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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

System Characterization Results for the QuickBird Sensor

An overall system characterization was performed on several DigitalGlobe' QuickBird image products by the NASA Applied Research & Technology Project Office (formerly the Applied Sciences Directorate) at the John C. Stennis Space Center. This system characterization incorporated geopositional accuracy assessments, a spatial resolution assessment, and a radiometric calibration assessment. Geopositional assessments of standard georeferenced multispectral products were obtained using an array of accurately surveyed geodetic targets evenly spaced throughout a scene. Geopositional accuracy was calculated in terms of circular error. Spatial resolution of QuickBird panchromatic imagery was characterized based on edge response measurements using edge targets and the tilted-edge technique. Relative edge response was estimated as a geometric mean of normalized edge response differences measured in two directions of image pixels at points distanced from the edge by -0.5 and 0.5 of ground sample distance. A reflectance-based vicarious calibration approach, based on ground-based measurements and radiative transfer calculations, was used to estimate at-sensor radiance. These values were compared to those measured by the sensor to determine the sensor's radiometric accuracy. All imagery analyzed was acquired between fall 2005 and spring 2006. These characterization results were compared to previous years' results to identify any temporal drifts or trends.

Holekamp, Kara↗
NASA NTRS2002

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 km or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed-shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗
NASA NTRS2002

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 kin or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed- shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann↗
NASA NTRS1988

Portable high-speed photometry systems for observing occultations

Because of their high spatial resolution, stellar occultations have proven extremely effective for learning about planetary upper atmospheres, asteroids, and planetary rings. The ring orbit studies for Uranus have been particularly fruitful because researchers have been able, through occultations, to obtain data of high spatial resolution (approximately 2 km) at the rate of 1 to 2 times per year. THe occultation program at M.I.T. involves: (1) identifying the scientific questions that can be answered by occultation events, (2) predicting the zone of visibilty for the useful events, (3) maintaining and improving a set of portable high-speed photometric systems, (4) obtaining the observations, and (5) reducing the data and interpreting the results. Accomplishments during the past year include: (1) a comprehensive analysis of stellar occultation data to obtain an oblateness for Uranus at the 10 ubar level of 0.0193 plus or minus 0.0010, a value consistent with the planet being in hydrostatic equilibrium and undergoing rotation at the period found by Voyger; (2) establishing an upper limit of 0.004 km on the equivalent depth of 1986U1R from 2.2 micrometer occultation data; (3) the discovery of low-amplitude waves on the edges of the epsilon ring of Uranus; and (4) the acquisition of several hundred charge coupled device strip scans of 6 weeks at Mauna Kea for the purpose of generating a prediction for the stellar occultation of Pluto.

Elliot, James L.↗
NASA NTRS1998

Stellar Occultation Studies of the Solar System

Earth-based observations of stellar occultations provide extremely high spatial resolution for bodies in the outer solar system, about 10,000 times better than that of traditional imaging observations. Stellar occultation data can be used to establish the structure of atmospheres and rings of solar system bodies at high spatial resolution. Airborne occultation observations are particularly effective, since the controlled mobility of the observing platform allows the observer to fly within the optimum part of the occultation shadow for most events that are visible from Earth. Airborne observations are carried out above any clouds and are nearly free of scintillation noise from the Earth's atmosphere. KAO occultation observations resulted in the first detection of gravity waves in the Martian atmosphere, discovery of the Uranian rings, the first detection of Pluto's atmosphere, the first Earth-based investigations of Triton's atmosphere, and the discovery of narrow jets from Chiron's nucleus. The first SOFIA occultation opportunity will be an investigation of Pluto's atmospheric structure in November, 2002, and will resolve a problem that has lingered since the KAO discovery observation fourteen years earlier. We plan to continue our successful airborne occultation program with the greatly enhanced capability provided by SOFIA. We propose here to replace our KAO occultation photometer with one having twice the throughput, half the noise, a somewhat wider wavelength range, four times the field of view, and ten times the frame rate to optimize its performance and to capitalize on the larger collecting area offered by SOFIA. It will also allow for simultaneous visible and IR occultation observations, greatly enriching the results that we can obtain from occultations. We call this new imaging occultation photometer HOPI (High-speed Occultation Photometer and Imager). HOPI will provide a signal-to-noise ratio two to four times that of our present photometer for a given event, will permit useful observations of the more numerous events involving fainter stars, and will allow higher time resolution observations to be made. HOPI's characteristics also make it an ideal instrument for initial and ongoing evaluations of the SOFIA telescope's performance.

