surface. The model is not sensitive to increases in the sphere area index beyond a value of 0.4. Observed soil reflectance factor data for a tilled field are noted to be consistent with those predicted by the model's expression of soil reflectance as a function of the horizontal area obscured by a sphere, the amount of surface in shadow, and relative brightness of a sphere, and the fraction of diffuse illumination.