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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Scanning thermal plumes

Over a three-year period 800 thermal line scans of power plant plumes were made by an airborne scanner, with ground truth measured concurrently at the plants. Computations using centered finite differences in the thermal scanning imagery show a lower bound in the horizontal temperature gradient in excess of 1.6 C/m. Gradients persist to 3 m below the surface. Vector plots of the velocity of thermal fronts are constructed by tracing the front motion in successive thermal images. A procedure is outlined for the two-point ground calibration of a thermal scanner from an equation describing the scanner signal and the voltage for two known temperatures. The modulation transfer function is then calculated by input of a thermal step function and application of digital time analysis techniques using Fast Fourier Transforms to the voltage output. Field calibration tests are discussed. Data accuracy is limited by the level of ground truth effort chosen.

Scarpace, F. L.↗
NASA NTRS1973

A study to explore the use of orbital remote sensing to determine native arid plant distribution

The author has identified the following significant results. A theory has been developed of a method for determining the reflectivities of natural areas from ERTS-1 data. This method requires the following measurements: (1) ground truth reflectivity data from two different calibration areas; (2) radiance data from ERTS-1 MSS imagery for the same two calibration areas; and (3) radiance data from ERTS-1 MSS imagery for the area(s) in which reflectivity is to be determined. The method takes into account sun angle effects and atmospheric effects on the radiance seen by the space sensor. If certain assumptions are made, the ground truth data collection need not be simultaneous with the ERTS-1 overflight. The method allows the calculation of a conversion factor for converting ERTS-1 MSS radiance measurements of a given overflight to reflectivity values. This conversion factor can be used to determine the reflectivity of any area in the general vicinity of the calibration areas which has a relatively similar overlying atmosphere. This method, or some modification of it, may be useful in ERTS investigations which require the determination of spectral signatures of areas from spacecraft data.

Mcginnies, W. G.↗
NASA NTRS1975

Single-class classification

Often, when classifying multispectral data, only one class or crop is of interest, such as wheat in the Large Area Crop Inventory Experiment (LACIE). Usual procedures for designing a Bayes classifier require that labeled training samples and therefore ground truth be available for the 'class of interest' plus all confusion classes defined by the multispectral data. This paper will consider the problem of designing a two-class Bayes classifier which will classify data into the 'class of interest' or the 'other' classes but will require only labeled training samples from the 'class of interest' to design the classifier. Thus, this classifier minimizes the need for ground truth. For these reasons, the classifier is referred to as a single-class classifier. A procedure for evaluating the overall performance of the single-class classifier in terms of the probability of error will be discussed.

Minter, T. C.↗
NASA NTRS1973

Geodetic analysis of Skylab altimetry preliminary data - SL/2 EREP pass 9

The author has identified the following significant results. The analysis was based on a time series intrinsic relationship between the satellite ephemeris, altimeter measured ranges, and the corresponding a priori values of subsatellite geoidal heights. Using sequential least squares processing with parameter weighting, the objective was to recover (1) the absolute geoidal heights of the subsatellite points, and (2) the associated altimeter calibration constant(s). Preliminary results from Skylab altimetry are given, using various combinations of orbit ephemeris and altimeter ranges as computed differently by NASA/JSC and NASA/Wallops. The influences of orbit accuracy, weighting functions, and a priori ground truth are described, based on the various combination solutions. It is shown that to deduce geoidal height by merely subtracting the height of the satellite from the altimeter range is inadmissible. The results of such direct subtraction can be very misleading if the orbit used is computed from data that included altimeter data used as height constraints. In view of the current state of knowledge, the use of geodetic ground truth samples as control benchmarks appears indispensable for the recovery of absolute geoidal heights with correct scale.

