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Ormsby, J. P.

Publications and source records attributed to Ormsby, J. P..

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Remote sensing for oceanography, hydrology and agriculture; Proceedings of Symposia A5, A3 and A9 of the COSPAR 29th Plenary Meeting, Washington, Aug. 28-Sept. 5, 1992

New results from satellite studies of the ocean and radar mapping of the earth are presented. Atttention is given to data from the ERS-1 satellite. Synthetic aperture radar mapping of land surface features and sea ice, radar backscatter measurements, and orbit altitude measurements are discussed. The use of remote sensing in hydrology, soil moisture determination, precipitation measurement, agricultural meteorology, and crop growth estimation is reviewed.

Gower, J. F. R.↗
NASA NTRS1993

HYDROSAT - An instrument platform for hydrology

This paper discusses a multisensor satellite approach for the study of hydrological applications. Spectral as well as spatial and temporal characteristics of specific operational and planned instruments applicable to hydrology are presented. A hydrology specific series of sensors are proposed to fill the gaps not covered by the current and planned systems. We have called this hypothetical platform HYDROSAT. In addition, the trade-offs between a geostationary satellite and a polar orbiter are explored.

Ormsby, J. P.↗
NASA NTRS1992

Evaluation of natural and man-made features using Landsat TM data

Landsat-5 TM data of a subscene of Washington, D.C. are utilized to distinguish man-made and natural surfaces through analysis of their spectral response. A quantitative measure of the separability and thus the ability to separate different surface features is calculated utilizing the quantity known as divergence, a measure of the dissimilarity between two distributions. The thermal band, TM band 6 (10.4-12.5 microns), was shown to improve the separability when replacing a visible band, but decreased the separability when included with the middle IR bands.

Ormsby, J. P.↗
NASA NTRS1987

Vegetation spatial variability and its effect on vegetation indices

Landsat MSS data were used to simulate low resolution satellite data, such as NOAA AVHRR, to quantify the fractional vegetation cover within a pixel and relate the fractional cover to the normalized difference vegetation index (NDVI) and the simple ratio (SR). The MSS data were converted to radiances from which the NDVI and SR values for the simulated pixels were determined. Each simulated pixel was divided into clusters using an unsupervised classification program. Spatial and spectral analysis provided a means of combining clusters representing similar surface characteristics into vegetated and non-vegetated areas. Analysis showed an average error of 12.7 per cent in determining these areas. NDVI values less than 0.3 represented fractional vegetated areas of 5 per cent or less, while a value of 0.7 or higher represented fractional vegetated areas greater than 80 per cent. Regression analysis showed a strong linear relation between fractional vegetation area and the NDVI and SR values; correlation values were 0.89 and 0.95 respectively. The range of NDVI values calculated from the MSS data agrees well with field studies.

Ormsby, J. P.↗
NASA NTRS1987

Quantifying spatial and temporal variabilities of microwave brightness temperature over the U.S. Southern Great Plains

Spatial and temporal variabilities of microwave brightness temperature over the U.S. Southern Great Plains are quantified in terms of vegetation and soil wetness. The brightness temperatures (TB) are the daytime observations from April to October for five years (1979 to 1983) obtained by the Nimbus-7 Scanning Multichannel Microwave Radiometer at 6.6 GHz frequency, horizontal polarization. The spatial and temporal variabilities of vegetation are assessed using visible and near-infrared observations by the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR), while an Antecedent Precipitation Index (API) model is used for soil wetness. The API model was able to account for more than 50 percent of the observed variability in TB, although linear correlations between TB and API were generally significant at the 1 percent level. The slope of the linear regression between TB and API is found to correlate linearly with an index for vegetation density derived from AVHRR data.

Choudhury, B. J.↗
NASA NTRS1986

Wetland physical and biotic studies using multispectral data

A November 1982 Landsat-4 TM scene and March and September 1984 airborne L-band radar data for a brackish-wetland area of the Blackwater National Wildlife Refuge (near Chesapeake Bay) are analyzed to monitor changes in vegetation and water area. The accuracy of level-I classification of the TM image is found to be 81 percent, but that of the few level-II/III classes for which ground truth was available is only 53 percent. The value of radar images for discriminating water areas obscured by vegetation and estimating plant heights is indicated.

