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At least 55 records · Page 3

Operational MTF for Landsat Thematic Mapper

The Landsat Thematic Mapper (TM) represents significant improvements in spatial, spectral, and radiometric resolution over the older Multispectral Scanner System (MSS). For the last three years, NASA has conducted the Landsat Image Data Quality Analysis (LIDQA) program to quantify the performance of the TM on the Landsat-4 and 5 spacecraft. As part of this program, analysis of the TM imagery to extract the overall system modulation transfer function (MTF) has been performed. In this paper, the San Mateo Bridge in San Francisco is described as a target for calculation of the line spread function and MTF. The analysis of two TM scenes, one from 12/31/82 and one from 8/12/83, yielded effective-instantaneous-field-of-views (EIFOVs) of 40.8 meters and 48.6 meters, respectively. These values are compared with the 33.8 meter EIFOV predicted by component modelling of the TM sensor, and the differences discussed.

Schowengerdt, R.↗

LANDSAT-4 MSS and Thematic Mapper data quality and information content analysis

LANDSAT-4 thematic mapper (TM) and multispectral scanner (MSS) data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and supervised classifiers on test data. A detailed spectral class analysis (multispectral classification) was carried out to compare the information content of the MSS and TM for a large number of scene classes. A temperature-mapping experiment was carried out for a cooling pond to test the quality of thermal-band calibration. Overall TM data quality is very good. The MSS data are noisier than previous LANDSAT results.

Anuta, P.↗

Landsat-4 MSS and Thematic Mapper data quality and information content analysis

Landsat-4 Thematic Mapper and Multispectral Scanner data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic Mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and numerous supervised classifiers on data from Iowa and Illinois. A detailed spectral class analysis (multispectral classification) was carried out on data from the Des Moines, IA area to compare the information content of the MSS and TM for a large number of scene classes.

Anuta, P. E.↗

Investigation of several aspects of LANDSAT-4 data quality

Preliminary analysis of band-to-band registration in a TM scene of San Francisco, California by flickering different band pairs on the display showed no major problems. The power spectra of individual lines in each band on the A-tape of a Washington, D.C. scene, which represented data from individual detectors, was calculated. The power spectra for each detector were averaged and the peak-to-peak amplitudes were calculated as a function of frequency. Estimated system modulation transfer functions were calculated for bands 3 and 4 for a 128 x 128 pixel area of the San Francisco Bay containing the San Matteo Bridge. The shape and width of the modulation transfer functions appear reasonable, but further study is required to establish confidence in the results which yield an effective-instantaneous field of view of 33.6 meters and 40.8 meters in bands 3 and 4, respectively.

Wrigley, R. C.↗

Quasi Real Time Data Analysis for Air Quality Monitoring with an Electronic Nose

Cabin Air Quality Monitoring: A) Functions; 1) Incident monitor for targeted contaminants exceeding targeted concentrations. Identify and quantify. 2) Monitor for presence of compounds associated with fires or overheating electronics. 3) Monitor clean-up process. B) Characteristics; 1) Low mass, low power device. 2) Requires little crew time for maintenance and calibration. 3) Detects, identifies and quantifies selected chemical species at or below 24 hour SMAC.

data analysis↗

Enabling Analysis of Air Quality Data From Tropospheric Emissions: Monitoring of POllution (Tempo) Via Cloud-Based Tools

Launched in April 2023, the Tropospheric Emissions: Monitoring of POllution (TEMPO) instrument provides high-resolution measurements of key atmospheric pollutants, such as ozone, nitrogen dioxide, and formaldehyde. Maximizing the use and utility of this new source of air quality information requires streamlining data access for a wide variety of research, public health, and other interested users. These varied applications often require the data to be structured in different ways, e.g., specific formats, array shapes, or file sizes. To enable access to TEMPO data in different forms, the NASA Atmospheric Science Data Center (ASDC), as part of the NASA Earth Science Data and Information System (ESDIS), provides a variety of cloud-based data transformation and GIS visualization tools. This presentation demonstrates methods of accessing and working with TEMPO data through these services, while highlighting aspects of the software and algorithmic workflows that perform the necessary data transformations. Examples include data subsetting, concatenation, and visualizations accessible via Jupyter notebooks and GIS software.

