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At least 1,081 records · Page 60

In situ ozone data for evaluation of the laser absorption spectrometer ozone remote sensor: 1979 southeastern Virginia urban plume study summer field program

Ozone data from the 1979 Southeastern Virginia Urban Study (SEV-UPS) field program are presented. The SEV-UPS was conducted for evaluation of an ozone remote sensor, the Laser Absorption Spectrometer. During the measurement program, remote-sensor evaluation was in two areas; (1) determination of the remote sensor's accuracy, repeatability, and operational characteristics, and (2) demonstration of the application of remotely sensed ozone data in air-quality studies. Data from six experiments designed to provide in situ ozone data for evaluation of the sensor in area 1, above, are presented. Experiments consisted of overflights of a test area with the remote sensor aircraft while in situ measurements with a second aircraft and selected surface stations provided correlative ozone data within the viewing area of the remote sensor.

Gregory, G. L.↗

Meteorological and air pollution modeling for an urban airport

Results are presented of numerical experiments modeling meteorology, multiple pollutant sources, and nonlinear photochemical reactions for the case of an airport in a large urban area with complex terrain. A planetary boundary-layer model which predicts the mixing depth and generates wind, moisture, and temperature fields was used; it utilizes only surface and synoptic boundary conditions as input data. A version of the Hecht-Seinfeld-Dodge chemical kinetics model is integrated with a new, rapid numerical technique; both the San Francisco Bay Area Air Quality Management District source inventory and the San Jose Airport aircraft inventory are utilized. The air quality model results are presented in contour plots; the combined results illustrate that the highly nonlinear interactions which are present require that the chemistry and meteorology be considered simultaneously to make a valid assessment of the effects of individual sources on regional air quality.

Swan, P. R.↗

Evaluation of three techniques for classifying urban land cover patterns using LANDSAT MSS data

Three computer quantitative techniques for determining urban land cover patterns are evaluated. The techniques examined deal with the selection of training samples by an automated process, the overlaying of two scenes from different seasons of the year, and the use of individual pixels as training points. Evaluation is based on the number and type of land cover classes generated and the marks obtained from an accuracy test. New Orleans, Louisiana and its environs form the study area.

Baumann, P. R.↗

Summary of measurement results of ozone, methane, and nonmethane hydrocarbons for C-54 aircraft. 1979 Southeastern Virginia Urban Plume Study

Methane, nonmethane hydrocarbon, and ozone data collected in a C-54 aircraft during the 1979 Southeastern Virginia Urban Plume Study are presented. Three major aircraft experiments were flown on five separate days in August collecting 20 hours of flight data. Direct correlation between ozone and hydrocarbon plumes was observed on several occasions.

Cofer, W. R., III↗

Applications of HCMM satellite data to the study of urban heating patterns

A research summary is presented and is divided into two major areas, one developmental and the other basic science. In the first three sub-categories are discussed: image processing techniques, especially the method whereby surface temperature image are converted to images of surface energy budget, moisture availability and thermal inertia; model development; and model verification. Basic science includes the use of a method to further the understanding of the urban heat island and anthropogenic modification of the surface heating, evaporation over vegetated surfaces, and the effect of surface heat flux on plume spread.

Carlson, T. N.↗

Urban air pollution and solar energy

The design and performance of solar energy systems for many potential applications (industrial/residential heat, electricity generation by solar concentration and photovoltaics) will be critically affected by local insolation conditions. The effects of urban air pollution are considered and reviewed. A study of insolation data for Alhambra, California (9 km south of Pasadena) shows that, during a recent second-stage photochemical smog alert (greater than or equal to 0.35 ppm ozone), the direct-beam insolation at solar noon was reduced by 40%, and the total global by 15%, from clean air values. Similar effects have been observed in Pasadena, and are attributable primarily to air pollution. Effects due to advecting smog have been detected 200 km away, in the Mojave Desert. Preliminary performance and economic simulations of solar thermal and photovoltaic power systems indicate increasing nonlinear sensitivity of life cycle plant cost to reductions in insolation levels due to pollution.