Ormsby, J. P.↗
NASA NTRS1985

The effects of merging TM and A/C radar on wetland classification

While radar does not provide detailed begetation discrimination, it provide the means to separate areas of different moisture conditions. Thus, the use of LANDSAT Thematic Mapper (TM) in conjunction with the microwave data was attempted. If successful, information on shoreline cover, emergent wetland vegetation and extent, and submerged grassbeds would provide much needed data for planning and maintenance of wetlands. Originally, the goal was to determine the accuracy with which one could categorize various types of vegetation and land use within an inland wetland using LANDSAT TM data. First, a Level 1/2 supervised classification was performed. Following a more detailed ground trust survey, a Level 3 classification was done. Aircraft L-band radar data were received and the decision was made to merge the TM and L-band data and assess whether vegetation catagories within the wetland areas could be better defined. Preliminary results indicate vegetation delineation is improved for open agricultural areas and water, but other features are more confused.

Ormsby, J. P.↗
NASA NTRS1985

Detection of lowland flooding using active microwave systems

The development of radar systems with longer wavelenths (greater than 3 cm) has provided new possibilities regarding the utilization of radar. Thus, it has been found that the interpretation of data from radar images can be a valuable classification aid for applications related to water resources. In the case of an interpreter accustomed to photographic or visible/infrared images, an evaluation of radar images presents some problems, because the radar is sensing a set of surface characteristics which have little influence on visible/infrared systems. Detectable features in radar images caused by differences in dielectric properties are usually associated with the water content of either soils or vegetation. The present paper is concerned with studies which were initiated in 1976. The studies had the objective to define the magnitude of the effects on radar data caused by flood waters under vegetation. The obtained results indicate the feasibility to detect flood conditions beneath a forest canopy, and to obtain an improved definition of the land-water boundary.

Ormsby, J. P.↗
NASA NTRS1984

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.↗
NASA NTRS1983

Use of Seasat synthetic aperture radar and Landsat multispectral scanner subsystem data for Alaskan glaciology studies

Three Seasat synthetic aperture radar (SAR) and three Landsat multispectral scanner subsystem (MSS) scenes of three areas of Alaska were analyzed for hydrological information. The areas were: the Dease Inlet in northern Alaska and its oriented or thaw lakes, the Ruth and Tokositna valley glaciers in south central Alaska, and the Malaspina piedmont glacier on Alaska's southern coast. Results for the first area showed that the location and identification of some older remnant lake basins were more easily determined in the registered data using an MSS/SAR overlay than in either SAR or MSS data alone. Separately, both SAR and MSS data were useful for determination of surging glaciers based on their distinctive medial moraines, and Landsat data were useful for locating the glacier firn zone. For the Malaspina Glacier scenes, the SAR data were useful for locating heavily crevassed ice beneath glacial debris, and Landsat provided data concerning the extent of the debris overlying the glacier.

Hall, D. K.↗
NASA NTRS1982

Classification of simulated and actual NOAA-6 AVHRR data for hydrologic land-surface feature definition

An examination of the possibilities of using Landsat data to simulate NOAA-6 Advanced Very High Resolution Radiometer (AVHRR) data on two channels, as well as using actual NOAA-6 imagery, for large-scale hydrological studies is presented. A running average was obtained of 18 consecutive pixels of 1 km resolution taken by the Landsat scanners were scaled up to 8-bit data and investigated for different gray levels. AVHRR data comprising five channels of 10-bit, band-interleaved information covering 10 deg latitude were analyzed and a suitable pixel grid was chosen for comparison with the Landsat data in a supervised classification format, an unsupervised mode, and with ground truth. Landcover delineation was explored by removing snow, water, and cloud features from the cluster analysis, and resulted in less than 10% difference. Low resolution large-scale data was determined useful for characterizing some landcover features if weekly and/or monthly updates are maintained.

