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Spatial Resolution Characterization for Aerial Digital Imagery

The U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration have jointly conducted characterizations of aerial digital imagery from commercial data providers. In a typical scenario, a vendor acquired imagery over the Stennis Space Center test range and provided a common data package to SSC. SSC personnel analyzed the geopositional accuracy and spatial resolution of the images, then documented the characterization results in a report and delivered the report to the USGS. Spatial resolution characterization was based on edge response measurements using one of the SSC edge targets and the tilted-edge technique. Relative Edge Response (RER) has been estimated for aerial digital imagery from several commercial data providers. RER is one of the engineering parameters used in the General Image Quality Equation to provide predictions of imaging system performance expressed in terms of the National Imagery Interpretability Rating Scale.

Blonski, Slawomir↗

Characterizing the Spatial and Temporal Distribution of Aerosol Optical Thickness Over the Atlantic Basin Utilizing GOES-8 Multispectral Data

In recent years, modeling and analysis efforts have suggested that the direct and indirect radiative effects of both anthropogenic and natural aerosols play a major role in the radiative balance of the earth and are an important factor in climate change calculations. The direct effects of aerosols on radiation and indirect effects on cloud properties are not well understood at this time. In order to improve the characterization of aerosols within climate models it is important to accurately parameterize aerosol forcing mechanisms at the local, regional, and global scales. This includes gaining information on the spatial and temporal distribution of aerosols, transport regimes and mechanisms, aerosol optical thickness, and size distributions. Although there is an expanding global network of ground measurements of aerosol optical thickness and size distribution at specific locations, satellite data must be utilized to characterize the spatial and temporal extent of aerosols and transport regimes on regional and global scales. This study was part of a collaborative effort to characterize aerosol radiative forcing over the Atlantic basin associated with the following three major aerosol components in this region: urban/sulfate, Saharan dust, and biomass burning. In-situ ground measurements obtained by a network of sun photometers during the Smoke Clouds and Radiation Experiment in Brazil (SCAR-B) and the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX) were utilized to develop, calibrate, and validate a Geostationary Operational Environmental Satellite (GOES)-8 aerosol optical thickness (AOT) product. Regional implementation of the GOES-8 AOT product was used to augment point source measurements to gain a better understanding of the spatial and temporal distributions of Atlantic basin aerosols during SCAR-B and TARFOX.

Fox, Robert↗

Spatial and Temporal Characterization of Cyanobacteria Blooms in the Mississippi Sound and Their Relationship to the Bonnet Carré Spillway Openings

During the spring and summer of 2019, an unprecedented cyanobacterial harmful algal bloom (cyanoHAB) was responsible for beach advisories on 25 beaches along the Mississippi Sound for over 3 months. Due to the preceding heavy rainfall and flooding within the Mississippi River watershed, for the first time in history, the Bonnet Carré Spillway (BCS) opened twice in one year during 2019. The coastal cyanoHAB coincided with the second BCS opening. The main objectives of this study were: (1) to investigate the potential for using the National Aeronautics and Space Administration (NASA) ocean color standard Cyanobacteria Index (CIcyano) algorithm to characterize the spatial and temporal extent of the 2019 cyanoHAB; (2) to couple the CIcyano data with river discharge, salinity, and modeled-wind data to study the conditions leading to the cyanoHAB and factors aiding the advection and persistence of the bloom within the Mississippi Sound, including a possible relationship to the BCS; (3) to further investigate the relationship with the BCS by repeating the methods using data from 2018, which was a year when the BCS was opened but no evidence of cyanoHABs was reported along the Mississippi coast. Weekly means and monthly frequency CIcyano images, river discharge, salinity, and modeled-wind data from February to September of 2018 and 2019 were analyzed, which coincide with three BCS openings. In March 2018, a cyanobacteria bloom was observed within Lake Pontchartrain coinciding with the BCS opening; however, the month-long bloom was contained to the lake. Two distinct cyanoHABs were observed in 2019 and both blooms were advected into the Mississippi Sound, and likely contributed to the 3-month-long beach water advisories of 2019 along the Mississippi coastline. From March to mid-July 2019, salinity at stations within the Mississippi Sound was consistently near zero indicating high levels of freshwater. During that time, winds were predominantly northwestward, preventing the BCS waters from flushing into the Mississippi Shelf and resulting in BCS waters remaining longer within the estuarine lakes and Mississippi Sound. Although the BCS had an undeniable impact on the presence of the coastal cyanoHAB of 2019, other variables including wind direction, water flow, mixing, and persistence of freshwater within the Sound can determine the intensity and extent of the cyanoHABs. Coupling in situ phytoplankton information from freshwater water bodies to the marine continuum along with water flow, wind data, and satellite imagery could help identify cyanoHABs at early stages and forecast their trajectory and potential impacts on coastal areas.

