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Gervin, J. C.

Publications and source records attributed to Gervin, J. C..

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Science and Observation Recommendations for Future NASA Carbon Cycle Research

Between October 2000 and June 2001, an Agency-wide planning, effort was organized by elements of NASA Goddard Space Flight Center (GSFC) to define future research and technology development activities. This planning effort was conducted at the request of the Associate Administrator of the Office of Earth Science (Code Y), Dr. Ghassem Asrar, at NASA Headquarters (HQ). The primary points of contact were Dr. Mary Cleave, Deputy Associate Administrator for Advanced Planning at NASA HQ (Headquarters) and Dr. Charles McClain of the Office of Global Carbon Studies (Code 970.2) at GSFC. During this period, GSFC hosted three workshops to define the science requirements and objectives, the observational and modeling requirements to meet the science objectives, the technology development requirements, and a cost plan for both the science program and new flight projects that will be needed for new observations beyond the present or currently planned. The plan definition process was very intensive as HQ required the final presentation package by mid-June 2001. This deadline was met and the recommendations were ultimately refined and folded into a broader program plan, which also included climate modeling, aerosol observations, and science computing technology development, for contributing to the President's Climate Change Research Initiative. This technical memorandum outlines the process and recommendations made for cross-cutting carbon cycle research as presented in June. A separate NASA document outlines the budget profiles or cost analyses conducted as part of the planning effort.

McClain, Charles R.↗
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 NTRS1986

The effect of Thematic Mapper spectral properties on land cover mapping for hydrologic modeling

The accuracy of unsupervised land-cover classification from all seven Landsat TM bands and from six combinations of three or four bands is evaluated using images of the Clinton River Basin, a suburban watershed near Detroit. Data from aerial TMS photography, USGS topographic maps, and ground surveys are employed to determine the classification accuracy. The mapping accuracy of all seven bands is found to be significantly better (6 percent overall, 12 percent for residential areas, and 13 percent for commercial districts) than that with bands 2, 3, and 4; but almost the same accuracy is obtained by including at least one band from each major spectral region (visible, NIR, and mid-IR).

Gervin, J. C.↗
NASA NTRS1986

Floodplain land cover mapping using Thematic Mapper data

The accuracy of land-cover classifications based on Landsat-4 TM and MSS images (obtained in August 1982) and airborne TMS images (obtained in September 1981) of the New Martinsville, West Virginia area is evaluated by comparison with ground-truth data. TM, TMS, and MSS are found to have overall mapping accuracies 80.1, 78.5, and 75.6 percent; agriculture/grass accuracies 62.0, 29.7, and 46.6 percent; and developed-area accuracies 67.2, 77.8, and 59.4 percent, respectively.

Kerber, A. G.↗
NASA NTRS1985

Comparison of MSS and TM Data for Landcover Classification in the Chesapeake Bay Area: a Preliminary Report

An area bordering the Eastern Shore of the Chesapeake Bay was selected for study and classified using unsupervised techniques applied to LANDSAT-2 MSS data and several band combinations of LANDSAT-4 TM data. The accuracies of these Level I land cover classifications were verified using the Taylor's Island USGS 7.5 minute topographic map which was photointerpreted, digitized and rasterized. The the Taylor's Island map, comparing the MSS and TM three band (2 3 4) classifications, the increased resolution of TM produced a small improvement in overall accuracy of 1% correct due primarily to a small improvement, and 1% and 3%, in areas such as water and woodland. This was expected as the MSS data typically produce high accuracies for categories which cover large contiguous areas. However, in the categories covering smaller areas within the map there was generally an improvement of at least 10%. Classification of the important residential category improved 12%, and wetlands were mapped with 11% greater accuracy.

Mulligan, P. J.↗
NASA NTRS1985

Comparison of Land Cover Information from LANDSAT Multispectral Scanner (MSS) and Airborne Thematic Mapper Simulator (TMS) Data for Hydrologic Applications

Thematic mapper simulator (TMS) data produced a more accurate and spatially contiguous classification than MSS for the Clinton River Basin in Michigan. While the accuracy of the 4-band TMS data set was as good as the 7-band, the 3-band TMS data sets were also better than the MSS. The combination of bands selected based on the transformed divergence technique provided one band in each of the major regions of the spectrum: visible (band 3), near IR (band 4), middle IR (band 5) and thermal IR (band 7). These results should be viewed with some caution, since the data are from a TMS rather than the actual TM and the MSS data were obtained in early summer while the TMS was flown in late summer. The higher accuracies for the developed categories (residential and commercial) should improve the predictions of runoff in flood forecasting models and of flood damage for damage calculation models appreciably.

Gervin, J. C.↗
NASA NTRS1985

Comparison of level I land cover classification accuracy for MSS and AVHRR data

The capabilities of the Advanced Very-High-Resolution Radiometer (AVHRR) for land-cover mapping were investigated by comparing the accuracy of land-cover information for the Washington, DC area derived from NOAA-7 AVHRR data with that from Landsat Multispectral Scanner Subsystem (MSS) data. Unsupervised level I land-cover classifications were performed for MSS and AVHRR data sets collected on July 11, 1981. A detailed accuracy assessment was conducted based on ground data delineated on 12 U.S. Geological Survey 7-5 min series topographic maps. These results produced overall land-cover classification accuracies of 71.9 and 76.8 per cent for AVHRR and MSS, respectively. While the accuracies for predominant categories were similar for both sensors, land-cover discrimination for less commonly occurring and/or spatially heterogeneous categories was improved with the MSS data set. The AVHRR, however, performed as well as or better than the MSS in classifying large homogeneous areas. The application of AVHRR data with its lower processing cost and more frequent worldwide coverage appears promising for regional land-cover mapping.