Mourad, A. G.↗
NASA NTRS2014

In-Situ and Remote-Sensing Data Fusion Using Machine Learning Techniques to Infer Urban and Fire Related Pollution Plumes

Airmass type characterization is key in understanding the relative contribution of various emission sources to atmospheric composition and air quality and can be useful in bottom-up model validation and emission inventories. However, classification of pollution plumes from space is often not trivial. Sub-orbital campaigns, such as SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) give us a unique opportunity to study atmospheric composition in detail, by using a vast suite of in-situ instruments for the detection of trace gases and aerosols. These measurements allow identification of spatial and temporal atmospheric composition changes due to various pollution plumes resulting from urban, biogenic and smoke emissions. Nevertheless, to transfer the knowledge gathered from such campaigns into a global spatial and temporal context, there is a need to develop workflow that can be applicable to measurements from space. In this work we rely on sub-orbital in-situ and total column remote sensing measurements of various pollution plumes taken aboard the NASA DC-8 during 2013 SEAC4RS campaign, linking them through a neural-network (NN) algorithm to allow inference of pollution plume types by input of columnar aerosol and trace-gas measurements. In particular, we use the 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) airborne measurements of wavelength dependent aerosol optical depth (AOD), particle size proxies, O3, NO2 and water vapor to classify different pollution plumes. Our method relies on assigning a-priori ground-truth labeling to the various plumes, which include urban pollution, different fire types (i.e. forest and agriculture) and fire stage (i.e. fresh and aged) using cluster analysis of aerosol and trace-gases in-situ and auxiliary (e.g. trajectory) data and the training of a NN scheme to fit the best prediction parameters using 4STAR measurements as input. We explore our misclassification rates as related to our ground-truth labels, and with multi-layered pollution plume cases. The next step in our analysis is to optimize parameter selection for a scheme that can be applied to space-borne aerosol and trace-gas observation platforms such as OMI, and future geostationary satellites such as TEMPO and GEO-CAPE.

Neural-network↗
NASA NTRS1985

Mobile intercept of storms

The primary goal was to acquire lightning data to serve as ground truth for U2 overflights. Researchers were successful in instrumenting the Univ. of Mississippi/National Severe Storms Lab. (UM/NSSL) mobile laboratory and in coordinating storm intercept through communication to the U2 provided by airplane guidance at NSSL and through direct communication with the U2 pilot from a portable transceiver in the mobile lab. A demonstration showed that a mobile laboratory can be directed within a large geographical area and used to collect ground truth data for comparison with airborne data on a routine basis with proper utilization of forecasts, nowcasts, and communication among all participants. After the U2 flights, researchers turned their attention solely to intercepting severe storms within the area of Oklahoma with good Doppler radar coverage. They incorporated a second vehicle, which followed the mobile lab and from which they released instrumented balloons. This project utilized a standard meteorological rawinsonde and a balloon-borne electric field meter. They were successful in flying, tracking, and receiving data from mobily launched balloons on several days. Researchers believe that they have demonstrated the ability to obtain meteorological and electrical data in severe storms using instrumented balloons. This also includes the capability to launch into the mesocyclone region and for multiple launches in the same storm.

Arnold, R. T.↗
NASA NTRS1973

Application of selected methods of remote sensing for detecting carbonaceous water pollution

A reach of the Houston Ship Channel was investigated during three separate overflights correlated with ground truth sampling on the Channel. Samples were analyzed for such conventional parameters as biochemical oxygen demand, chemical oxygen demand, total organic carbon, total inorganic carbon, turbidity, chlorophyll, pH, temperature, dissolved oxygen, and light penetration. Infrared analyses conducted on each sample included reflectance ATR analysis, carbon tetrachloride extraction of organics and subsequent scanning, and KBr evaporate analysis of CCl4 extract concentrate. Imagery which was correlated with field and laboratory data developed from ground truth sampling included that obtained from aerial KA62 hardware, RC-8 metric camera systems, and the RS-14 infrared scanner. The images were subjected to analysis by three film density gradient interpretation units. Data were then analyzed for correlations between imagery interpretation as derived from the three instruments and laboratory infrared signatures and other pertinent field and laboratory analyses.