Bonnet Carré Spillway↗

Spatial Resolution Characterization for AWiFS Multispectral Images

Within the framework of the Joint Agency Commercial Imagery Evaluation program, the National Aeronautics and Space Administration, the National Geospatial-Intelligence Agency, and the U.S. Geological Survey cooperate in the characterization of high-to-moderate-resolution commercial imagery of mutual interest. One of the systems involved in this effort is the Advanced Wide Field Sensor (AWiFS) onboard the Indian Remote Sensing (IRS) Reourcesat-1 satellite, IRS-P6. Spatial resolution of the AWiFS multispectral images was characterized by estimating the value of the system Modulation Transfer Function (MTF) at the Nyquist spatial frequency. The Nyquist frequency is defined as half the sampling frequency, and the sampling frequency is equal to the inverse of the ground sample distance. The MTF was calculated as a ratio of the Fourier transform of a profile across an AWiFS image of the Lake Pontchartrain Causeway Bridge and the Fourier transform of a profile across an idealized model of the bridge for each spectral band evaluated. The mean MTF value for the AWiFS imagery evaluated was estimated to be 0.1.

Blonski, Slawomir↗

Proceedings of the 2004 High Spatial Resolution Commercial Imagery Workshop

Topics covered include: NASA Applied Sciences Program; USGS Land Remote Sensing: Overview; QuickBird System Status and Product Overview; ORBIMAGE Overview; IKONOS 2004 Calibration and Validation Status; OrbView-3 Spatial Characterization; On-Orbit Modulation Transfer Function (MTF) Measurement of QuickBird; Spatial Resolution Characterization for QuickBird Image Products 2003-2004 Season; Image Quality Evaluation of QuickBird Super Resolution and Revisit of IKONOS: Civil and Commercial Application Project (CCAP); On-Orbit System MTF Measurement; QuickBird Post Launch Geopositional Characterization Update; OrbView-3 Geometric Calibration and Geopositional Accuracy; Geopositional Statistical Methods; QuickBird and OrbView-3 Geopositional Accuracy Assessment; Initial On-Orbit Spatial Resolution Characterization of OrbView-3 Panchromatic Images; Laboratory Measurement of Bidirectional Reflectance of Radiometric Tarps; Stennis Space Center Verification and Validation Capabilities; Joint Agency Commercial Imagery Evaluation (JACIE) Team; Adjacency Effects in High Resolution Imagery; Effect of Pulse Width vs. GSD on MTF Estimation; Camera and Sensor Calibration at the USGS; QuickBird Geometric Verification; Comparison of MODTRAN to Heritage-based Results in Vicarious Calibration at University of Arizona; Using Remotely Sensed Imagery to Determine Impervious Surface in Sioux Falls, South Dakota; Estimating Sub-Pixel Proportions of Sagebrush with a Regression Tree; How Do YOU Use the National Land Cover Dataset?; The National Map Hazards Data Distribution System; Recording a Troubled World; What Does This-Have to Do with This?; When Can a Picture Save a Thousand Homes?; InSAR Studies of Alaska Volcanoes; Earth Observing-1 (EO-1) Data Products; Improving Access to the USGS Aerial Film Collections: High Resolution Scanners; Improving Access to the USGS Aerial Film Collections: Phoenix Digitizing System Product Distribution; System and Product Characterization: Issues Approach; Innovative Approaches to Analysis of Lidar Data for the National Map; Changes in Imperviousness near Military Installations; Geopositional Accuracy Evaluations of QuickBird and OrbView-3: Civil and Commercial Applications Project (CCAP); Geometric Accuracy Assessment: OrbView ORTHO Products; QuickBird Radiometric Calibration Update; OrbView-3 Radiometric Calibration; QuickBird Radiometric Characterization; NASA Radiometric Characterization; Establishing and Verifying the Traceability of Remote-Sensing Measurements to International Standards; QuickBird Applications; Airport Mapping and Perpetual Monitoring Using IKONOS; OrbView-3 Relative Accuracy Results and Impacts on Exploitation and Accuracy Improvement; Using Remotely Sensed Imagery to Determine Impervious Surface in Sioux Falls, South Dakota; Applying High-Resolution Satellite Imagery and Remotely Sensed Data to Local Government Applications: Sioux Falls, South Dakota; Automatic Co-Registration of QuickBird Data for Change Detection Applications; Developing Coastal Surface Roughness Maps Using ASTER and QuickBird Data Sources; Automated, Near-Real Time Cloud and Cloud Shadow Detection in High Resolution VNIR Imagery; Science Applications of High Resolution Imagery at the USGS EROS Data Center; Draft Plan for Characterizing Commercial Data Products in Support of Earth Science Research; Atmospheric Correction Prototype Algorithm for High Spatial Resolution Multispectral Earth Observing Imaging Systems; Determining Regional Arctic Tundra Carbon Exchange: A Bottom-Up Approach; Using IKONOS Imagery to Assess Impervious Surface Area, Riparian Buffers and Stream Health in the Mid-Atlantic Region; Commercial Remote Sensing Space Policy Civil Implementation Update; USGS Commercial Remote Sensing Data Contracts (CRSDC); and Commercial Remote Sensing Space Policy (CRSSP): Civil Near-Term Requirements Collection Update.