Gammon, R. B.↗

Detecting residential land-use development at the urban fringe

Problems associated with the use of Landsat multispectral scanner (MSS) imagery for the detection of urban growth and land use patterns are discussed. The presence of vegetation, either original or added between scanning periods, has been found to dramatically effect the range of signatures in a given area. Different land use developmental stages have been successfully identified by means of 1:50,000 scale panchromatic aerial photography, a resolution only considered possible by spaceborne instrumentation with the advent of the Landsat D satellite. Textural information generated through the grey-tone spatial-dependency matrix for the Landsat band 5 data is compared for different years and a change detection algorithm is described. It is found that the addition of vegetation during development after the removal of natural vegetation resulted in error of omission in the single band data, which must therefore only be used in concert with other data sources.

Jensen, J. R.↗

Urban area change detection procedures with remote sensing data

The underlying factors affecting the detection and identification of nonurban to urban land cover change using satellite data were studied. Computer programs were developed to create a digital scene and to simulate the effect of the sensor point spread function (PSF) on the transfer of modulation from the scene to an image of the scene. The theory behind the development of a digital filter representing the PSF is given as well as an example of its application. Atmospheric effects on modulation transfer are also discussed. A user's guide and program listings are given.

Maxwell, E. L.↗

The evaluation of alternate methodologies for land cover classification in an urbanizing area

The usefulness of LANDSAT in classifying land cover and in identifying and classifying land use change was investigated using an urbanizing area as the study area. The question of what was the best technique for classification was the primary focus of the study. The many computer-assisted techniques available to analyze LANDSAT data were evaluated. Techniques of statistical training (polygons from CRT, unsupervised clustering, polygons from digitizer and binary masks) were tested with minimum distance to the mean, maximum likelihood and canonical analysis with minimum distance to the mean classifiers. The twelve output images were compared to photointerpreted samples, ground verified samples and a current land use data base. Results indicate that for a reconnaissance inventory, the unsupervised training with canonical analysis-minimum distance classifier is the most efficient. If more detailed ground truth and ground verification is available, the polygons from the digitizer training with the canonical analysis minimum distance is more accurate.

Smekofski, R. M.↗

The classification of LANDSAT data for the Orlando, Florida, urban fringe area

Procedures used to map residential land cover on the Orlando, Florida, Urban fringe zone are detailed. The NASA Bureau of the Census Applications Systems Verification and Transfer project and the test site are described as well as the LANDSAT data used as the land cover information sources. Both single-date LANDSAT data processing and multitemporal principal components LANDSAT data processing are described. A summary of significant findings is included.

Walthall, C. L.↗

An evaluation of Seasat SAR imagery for urban analysis

Digitally processed Seasat SAR imagery of the Denver, Colorado, area is analyzed with regard to the types of urban data that can be detected and/or inferred from satellite-borne L-band systems. Black-and-white images of the scene were generated at three scales to determine the advantages and detail discernible at each level of display. The large-scale imagery was density-sliced to evaluate the feasibility of producing a semiautomated land-cover classification from the SAR data. Gray level classes were assigned colors to aid interpretation and subsequently compared with the black-and-white images to assess the contribution of each technique and benefits of combining the data from both procedures.

Henderson, F. M.↗

An Initial Analysis of LANDSAT-4 Thematic Mapper Data for the Discrimination of Agricultural, Forested Wetland, and Urban Land Covers

An initial analysis of LANDSAT 4 Thematic Mapper (TM) data for the discrimination of agricultural, forested wetland, and urban land covers is conducted using a scene of data collected over Arkansas and Tennessee. A classification of agricultural lands derived from multitemporal LANDSAT Multispectral Scanner (MSS) data is compared with a classification of TM data for the same area. Results from this comparative analysis show that the multitemporal MSS classification produced an overall accuracy of 80.91% while the TM classification yields an overall classification accuracy of 97.06% correct.