Elliot, James L.↗
NASA NTRS1998

Stellar Occultation Studies of the Solar System

Earth-based observations of stellar occultations provide extremely high spatial resolution for bodies in the outer solar system, about 10,000 times better than that of traditional imaging observations. Stellar occultation data can be used to establish the structure of atmospheres and rings of solar system bodies at high spatial resolution. Airborne occultation observations are particularly effective, since the controlled mobility of the observing platform allows the observer to fly within the optimum part of the occultation shadow for most events that are visible from Earth. Airborne observations are carried out above any clouds and are nearly free of scintillation noise from the Earth's atmosphere. KAO occultation observations resulted in the first detection of gravity waves in the Martian atmosphere, discovery of the Uranian rings, the first detection of Pluto's atmosphere, the first Earth-based investigations of Triton's atmosphere, and the discovery of narrow jets from Chiron's nucleus. The first SOFIA occultation opportunity will be an investigation of Pluto's atmospheric structure in November, 2002, and will resolve a problem that has lingered since the KAO discovery observation fourteen years earlier. We plan to continue our successful airborne occultation program with the greatly enhanced capability provided by SOFIA. We propose here to replace our KAO occultation photometer with one having twice the throughput, half the noise, a somewhat wider wavelength range, four times the field of view, and ten times the frame rate to optimize its performance and to capitalize on the larger collecting area offered by SOFIA. It will also allow for simultaneous visible and IR occultation observations, greatly enriching the results that we can obtain from occultations. We call this new imaging occultation photometer HOPI (High-speed Occultation Photometer and Imager). HOPI will provide a signal-to-noise ratio two to four times that of our present photometer for a given event, will permit useful observations of the more numerous events involving fainter stars, and will allow higher time resolution observations to be made. HOPI's characteristics also make it an ideal instrument for initial and ongoing evaluations of the SOFIA telescope's performance.

Elliot, James L.↗
NASA NTRS2023

A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR

The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R 2 ) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value −235 mm w.e. yr -1 (original) to −57 mm w.e. yr -1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature.

Greenland Ice Sheet↗
DOE OSTI2020

A High-resolution Regional Wave Resource Characterization For The U.S. West Coast

Objectives/Scope: Wave resource characterization is a critical step for wave energy converter deployment in the coastal ocean and relies on long-term, high-resolution wave datasets. This study presents a detailed modeling study of the wave resource along the U.S. West Coast (Washington, Oregon, and California), a coastal region that was identified with high wave energy potential in earlier studies. Methods, Procedures, Process: The wave hindcast covers a 32-year period from 1979 to 2010 and is based on a multi-resolution, unstructured-grid SWAN model framework. Model configuration closely follows and meets the requirements recommended by the International Electrotechnical Commission Technical Specification (IEC TS) for wave energy resource assessment and characterization (Class 2 - feasibility study). The model domain covers the entire U.S. Exclusive Economic Zone (EEZ) in the West Coast and has a spatial resolution varying from ~300 m in the nearshore region (20 km from the shoreline) to ~2500 m within the EEZ and ~5000 m at the open boundary, which extends beyond the EEZ. The model was forced by hourly 2-D wave spectra produced by a two-way nested WaveWatch III model, which covers the global ocean domain and the broader U.S. West Coast region domain with spatial resolutions of 0.5 degree and 10 arc-minutes, respectively. Both wave models are forced by hourly, 0.5-degree wind forcing obtained from NCEP’s Climate Forecast System Reanalysis (CFSR) product. Results, Observations, Conclusions: The standard model output for the SWAN model includes 3-hourly output for the six IEC wave resource parameters (e.g., omnidirectional wave power) at each grid point and hourly 2-D spectra at more than 50 NDBC buoys. Extensive model validation was achieved by comparing the six model-predicted IEC parameters with those derived from field observations at representative NDBC buoys. The error statistics indicated the model’s satisfactory performance. Further analyses were conducted to systematically evaluate the temporal and spatial distributions of wave energy potential and wave climate along the U.S. West Coast. Results suggest that Washington and Oregon coasts have similar nearshore wave resource, which is significantly higher than resources in Southern California. Strong seasonal variations are also observed, e.g., high wave energy tends to occur in the winter months. In summary, this study produced the first high-resolution, comprehensive dataset on wave energy distribution along the U.S. West Coast. Novel/Additive Information: The results are being used by the National Renewable Energy Laboratory to update the MHK Atlas, which was originally derived from NOAA’s 4-arc-minute WaveWatch III model output. In addition, the monthly averaged wave energy climatology dataset can be readily shared to support a variety of research and application efforts within the EEZ of the U.S. West Coast.