Davis, E. M.↗
NASA NTRS1989

Radiometric calibration of Landsat Thematic Mapper Thermal Band

Radiometric calibration of satellite-acquired data is essential for quantitative scientific studies, as well as for a variety of image-processing applications. This paper describes a multiyear, on-orbit radiometric calibration of the Landsat Thematic Mapper (TM) Band 6 conducted at DOE's Pacific Northwest Laboratory. Numerous Landsat TM scenes acquired and analyzed included day and night coverages at several geographical locations over several seasons. Concurrent with Landsat overpasses, thermal field and local meteorological (surface and radiosonde) measurements were collected. At-satellite (uncorrected) radiances and temperatures for water and nonwater land cover were compared to ground truth (GT) measurements after making adjustments for atmospheric (using LOWTRAN), mixed-pixel, and emissivity effects. Results indicate that, for both water and nonwater features, TM Band 6 average corrected temperature determinations using local radiosonde data to adjust for atmospheric effects, and using appropriate emissivities, are within 1.0 C of GT temperature values. Temperatures of water pixels derived from uncorrected TM Band 6 data varied roughly between 1 and 3 C of ground truth values for water temperatures ranging between 4 and 24 C. Moreover, corrections using nonlocal and noncoincident radiosonde data resulted in errors as large as 12 C. Corrections using the U.S. Standard Atmosphere gave temperature values within 1 to 2 C of GT. The average uncertainty for field instruments was + or - 0.2 C; average uncertainty for Landsat TM corrected temperature determinations was + or - 0.4 C.

Wukelic, G. E.↗
NASA NTRS1992

Activities relating to understanding the initiation, organization and structure of moist convection in the Southeast environment

In the spring and summer of 1986, NASA/Marshall Space Flight Center (MSFC) will sponsor the Satellite Precipitation And Cloud Experiment (SPACE) to be conducted in the Central Tennessee, Northern Alabama, and Northeastern Mississippi area. The field program will incorporate high altitude flight experiments associated with meteorological remote sensor development for future space flight, and an investigation of precipitation processes associated with mesoscale and small convective systems. In addition to SPACE, the MIcroburst and Severe Thunderstorm (MIST) program, sponsored by the National Science Foundation (NSF), and the FAA-Lincoln Laboratory Operational Weather Study (FLOWS), sponsored by the Federal Aviation Administration (FAA), will take place concurrently within the SPACE experiment area. All three programs (under the joint acronym COHMEX (COoperative Huntsville Meteorological EXperiment)) will provide a data base for detailed analysis of mesoscale convective systems while providing ground truth comparisons for remote sensor evaluation. The purpose of this document is to outline the experiment design criteria for SPACE, and describe the special observing facilities and data sets that will be available under the COHMEX joint program. In addition to the planning of SPACE-COHMEX, this document covers three other parts of the program. The field program observations' main activity was the operation of an upper air rawinsonde network to provide ground truth for aircraft and spacecraft observations. Another part of the COHMEX program involved using boundary layer mesoscale models to study and simulate the initiation and organization of moist convection due to mesoscale thermal and mechanical circulations. The last part of the program was the collection, archival and distribution of the resulting COHMEX-SPACE data sets.

Mcnider, Richard T.↗
NASA NTRS1980

Remote sensing of particulate concentrations in water

Determination of residual radiance is essential in remote sensing measurements of suspended solids in the absence of real-time ground-truth data. Some typical background corrections are presented for Lake Superior and the spectral distribution of the residual radiance is determined from three major categories of turbidity in the lake. The results tested with Landsat 2 digital tape data indicate that for large bodies of water general information on atmospheric scattering, water clarity, and optical properties of suspended solids enables one to estimate the concentrations of particulates to within + or - 0.5 mg/liter in the absence of real-time ground-truth data.

Sydor, M.↗
NASA NTRS1990

Estimation of subpixel vegetation cover using red-infrared scattergrams

The bulk properties of discontinuous vegetation canopies are estimated at subpixel scales by applying the method of moments to a linear stochastic geometric model of canopy-soil reflectance and one set of multispectral observations without ground truth. The procedure involves the formulation of conditional moments for subsets of pixels that possess similar properties and can be identified through their common orientation in red-infrared scattergrams. The analysis is facilitated by assuming geometric similarity among the canopy elements and by formulating a sampling scale ratio in terms of the bulk geometric scales of the canopy and the pixel. Three versions of the method are demonstrated using two simulated scenes and an actual forested watershed for which aerial radiometric data and corresponding ground truth were obtained.