Ormsby, J. P.↗
NASA NTRS1982

The use of Landsat-3 thermal data to help differentiate land covers

Landsat-3 Multispectral Scanner Subsystem (MSS) digital data of the Baltimore, Maryland area gathered on May 24, 1978, are examined to show the usefulness of thermal data in providing better discrimination between agricultural and residential areas, certain types of urban/industrial areas and water, cloud shadows and water, and bare-extractive areas and bright urban cover types. High altitude aircraft imagery taken on May 3, 1978, provides ground truth and training site verification. Two classifications are made for each training site: the initial one using bands 4, 5, and 7 and a second in which the thermal data are included with the visible and near infrared data. This permits a direct comparison of areas spectrally similar with and without the inclusion of the thermal data. Commission errors determined from selected subsets of the data show reductions of 95% for the urban/industrial versus water themes, 84% for the residential versus agriculture themes, 64.0% for the bare-extractive versus bright urban themes, and 24% for the cloud shadow versus water themes when the thermal data are included in the signature.

Ormsby, J. P.↗
NASA NTRS1979

LANDSAT digital analysis of the initial recovery of the Kokolik River tundra fire area, Alaska

The author has identified the following significant results. Considerable regrowth of vegetation was observed between August 1977 and August 1978, both in the field and through analysis of LANDSAT near infrared digital data. The spectral reflectances in the burned areas were found to increase with the age of the burn in a one year period due to vegetation regrowth. Regrowth was particularly evident in the lightly burned portions of the burned area. Image analysis techniques using the AOIPS system permitted delineation of burn severity categories. The conditions and type of ground cover prior to the fire influenced the severity of burning, as did the direction of the winds while the burning was in progress as determined from field and LANDSAT observations. More severe burning was induced by winds blowing in the northeastern and southeastern portions of the burned area.

Hall, D. K.↗
NASA NTRS1979

Results of a statistical approach to rainfall estimation using Nimbus 5 6.7 micrometers and 11.5 micrometers THIR data

Nimbus 5 6.7 mm and 11.5 mm temperature humidity infrared radiometer (THIR) data were used in a simple multiple regression scheme to test the feasibility of using these data to estimate hourly rainfall. Throughout the test area (85 W to 105 W and 45 N to 30 N) subareas (8 deg x 6 deg) were chosen from which point to point and areal statistics were obtained. Four subsets of data were used. The first consisted of only those surface stations indicating precipitation whose latitude and longitude coincided with the THIR grid points. A second used surface stations 0.1 degree from the THIR grid points. The third was a combination of subsets one and two. A reciprocal distance weighting scheme was used to derive precipitation values in data sparse areas. A fourth subset was made using these data combined with the data from subsets one and two. Point estimates resulted in negative correlations between estimated and grid derived "surface" precipitation. One degree areal estimates showed a slight improvement with a correlation coefficient of approximately 0.11. Single regression areal estimates resulted in correlations of approximately 0.11 and 0.20 for the 6.7 mm and 11.5 mm data respectively. These poor results were attributed to problems which are inherent in the satellite data (location errors, short temporal span of data, wavelength of sensors, etc.) and the lack of sufficient surface data to better verify the satellite estimate.

Ormsby, J. P.↗
NASA NTRS1977

Mesoscale cloud phenomena observed by LANDSAT

Examples of certain mesoscale cloud features - jet cirrus, eddies/vortices, cloud banding, and wave clouds - were collected from LANDSAT imagery and placed into Mason's four groups of causes of cloud formation based on the mechanism of vertical motion which produces condensation. These groups are as follows: (1) layer clouds formed by widespread regular ascent; (2) layer clouds caused by irregular stirring motions; (3) convective clouds; and (4) clouds formed by orographic disturbances. These mechanisms explain general cloud formation. Once formed, other forces may play a role in the deformation of a cloud or cloud mass into unusual and unique meso- and microscale patterns. Each example presented is followed by a brief discussion describing the synoptic situation, and some inference into the formation and occurrence of the more salient features. No major attempt was made to discuss in detail the meteorological and topographic interplay producing these mesoscale features.

Ormsby, J. P.↗