Wang, Taiping↗
NASA NTRS2019

Evaluation of MODIS and VIIRS Cloud-Gap-Filled Snow-Cover Products for Production of an Earth Science Data Record

MODerate resolution Imaging Spectroradiometer (MODIS) cryosphere products have been available since 2000 – following the 1999 launch of the Terra MODIS and the 2002 launch of the Aqua MODIS – and include global snow-cover extent (SCE) (swath, daily, and 8 d composites) at 500 m and ∼5 km spatial resolutions. These products are used extensively in hydrological modeling and climate studies. Reprocessing of the complete snow-cover data record, from Collection 5 (C5) to Collection 6 (C6) and Collection 6.1 (C6.1), has provided improvements in the MODIS product suite. Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Collection 1 (C1) snow-cover products at a 375 m spatial resolution have been available since 2011 and are currently being reprocessed for Collection 2 (C2). Both the MODIS C6.1 and the VIIRS C2 products will be available for download from the National Snow and Ice Data Center beginning in early 2020 with the complete time series available in 2020. To address the need for a cloud-reduced or cloud-free daily SCE product for both MODIS and VIIRS, a daily cloud-gap-filled (CGF) snow-cover algorithm was developed for MODIS C6.1 and VIIRS C2 processing. MOD10A1F (Terra) and MYD10A1F (Aqua) are daily, 500 m resolution CGF SCE map products from MODIS. VNP10A1F is the daily, 375 m resolution CGF SCE map product from VIIRS. These CGF products include quality-assurance data such as cloud-persistence statistics showing the age of the observation in each pixel. The objective of this paper is to introduce the new MODIS and VIIRS standard CGF daily SCE products and to provide a preliminary evaluation of uncertainties in the gap-filling methodology so that the products can be used as the basis for a moderate-resolution Earth science data record (ESDR) of SCE. Time series of the MODIS and VIIRS CGF products have been developed and evaluated at selected study sites in the US and southern Canada. Observed differences, although small, are largely attributed to cloud masking and differences in the time of day of image acquisition. A nearly 3-month time-series comparison of Terra MODIS and S-NPP VIIRS CGF snow-cover maps for a large study area covering all or parts of 11 states in the western US and part of southwestern Canada reveals excellent correspondence between the Terra MODIS and S-NPP VIIRS products, with a mean difference of 11 070 sqkm, which is ∼0.45 % of the study area. According to our preliminary validation of the Terra and Aqua MODIS CGF SCE products in the western US study area, we found higher accuracy of the Terra product compared with the Aqua product. The MODIS CGF SCE data record beginning in 2000 has been extended into the VIIRS era, which should last at least through the early 2030s.

Hall, Dorothy K.↗
DOE OSTI2022

Revealing local order via high energy EELS

Short range order (SRO) is critical in determining the performance of many important engineering materials. However, accurate characterization of SRO with high spatial resolution – which is needed for the study of individual nanoparticles and at material defects and interfaces – is often experimentally inaccessible. Here, we locally quantify SRO via scanning transmission electron microscopy with extended energy loss fine structure analysis. Specifically, we use novel instrumentation to perform electron energy loss spectroscopy out to 12 keV, accessing energies which are conventionally only possible using a synchrotron. Our data is of sufficient energy resolution and signal-to-noise ratio to perform quantitative extended fine structure analysis, which allows determination of local coordination environments. To showcase this technique, we investigate a multicomponent metallic glass nanolaminate and locally quantify the SRO with <10 nm spatial resolution; this measurement would have been impossible with conventional synchrotron or electron microscopy methods. Finally, we discuss the nature of SRO within the metallic glass phase, as well as the wider applicability of our approach for determining processing–SRO–property relationships in complex materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Near, far, wherever you are: simulations on the dose efficiency of holographic and ptychographic coherent imaging