Daniel Kaufman↗

Image processing developments and applications for water quality monitoring and trophic state determination

Remote sensing data analysis of water quality monitoring is evaluated. Data anaysis and image processing techniques are applied to LANDSAT remote sensing data to produce an effective operational tool for lake water quality surveying and monitoring. Digital image processing and analysis techniques were designed, developed, tested, and applied to LANDSAT multispectral scanner (MSS) data and conventional surface acquired data. Utilization of these techniques facilitates the surveying and monitoring of large numbers of lakes in an operational manner. Supervised multispectral classification, when used in conjunction with surface acquired water quality indicators, is used to characterize water body trophic status. Unsupervised multispectral classification, when interpreted by lake scientists familiar with a specific water body, yields classifications of equal validity with supervised methods and in a more cost effective manner. Image data base technology is used to great advantage in characterizing other contributing effects to water quality. These effects include drainage basin configuration, terrain slope, soil, precipitation and land cover characteristics.

Blackwell, R. J.↗

Impact of Canadian Wildfires 2023 on North Atlantic's Region Air Quality: An Analysis Using ASDC Data

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. NASA's Atmospheric Science Data Center (ASDC) is in the Science Directorate located at NASA'S Langley Research Center in Hampton, Virginia. The Science Directorate's Climate Science Branch, Atmospheric Composition Branch, and Chemistry and Dynamics Branch work with ASDC to study changes in the Earth and its atmosphere. ASDC projects focus on the Earth science disciplines: Radiation Budget, Clouds, Aerosols, and Tropospheric Composition. All the products chosen for this analysis are products hosted by ASDC and available for users to obtain via our services [1].

Hazem Mahmoud↗

Impact of Canadian Wildfires on Mid Atlantic’s Region Air Quality: An Analysis Using ASDC Data

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗

Quality Control and Analysis of Microphysical Data Collected in TRMM Aircraft Validation Experiments

This report summarizes our efforts on the funded project 'Quality Control and Analysis of Microphysical Data Collected in TRMM Airborne Validation Experiments', NASA NAG5-9663, Andrew Heymsfield, P. I. We begin this report by summarizing our activities in FY2000-FY2004. We then present some highlights of our work. The last part of the report lists the publications that have resulted from our funding through this grant.

Heymsfield, Andrew J.↗

Analysis of flexible aircraft longitudinal dynamics and handling qualities. Volume 2: Data

Two analysis methods are applied to a family of flexible aircraft in order to investigate how and when structural (especially dynamic aeroelastic) effects affect the dynamic characteristics of aircraft. The first type of analysis is an open loop modal analysis technique. This method considers the effect of modal residue magnitudes on determining vehicle handling qualities. The second method is a pilot in the loop analysis procedure that considers several closed loop system characteristics. Both analyses indicated that dynamic aeroelastic effects caused a degradation in vehicle tracking performance, based on the evaluation of some simulation results. Volume 2 consists of the presentation of the state variable models of the flexible aircraft configurations used in the analysis applications mode shape plots for the structural modes, numerical results from the modal analysis frequency response plots from the pilot in the loop analysis and a listing of the modal analysis computer program.