Source record↗

SNPP VIIRS Spectral Bands Co-Registration and Spatial Response Characterization

The Visible Infrared Imager Radiometer Suite (VIIRS) instrument onboard the Suomi National Polar‐orbiting Partnership (SNPP) satellite was launched on 28 October 2011. The VIIRS has 5 imagery spectral bands (I-bands), 16 moderate resolution spectral bands (M-bands) and a panchromatic day/night band (DNB). Performance of the VIIRS spatial response and band-to-band co-registration (BBR) was measured through intensive pre-launch tests. These measurements were made in the non-aggregated zones near the start (or end) of scan for the I-bands and M-bands and for a limited number of aggregation modes for the DNB in order to test requirement compliance. This paper presents results based on a recently re-processed pre-launch test data. Sensor (detector) spatial impulse responses in the scan direction are parameterized in terms of ground dynamic field of view (GDFOV), horizontal spatial resolution (HSR), modulation transfer function (MTF), ensquared energy (EE) and integrated out-of-pixel (IOOP) spatial response. Results are presented for the non-aggregation, 2-sample and 3-sample aggregation zones for the I-bands and M-bands, and for a limited number of aggregation modes for the DNB. On-orbit GDFOVs measured for the 5 I-bands in the scan direction using a straight bridge are also presented. Band-to-band co-registration (BBR) is quantified using the prelaunch measured band-to-band offsets. These offsets may be expressed as fractions of horizontal sampling intervals (HSIs), detector spatial response parameters GDFOV or HSR. BBR bases on HSIs in the non-aggregation, 2-sample and 3-sample aggregation zones are presented. BBR matrices based on scan direction GDFOV and HSR are compared to the BBR matrix based on HSI in the non-aggregation zone. We demonstrate that BBR based on GDFOV is a better representation of footprint overlap and so this definition should be used in BBR requirement specifications. We propose that HSR not be used as the primary image quality indicator, since we show that it is neither an adequate representation of the size of sensor spatial response nor an adequate measure of imaging quality.

Suomi NPP VIIRS↗

Quantitative characterization of spatial distribution of particles in materials: Application to materials processing

Most engineering materials contain second phase particles or fibers which serve to reinforce the matrix phase. The effect of reinforcements on material properties is usually analyzed in terms of the average volume fraction and spacing of reinforcements, quantities which are global microstructural characteristics. However, material properties can also depend on local microstructural characteristics; for example, on how uniformly the reinforcing phase is distributed in the material. The analysis method will then be applied to a materials processing problem to discover how processing parameters can be selected to maximize redistribution of the reinforcing phase during processing. Several mathematical analysis methods could be adapted to the problem of characterizing the distribution of particles in materials. A tessellation-based method was selected. In the first phase of the investigation, a software package was written to automate the analysis. Typical results are shown. The analysis technique allows the degree to which particles are clustered together, the size and spacing of particle clusters, and the particle density in clusters to be found. The analysis methods were applied to computer-generated distributions and to a few real particle-containing materials. Methods for analyzing a nonuniform particle distribution in a material can be applied to two broad classes of materials science problems: understanding how the resulting particle distribution affects properties. The analysis method described is applied to a materials processing problem: how to select extrusion conditions to maximize the redistribution of reinforcing particles that are initially nonuniformly distributed. In addition, the tessellation-based method to analyze star distributions in spiral galaxies was adapted, illustrating the diverse types of problems to which the analysis method can be applied.