Different studies in X-ray microscopy have arrived at conflicting conclusions about the dose efficiency of imaging modes involving the recording of intensity distributions in the near (Fresnel regime) or far (Fraunhofer regime) field downstream of a specimen. A numerical study is presented on the dose efficiency of near-field holography, near-field ptychography and far-field ptychography, where ptychography involves multiple overlapping finite-sized illumination positions. Unlike what has been reported for coherent diffraction imaging, which involves recording a single far-field diffraction pattern, it is found that all three methods offer similar image quality when using the same fluence on the specimen, with far-field ptychography offering slightly better spatial resolution and a lower mean error. These results support the concept that (if the experiment and image reconstruction are done properly) the sample can be near or far; wherever you are, photon fluence on the specimen sets one limit to spatial resolution.

42 ENGINEERING↗
NASA NTRS1990

Image construction from the IRAS survey and data fusion

The IRAS survey data can be used successfully to produce images of extended objects. The major difficulty, viz. non-uniform sampling, different response functions for each detector, and varying signal-to-noise levels for each detector for each scan, were resolved. The results of three different image construction techniques are compared: co-addition, constrained least squares, and maximum entropy. The maximum entropy result is superior. An image of the galaxy M51 with an average spatial resolution of 45 arc seconds, is presented using 60 micron survey data. This exceeds the telescope diffraction limit of 1 minute of arc, at this wavelength. Data fusion is a proposed method for combining data from different instruments, with different spatial resolutions, at different wavelengths. Direct estimates of the physical parameters, temperature, density and composition, can be made from the data without prior images (re-)construction. An increase in the accuracy of these parameters is expected as the result of this more systematic approach.

Bontekoe, Tj. R.↗
NASA NTRS1993

Spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall-measurement systems

Three-dimensional radar data for three summer Florida storms are used as input to a microwave radiative transfer model. The model simulates microwave brightness observations by a 19-GHz, nadir-pointing, satellite-borne microwave radiometer. The statistical distribution of rainfall rates for the storms studied, and therefore the optimal conversion between microwave brightness temperatures and rainfall rates, was found to be highly sensitive to the spatial resolution at which observations were made. The optimum relation between the two quantities was less sensitive to the details of the vertical profile of precipitation. Rainfall retrievals were made for a range of microwave sensor footprint sizes. From these simulations, spatial sampling-error estimates were made for microwave radiometers over a range of field-of-view sizes. The necessity of matching the spatial resolution of ground truth to radiometer footprint size is emphasized. A strategy for the combined use of raingages, ground-based radar, microwave, and visible-infrared (VIS-IR) satellite sensors is discussed.

Turner, B. J.↗
NASA NTRS2015

Tropospheric Emissions: Monitoring of Pollution Overview

TEMPO is now well into its implementation phase, having passed both its Key Decision Point C and the Critical Design Review (CDR) for the instrument. The CDR for the ground systems will occur in March 2016 and the CDR for the Mission component at a later date, after the host spacecraft has been selected. TEMPO is on schedule to measure atmospheric pollution for greater North America from space using ultraviolet and visible spectroscopy. TEMPO measures from Mexico City to the Canadian oil sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution. TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry. Measurements are from geostationary (GEO) orbit, to capture the inherent high variability in the diurnal cycle of emissions and chemistry. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies. TEMPO takes advantage of a GEO host spacecraft to provide a modest cost mission that measures the spectra required to retrieve O3, NO2, SO2, H2CO, C2H2O2, H2O, aerosols, cloud parameters, and UVB radiation. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric O3 chemistry cycle. Multi-spectral observations provide sensitivity to O3 in the lowermost troposphere, substantially reducing uncertainty in air quality predictions by 50 percent. TEMPO quantifies and tracks the evolution of aerosol loading. It provides near-real-time air quality products that will be made widely, publicly available. TEMPO provides much of the atmospheric measurement capability recommended for GEO-CAPE in the 2007 National Research Council Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond. Instruments from Europe (Sentinel 4) and Asia (GEMS) will form parts of a global GEO constellation for pollution monitoring later this decade, with a major focus on intercontinental pollution transport. TEMPO will launch at a prime time to be a component of this constellation.