Quattrochi, D. A.↗

An Initial Analysis of LANDSAT-4 Thematic Mapper Data for the Discrimination of Agricultural, Forested Wetlands, and Urban Land Cover

The capabilities of TM data for discriminating land covers within three particular cultural and ecological realms was assessed. The agricultural investigation in Poinsett County, Arkansas illustrates that TM data can successfully be used to discriminate a variety of crop cover types within the study area. The single-date TM classification produced results that were significantly better than those developed from multitemporal MSS data. For the Reelfoot Lake area of Tennessee TM data, processed using unsupervised signature development techniques, produced a detailed classification of forested wetlands with excellent accuracy. Even in a small city of approximately 15,000 people (Union City, Tennessee). TM data can successfully be used to spectrally distinguish specific urban classes. Furthermore, the principal components analysis evaluation of the data shows that through photointerpretation, it is possible to distinguish individual buildings and roof responses with the TM.

Quattrochi, D. A.↗

Improved classification of small-scale urban watersheds using thematic mapper simulator data

The utility of Landsat MSS classification methods in the case of small, highly urbanized hydrological basins containing complex land-use patterns is limited, and is plagued by misclassifications due to the spectral response similarity of many dissimilar surfaces. Landsat MSS data for the Conley Creek basin near Atlanta, Georgia, have been compared to thematic mapper simulator (TMS) data obtained on the same day by aircraft. The TMS data were able to alleviate many of the recurring patterns associated with MSS data, through bandwidth optimization, an increase of the number of spectral bands to seven, and an improvement of ground resolution to 30 m. The TMS is thereby able to detect small water bodies, powerline rights-of-way, and even individual buildings.

Owe, M.↗

Use of the TM tasseled cap transform for interpretation of spectral contrasts in an urban scene

Investigations are being conducted with the objective to develop automated numerical image analysis procedures. In this context, an examination is performed of physically-based multispectral data transforms as a means to incorporate a priori knowledge of land radiance properties in the analysis process. A physically-based transform of TM observations was developed. This transform extends the Landsat MSS Tasseled Cap transform reported by Kauth and Thomas (1976) to TM data observations. The present study has the aim to examine the utility of the TM Tasseled Cap transform as applied to TM data from an urban landscape. The analysis conducted is based on 512 x 512 subset of the Washington, DC November 2, 1982 TM scene, centered on Springfield, VA. It appears that the TM tasseled cap transformation provides a good means to explain land physical attributes of the Washington scene. This result provides a suggestion regarding a direction by which a priori knowledge of landscape spectral patterns may be incorporated into numerical image analysis.

Goward, S. N.↗

Analysis methods for Thematic Mapper data of urban regions

Studies have indicated the difficulty in deriving a detailed land-use/land-cover classification for heterogeneous metropolitan areas with Landsat MSS and TM data. The major methodological issues of digital analysis which possibly have effected the results of classification are examined. In response to these methodological issues, a multichannel hierarchical clustering algorithm has been developed and tested for a more complete analysis of the data for urban areas.

Wang, S. C.↗

The use of multidate multichannel radiance data in urban feature analysis

Two images were obtained from thematic mappers on Landsats 4 and 5 over the Washington, DC area during November 1982 and March 1984. Selected training areas containing different types of urban land use were examined,one area consisting entirely of forest. Mean digital radiance values for each bandpass in each image were examined, and variances, standard deviations, and covariances between bandpasses were calculated. It has been found that two bandpasses caused forested areas to stand out from other land use types, especially for the November 1982 image. In order to evaluate quantitatively the possible utility of the principal components analysis in selected feature extraction, the eigenvectors were evaluated for principal axes rotations which rendered each selected land use type most separable from all other land use types. The evaluated eigenvectors were plotted as a function of land use type, whose order was decided by considering anticipated shadow component and by examining the relative loadings indicative of vegetation for each of the principal components for the different features considered. The analysis was performed for each seven-band image separately and for the two combined images. It was found that by combining the two images, more dramatic land use type separation could be obtained.

Duggin, M. J.↗