Jasinski, Michael F.↗
NASA NTRS1974

Coastal and estuarine studies with ERTS-1 and Skylab

Coastal vegetation, land use, current circulation, water turbidity, and ocean waste dispersion were studied by interpreting ERTS-1 and Skylab imagery with the help of ground truth collected during overpasses. Based on high-contrast targets such as piers and roads, the ERTS-1 multispectral scanner was found to have a resolution of 70-100 m, Skylab's S190A cameras about 20-40 m, and its S190B camera about 10-20 m. Important coastal land-use details can be more readily mapped using Skylab's imagery. On the other hand, the regular 18-day cycle of ERTS-1 allows observation of important man-made and natural changes, and facilitates collection of ground truth.

Klemas, V.↗
NASA NTRS2023

A Blind Convolutional Deep Autoencoder for Spectral Unmixing of Hyperspectral Images Over Waterbodies

Harmful algal blooms have dangerous repercussions for biodiversity, the ecosystem, and public health. Automatic identification based on remote sensing hyperspectral image analysis provides a valuable mechanism for extracting the spectral signatures of harmful algal blooms and their respective percentage in a region of interest. This paper proposes a new model called a non-symmetrical autoencoder for spectral unmixing to perform endmember extraction and fractional abundance estimation. The model is assessed in benchmark datasets, such as Jasper Ridge and Samson. Additionally, a case study of the HSI2 image acquired by NASA over Lake Erie in 2017 is conducted for extracting optical water types. The results using the proposed model for the benchmark datasets improve unmixing performance, as indicated by the spectral angle distance compared to five baseline algorithms. Improved results were obtained for various metrics. In the Samson dataset, the proposed model outperformed other methods for water (0.060) and soil (0.025) endmember extraction. Moreover, the proposed method exhibited superior performance in terms of mean spectral angle distance compared to the other five baseline algorithms. The non-symmetrical autoencoder for the spectral unmixing approach achieved better results for abundance map estimation, with a root mean square error of 0.091 for water and 0.187 for soil, compared to the ground truth. For the Jasper Ridge dataset, the non-symmetrical autoencoder for the spectral unmixing model excelled in the tree (0.039) and road (0.068) endmember extraction and also demonstrated improved results for water abundance maps (0.1121). The proposed model can identify the presence of chlorophyll-a in waterbodies. Chlorophyll-a is an essential indicator of the presence of the different concentrations of macrophytes and cyanobacteria. The non-symmetrical autoencoder for spectral unmixing achieves a value of 0.307 for the spectral angle distance metric compared to a reference ground truth spectral signature of chlorophyll-a. The source code for the proposed model, as implemented in this manuscript, can be found at https://github.com/EstefaniaAlfaro/autoencoder_owt_spectral.git.

hyperspectral imaging↗
NASA NTRS1992

A system for verifying models and classification maps by extraction of information from a variety of data sources

Recent updates to a geographical information system (GIS) called VICAR (Video Image Communication and Retrieval)/IBIS are described. The system is designed to handle data from many different formats (vector, raster, tabular) and many different sources (models, radar images, ground truth surveys, optical images). All the data are referenced to a single georeference plane, and average or typical values for parameters defined within a polygonal region are stored in a tabular file, called an info file. The info file format allows tracking of data in time, maintenance of links between component data sets and the georeference image, conversion of pixel values to `actual' values (e.g., radar cross-section, luminance, temperature), graph plotting, data manipulation, generation of training vectors for classification algorithms, and comparison between actual measurements and model predictions (with ground truth data as input).