Chance, Kelly↗
NASA NTRSDate not supplied

Spectrally Dependent Radiometric Measurement Errors Due to Ccd Serial Pixel-to-Pixel Readout Interference in the Ocean Color Instrument of the NASA PACE Mission

The Ocean Color Instrument on NASA’s PACE mission is a 322 887 nm hyperspectral imager with 1 km x 1 km nadir spatial resolution and 5 nm spectral resolution utilizing charge-coupled devices (CCDs) operating in Time Delay Integration (TDI) mode where each TDI column represents a different wavelength in 0.625 nm increments. After TDI, the charge is moved into serial output pixels and read out. The spatial resolution requires an 8.5 MHz readout rate. This only allows 59 ns for the CCD reset and video to be asserted and settled before sampling. The response exhibits serial pixel-to-pixel readout interference due to the lack of full settling. Each serial pixel value has a dependence on the value of the preceding pixel value. This leads to a spectrally dependent radiometric measurement error of up to 0.3 %. We explain the operation of the detection system, the behavior of the interference, and show the resulting measurement error based on data from both ground testing and on-orbit characterization.

Remote Sensing↗
NASA NTRS2024

Spectrally Dependent Radiometric Measurement Errors Due to CCD Serial Pixel-to-Pixel Readout Interference in the Ocean Color Instrument of the NASA PACE Mission

The Ocean Color Instrument on NASA’s PACE mission is a 322 887 nm hyperspectral imager with 1 km x 1 km nadir spatial resolution and 5 nm spectral resolution utilizing charge-coupled devices (CCDs) operating in Time Delay Integration (TDI) mode where each TDI column represents a different wavelength in 0.625 nm increments. After TDI, the charge is moved into serial output pixels and read out. The spatial resolution requires an 8.5 MHz readout rate. This only allows 59 ns for the CCD reset and video to be asserted and settled before sampling. The response exhibits serial pixel-to-pixel readout interference due to the lack of full settling. Each serial pixel value has a dependence on the value of the preceding pixel value. This leads to a spectrally dependent radiometric measurement error of up to 0.3 %. We explain the operation of the detection system, the behavior of the interference, and show the resulting measurement error based on data from both ground testing and on-orbit characterization.

Remote Sensing↗
NASA NTRS1984

Characterization of Landsat-4 MSS and TM digital image data

The launch of Landsat-4 in July 1982 represents a continuation in the remote sensing of earth resources. The 80-m spatial resolution provided by the Multispectral Scanner (MSS) on board the satellite is fine enough to resolve many natural features and land-use details in both rural and urban settings. The second sensor of the spacecraft, the Thematic Mapper (TM), introduces a new era of sensing with refined spatial resolution (30 m) and expanded spectral coverage (7 bands). This paper describes results from engineering studies of the characteristics of digital image data from the two Landsat-4 sensors. These studies form a part of the Landsat-4 Image Data Quality Analysis program (LIDQA). The image data were generally found to be of high quality and the TM provided several improvements over the MSS, in its spatial and spectral characteristics.

Malila, W. A.↗
NASA NTRS1992

Multi-resolution processing for fractal analysis of airborne remotely sensed data

Fractal geometry is increasingly becoming a useful tool for modeling natural phenomenon. As an alternative to Euclidean concepts, fractals allow for a more accurate representation of the nature of complexity in natural boundaries and surfaces. Since they are characterized by self-similarity, an ideal fractal surface is scale-independent; i.e. at different scales a fractal surface looks the same. This is not exactly true for natural surfaces. When viewed at different spatial resolutions parts of natural surfaces look alike in a statistical manner and only for a limited range of scales. Images acquired by NASA's Thermal Infrared Multispectral Scanner are used to compute the fractal dimension as a function of spatial resolution. Three methods are used to determine the fractal dimension - Schelberg's line-divider method, the variogram method, and the triangular prism method. A description of these methods and the results of applying these methods to a remotely-sensed image is also presented. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected was the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. This corresponds to 3 different pixel sizes - 5m, 15m, and 30m. After, simulating different spatial sampling intervals within the same image for each of the 3 image sets, the results are cross-correlated to compare the extent of detail and complexity that is obtained when data is taken at lower spatial intervals.

Jaggi, S.↗