Waszak, M. R.↗

User's Guide for ERB 7 Matrix. Volume 1: Experiment Description and Quality Control Report for Year 1

The Nimbus 7 ERB MATRIX Tape is a computer program in which radiances and irradiances are converted into fluxes which are used to compute the basic scientific output parameters, emitted flux, albedo, and net radiation. They are spatially averaged and presented as time averages over one-day, six-day, and monthly periods. MATRIX data for the period November 16, 1978 through October 31, 1979 are presented. Described are the Earth Radiation Budget experiment, the Science Quality Control Report, Items checked by the MATRIX Science Quality Control Program, and Science Quality Control Data Analysis Report. Additional material from the detailed scientific quality control of the tapes which may be very useful to a user of the MATRIX tapes is included. Known errors and data problems and some suggestions on how to use the data for further climatologic and atmospheric physics studies are also discussed.

Tighe, R. J.↗

Camera Setup for Unsteady Pressure Sensitive Paint at NASA Ames Research Center

The unsteady Pressure-Sensitive Paint Development Team at NASA Ames Research Center is conducting a Launch Vehicle Demo Test in the Unitary Plan Wind Tunnel’s 11-ft Transonic Wind Tunnel in the first half of 2024 to showcase improvements made to unsteady Pressure-Sensitive Paint technology. The unsteady Pressure-Sensitive Paint setup has upgraded from a four-camera system to an eight-camera system, prompting analysis to maximize the system performance and overall data quality. Additional analysis was performed to maximize the system resolving power when subject to test constraints such as model size and model tunnel positions. These analyses have uncovered new opportunities to improve the unsteady Pressure-Sensitive Paint technology and will allow the system to collect higher quality data with simple changes to the setup procedure.

Camera Calibration↗

Visual Data Analysis for Satellites

The Visual Data Analysis Package is a collection of programs and scripts that facilitate visual analysis of data available from NASA and NOAA satellites, as well as dropsonde, buoy, and conventional in-situ observations. The package features utilities for data extraction, data quality control, statistical analysis, and data visualization. The Hierarchical Data Format (HDF) satellite data extraction routines from NASA's Jet Propulsion Laboratory were customized for specific spatial coverage and file input/output. Statistical analysis includes the calculation of the relative error, the absolute error, and the root mean square error. Other capabilities include curve fitting through the data points to fill in missing data points between satellite passes or where clouds obscure satellite data. For data visualization, the software provides customizable Generic Mapping Tool (GMT) scripts to generate difference maps, scatter plots, line plots, vector plots, histograms, timeseries, and color fill images.

Lau, Yee↗

Radiometric analyses of Landsat-4 digital image data

The results of analyses of the radiometric characteristics of digital image data produced by the Landsat 4 MSS and TM sensors are reviewed. The MSS analysis found high quality data comparable to the products of previous Landsats, except for a low-level coherent noise effect having a magnitude of about 0.5 counts in each band and a spatial period of about 3.6 pixels. The TM analysis found excellent spatial resolution, generally high data quality and expected scan-angle effects. Procedures for equalizing detector responses appear to be working as intended. Two low-amplitude artifacts also were discovered. The first is associated with the direction of scan (TM employs bidirectional scanning). The second, a very low employs bidirectional scanning). The second, a very low frequency level-shift artifact which produces image banding that is most pronounced in TM1, could be a serious problem for water-related applications or others where average signal levels are low. Correction procedures are under investigation.

Malila, W. A.↗

Analysis of the quality of image data acquired by the LANDSAT-4 Thematic Mapper and Multispectral Scanners

The geometric quality of TM film and digital products is evaluated by making selective photomeasurements and by measuring the coordinates of known features on both the TM products and map products. These paired observations are related using a standard linear least squares regression approach. Using regression equations and coefficients developed from 225 (TM film product) and 20 (TM digital product) control points, map coordinates of test points are predicted. The residual error vectors and analysis of variance (ANOVA) were performed on the east and north residual using nine image segments (blocks) as treatments. Based on the root mean square error of the 223 (TM film product) and 22 (TM digital product) test points, users of TM data expect the planimetric accuracy of mapped points to be within 91 meters and within 117 meters for the film products, and to be within 12 meters and within 14 meters for the digital products.

Colwell, R. N.↗