Norikane, L.↗
NASA NTRS1997

JOVE Program

Coastal reef degradation and widespread bleaching of corals, i.e. loss of pigments and/or symbiotic zooxanthellae, is increasing globally. Remote sensing has great potential for assessing the extent of reef change. However, measuring reef change from remote platforms (boats, aircraft or satellites), requires ground-truth spectral algorithms characteristic of healthy and degraded reef populations. Our laboratory experiments demonstrated, for the first time, that healthy coral colonies emit characteristic fluorescence spectra in response to excitation with short wavelength (blue or ultraviolet) light. Furthermore, following stress, e.g. increased temperature, corals lose symbiotic algae and their health is compromised. We measured changes in coral fluorescence spectra along with pigment loss in response to temperature-induced stress. Following laboratory demonstration, we tested this approach in the field. The NASA P3 aircraft with the airborne oceanographic LIDAR system was used to map transects of coral reef in Hawaii. Ground truth samples of coral; were collected and analyzed for pigment density (pigments/surface area). Fluorescence spectra along transects showed consistent chlorophyll fluorescence peaks at 685 nm from the chlorophyll of the zooxanthellae and peaks between 400 and 570 nm believed to emanate from the coral tissue. Our results suggest that remote sensing of laser-induced fluorescence represents an efficient and effective approach to monitoring the health of coral reefs. Lists of papers, conferences, proposals awarded and a summary of student involvement is included in the appendices.

Hardy, John T.↗
NASA NTRS1975

ERTS-1 DCS technical support provided by Wallops Station

Wallops Station accepted the tasks of providing ground truth to several ERTS investigators, operating a DCP repair depot, designing and building an airborne DCP Data Acquisition System, and providing aircraft underflight support for several other investigators. Additionally, the data bank is generally available for use by ERTS and other investigators that have a scientific interest in data pertaining to the Chesapeake Bay area. Working with DCS has provided a means of evaluating the system as a data collection device possibly applicable to ongoing Earth Resources Program activities in the Chesapeake Bay area as well as providing useful data and services to other ERTS investigators. The two areas of technical support provided by Wallops, ground truth stations and repair for DCPs, are briefly discussed.

Smith, R.↗
NASA NTRS1976

Wind sets from SMS images - An assessment of quality for GATE

The paper analyzes the accuracy, representativeness, and reproducibility of tracer winds in the 1974 GARP Atlantic Tropical Experiment whose data are used as ground truth. The tracer winds were generated by tracking clouds in SMS (Synchronous Meteorological Satellite) images. Data availability limits comparisons to satellite winds with ship winds at the surface and at 250 mb. Attention is focused on how accurately the cloud displacements can be measured and on the extent to which the cloud displacements represent the wind field. Operator errors in obtaining the cloud displacements are examined in a series of reproducibility tests and wind sets. Differences between proximate satellite and ship winds were all under 3 m/sec. Representativeness of cloud tracers for cumulus and cirrus level flow is found to be good within the accuracy of currently available ground truth data.

Suchman, D.↗
NASA NTRS2016

SLAPex Freeze/Thaw 2015: The First Dedicated Soil Freeze/Thaw Airborne Campaign

Soil freezing and thawing is an important process in the terrestrial water, energy, and carbon cycles, marking the change between two very different hydraulic, thermal, and biological regimes. NASA's Soil Moisture Active/Passive (SMAP) mission includes a binary freeze/thaw data product. While there have been ground-based remote sensing field measurements observing soil freeze/thaw at the point scale, and airborne campaigns that observed some frozen soil areas (e.g., BOREAS), the recently-completed SLAPex Freeze/Thaw (F/T) campaign is the first airborne campaign dedicated solely to observing frozen/thawed soil with both passive and active microwave sensors and dedicated ground truth, in order to enable detailed process-level exploration of the remote sensing signatures and in situ soil conditions. SLAPex F/T utilized the Scanning L-band Active/Passive (SLAP) instrument, an airborne simulator of SMAP developed at NASA's Goddard Space Flight Center, and was conducted near Winnipeg, Manitoba, Canada, in October/November, 2015. Future soil moisture missions are also expected to include soil freeze/thaw products, and the loss of the radar on SMAP means that airborne radar-radiometer observations like those that SLAP provides are unique assets for freeze/thaw algorithm development. This paper will present an overview of SLAPex F/T, including descriptions of the site, airborne and ground-based remote sensing, ground truth, as well as preliminary results.

BOREAS↗