Parse, J. B.↗

Characterization of spatial statistics of distributed targets in SAR data

A statistical approach to the analysis of spatial statistics in polarimetric multifrequency SAR data, which is aimed at extracting the intrinsic variability of the target by removing variability from other sources, is presented. An image model, which takes into account three sources of spatial variability, namely, image speckle, system noise, and the intrinsic spatial variability of the target or texture, is described. It is shown that the presence of texture increases the image variance-to-mean square ratio and introduces deviations of the image autocovariance function from the expected SAR system response. The approach is exemplified by sea-ice SAR imagery acquired by the Jet Propulsion Laboratory three-frequency polarimetric airborne SAR. Data obtained indicate that, for different sea-ice types, the spatial statistics seem to vary more across frequency than across polarization and the observed differences increase in magnitude with decreasing frequency.

Rignot, E.↗

Application of Image Analysis for Characterization of Spatial Arrangements of Features in Microstructure

A number of microstructural processes are sensitive to the spatial arrangements of features in microstructure. However, very little attention has been given in the past to the experimental measurements of the descriptors of microstructural distance distributions due to the lack of practically feasible methods. We present a digital image analysis procedure to estimate the micro-structural distance distributions. The application of the technique is demonstrated via estimation of K function, radial distribution function, and nearest-neighbor distribution function of hollow spherical carbon particulates in a polymer matrix composite, observed in a metallographic section.

Louis, Pascal↗

Real-time three-dimensional color Doppler echocardiography for characterizing the spatial velocity distribution and quantifying the peak flow rate in the left ventricular outflow tract

Quantification of flow with pulsed-wave Doppler assumes a "flat" velocity profile in the left ventricular outflow tract (LVOT), which observation refutes. Recent development of real-time, three-dimensional (3-D) color Doppler allows one to obtain an entire cross-sectional velocity distribution of the LVOT, which is not possible using conventional 2-D echo. In an animal experiment, the cross-sectional color Doppler images of the LVOT at peak systole were derived and digitally transferred to a computer to visualize and quantify spatial velocity distributions and peak flow rates. Markedly skewed profiles, with higher velocities toward the septum, were consistently observed. Reference peak flow rates by electromagnetic flow meter correlated well with 3-D peak flow rates (r = 0.94), but with an anticipated underestimation. Real-time 3-D color Doppler echocardiography was capable of determining cross-sectional velocity distributions and peak flow rates, demonstrating the utility of this new method for better understanding and quantifying blood flow phenomena.

NASA Discipline Cardiopulmonary↗

Initial On-Orbit Spatial Resolution Characterization of OrbView-3 Panchromatic Images

Characterization was conducted under the Memorandum of Understanding among Orbital Sciences Corp., ORBIMAGE, Inc., and NASA Applied Sciences Directorate. Acquired five OrbView-3 panchromatic images of the permanent Stennis Space Center edge targets painted on a concrete surface. Each image is available at two processing levels: Georaw and Basic. Georaw is an intermediate image in which individual pixels are aligned by a nominal shift in the along-scan direction to adjust for the staggered layout of the panchromatic detectors along the focal plane array. Georaw images are engineering data and are not delivered to customers. The Basic product includes a cubic interpolation to align the pixels better along the focal plane and to correct for sensor artifacts, such as smile and attitude smoothing. This product retains satellite geometry - no rectification is performed. Processing of the characterized images did not include image sharpening, which is applied by default to OrbView-3 image products delivered by ORBIMAGE to customers. Edge responses were extracted from images of tilted edges in two directions: along-scan and cross-scan. Each edge response was approximated with a superposition of three sigmoidal functions through a nonlinear least-squares curve-fitting. Line Spread Functions (LSF) were derived by differentiation of the analytical approximation. Modulation Transfer Functions (MTF) were obtained after applying the discrete Fourier transform to the LSF.

Blonski, Slawomir↗

NASA IKONOS Characterization Methodologies

The objectives of IKONOS characterization are to: 1) Perform spatial characterization by measuring edge response of IKONOS images to evaluate Modulation Transfer Function (MTF); 2) Perform geolocational accuracy assessment of IKONOS imagery using surveyed geodetic targets; 3) Perform radiometric vicarious calibrations of IKONOS imagery and compare with Space Imaging calibration coefficients. Calibration activities conducted in West Texas, and at Stennis Space Center, Mississippi and Lunar Lake, Nevada are profiled in this viewgraph presentation.

Pagnutti, Mary↗

Development of Multi-Edge Slant Target for Unlocalized MTF Measurement of Airborne Imaging System Payloads

Calibration of imaging instruments is a critical step in effectively characterizing imaging data. A comprehensive characterization of an imaging system provides valuable insight into the overall uncertainties in the results derived from the raw data collected. The Scientifically Calibrated In-Flight Imagery (SCIFLI) team (based at NASA Langley Research Center) has designed, built, tested, and successfully flown the optical payload known as the SCIFLI Airborne Multispectral Imager (SAMI). SAMI is a multispectral imaging payload, complete with sensor configurations for the Ultraviolet-Visible spectrum as well as Near- Infrared, Shortwave Infrared, and Midwave Infrared bands and is fitted with various optical hardware designed to turn, split, and focus light beams to the respective in-band sensors. Radiometric calibrations are performed for SAMI such that the accuracy and uncertainty of thermal and spectral measurements are effectively characterized. However, SAMI does not regularly undergo spatial characterizations to evaluate the performance of the imager at high spatial frequencies. This is essential, as understanding the spatial sensor response of discrete sensors is just as important as the spectral sensor response. The payload currently utilizes a calibration cart for lab testing. Equipped with a modular setup and several radiation sources, it is perfect for performing high-quality radiometric calibrations. This work focuses on using the calibration cart to perform spatial calibrations. A custom designed calibration target is being used to evaluate the optical performance of SAMI. Specifically, the target is designed to measure the Modulation Transfer Function (MTF) of the imager in discrete locations around the focal plane. The results of this characterization will provide insight into the spatial resolution capabilities of the SAMI payload in practice. Future work includes using the results of the study to correct optical imperfections in imagery taken with SAMI.

SAMI↗

Status of MODIS Spatial and Spectral Characterization and Performance

Since launch, both Terra and Aqua MODIS instruments have continued to operate and make measurements of the earth's top of atmospheric (TOA) radiances and reflectance. MODIS collects data in 36 spectral bands covering wavelengths from 0.41 to 14.4 microns. These spectral bands and detectors are located on four focal plane assemblies (FPAs). MODIS on-board calibrators (OBC) include a spectro-radiometric calibration assembly (SRCA), which was designed to characterize and monitor sensor spatial and spectral performance, such as on-orbit changes in the band-to-band registration (BBR), modulation transfer function (MTF), spectral band center wavelengths (CW) and bandwidths (BW). In this paper, we provide a status update of MODIS spatial and spectral characterization and performance, following a brief description of SRCA functions and on-orbit calibration activities. Sensor spatial and spectral performance parameters derived from SRCA measurements are introduced and discussed. Results show that on-orbit spatial performance has been very stable for both Terra and Aqua MODIS instruments. The large BBR shifts in Aqua MODIS, an issue identified pre-launch, have remained the same over its entire mission. On-orbit changes in CW and BW are less than 0.5 nm and 1 nm, respectively, for most VIS/NIR spectral bands of both instruments.

Link, Daniel↗

Marked point process models of raindrop-size distributions

The principal process considered in this paper is the flux of raindrops through a volume of the atmosphere. This process is of fundamental importance for a wide variety of engineering and environmental problems, notably remote sensing of precipitation, infiltration of rainfall, soil erosion, atmospheric deposition of pollutants, and design of microwave communication systems. A marked point process model is developed in which the point process represents the arrival times of drops at the upper surface of a sample volume and the mark associated with a drop is its diameter. In the model, both the rate of occurrence of raindrops and the distribution of drop diameters vary randomly over time. Results that relate the drop-size distribution within the sample volume to the probability law of the drop-arrival process are presented. These results allow straightforward comparisons between temporal characterizations of drop-size distributions and spatial characterizations. Representations for derived processes such as rainfall rate and reflectivity are shown to be quite accurate using raindrop data from North Carolina.

Smith, James A.↗

Results of MODIS Band-to-Band Registration Characterization Using On-Orbit Lunar Observations

Since launch, lunar observations have been made regularly by both Terra and Aqua MODIS and used for a number of sensor calibration and characterization related applications, including radiometric stability monitoring, spatial characterization, optical leak and electronic cross-talk characterization, and calibration inter-comparison. MODIS has 36 spectral bands with a total of 490 individual detectors. They are located on four focal plane assemblies (FPA). This paper focuses on the use of MODIS lunar observations to characterize its band-to-band registration (BBR). In addition to BBR, the approach developed by the MODIS Characterization Support Team (MCST) can be used to characterize MODIS detector-to-detector registration (DDR). Long-term BBR results developed from this approach are presented and compared with that derived from a unique on-board calibrator (OBC). Results show that on-orbit changes of BBR have been very small for both Terra and Aqua MODIS and this approach can be applied to other remote sensing instruments.

Xiong, Xiaoxiong↗