Gervin, J. C.↗
NASA NTRS1984

Comparison of Land Cover Information from LANDSAT Multispectral Scanner (MSS) and Airborne Thematic Mapper Simulator (TMS) Data for Hydrologic Applications

Detailed land cover classifications were performed on the Thematic Mapper Simulator (TMS) and MSS data of the Clinton River Basin (acquired on August 19, 1981, and June 28, 1980, respectively) using supervised classification techniques. Differences in interclass separability were compared to select several promising TMS band combinations, selected from the 27 covering the Clinton River Basin. The TMS data produced a more accurate and spatially contiguous classification than MSS for this study site. While the accuracy of the 4-band TM data set was as good as the 7-band, the 3-band TMS data sets were also better than the MSS. These results indicate that both the increased spectral discrimination and spatial resolution contribute to improved classification accuracy. The possibility of reducing the data analysis burden associated with large TM data volumes through effective band selection therefore appears promising. The implications of the improved classification accuracy of TMS data are important for hydrologic and economic modeling. In particular, the higher accuracies for the developed categories (residential and commercial) should improve the predictions of runoff in flood forecasting models and of flood damage for damage calculation models appreciably.

Gervin, J. C.↗
NASA NTRS1984

Hydrological planning studies using Landsat-4 Thematic Mapper (TM)

NASA, in cooperation with the U.S. Army Corps of Engineers, is evaluating the capabilities of Landsat 4 Thematic Mapper (TM) data for environmental and hydrological applications. Attention is given to the results of studies conducted at the Clinton River Basin in Michigan and the eastern shore of the Chesapeake Bay in Maryland. In the former, the evaluation conducted was for the band combinations: (1) 2, 3, and 4; (2) 3, 4, and 5; (3) 3, 4, 5, and 6; and (4) all seven bands. In the latter case, Multispectral Scanner (MSS) and TM data were classified for combinations (1), (3) and (4). Wetland classification accuracy for the 7-band TM data in this study was found to be 9 percent higher than with MSS data, allowing more reliable and accurate monitoring.

Gervin, J. C.↗
NASA NTRS1983

The application of forest classification from Landsat data as a basis for natural hydrocarbon emission estimation and photochemical oxidant model simulations in southeastern Virginia

The possible contribution by natural hydrocarbon emissions to the total ozone budget recorded in the Tidewater region of southeastern Virginia during the height of the summer period was examined. Natural sources investigated were limited to the primary HC emitters and most prevalent natural vegetation, the forests. Three types and their areal coverage were determined for Region VI of the Virginia State Air Pollution Control Board using remotely sensed data from Landsat, a NASA experimental earth resources satellite. Emission factors appropriate to the specific types (coniferous 0.24 x 10 to the 13th, mixed 0.63 x 10 to the 13th, deciduous 1.92 x 10 to the 13th, microgram/h), derived from contemporary procedures, were applied to produce an overall regional emission rate of 2.79 x 10 to the 13th microgram/h for natural non-methane hydrocarbons (NMHC). This rate was used with estimates of the anthropogenic NO(x) and NMHC loading, as input into a photochemical box model. Additional HC loading on the order of that estimated to be produced by the natural forest communities was required in order to reach certain measured summer peak ozone levels as the computer simulation was unable to account for the measured episodic levels on the basis of the anthropogenic inventory alone.

Salop, J.↗
NASA NTRS1983

Comparative accuracies of AVHRR and MSS data used for Level I land cover classifications

The capabilities of the Advanced Very High Resolution Radiometer (AVHRR) for land cover mapping were investigated by comparing the accuracy of land cover information for the Washington, DC area derived from NOAA-7 AVHRR data with that from Landsat Multispectral Scanner (MSS) data. Unsupervised Level I land cover classifications were performed for MSS and AVHRR data sets collected on July 11, 1981. A detailed accuracy assessment was conducted based on ground truth delineated on six USGS 7.5 minute series topographic maps. Preliminary results produced overall land cover classification accuracies of 75.6 percent and 76.1 percent for AVHRR and MSS, respectively. While the accuracies for predominant categories such as agriculture, forest, and urban were similar for both sensors, discrimination of the less commonly occurring categories such as barren, wetland, and water was improved with the MSS data set. The AVHRR, however, performed as well as or better than the MSS in classifying large homogeneous areas. The application of AVHRR data with its lower processing cost and more frequent worldwide coverage appears promising for global land cover mapping.

Gervin, J. C.↗
NASA NTRS1983

Landsat-4 thematic mapper (TM) for cold environments

Landsat-4 was launched into a near-polar, sun-synchronous orbit on July 16, 1982. It is the largest and most complex of NASA's earth resources satellites. Landsat-4's instrument payload includes two remote sensors. The Multispectral Scanner Subsystem (MSS) is an electro-optical scanning radiometer with four spectral bands in the visible and near infrared, which was also carried aboard Landsats 1, 2, and 3. The second sensor, the Thematic Mapper (TM), represents a more advanced remote sensing instrument than the MSS. It uses a scanning mirror assembly to collect data from a 15.4 deg angle on both forward and reverse scans. It is pointed out that the improved spatial, spectral, and radiometric characteristics of TM have significant implications for satellite remote sensing in cold environments. The expected improvements are discussed, giving attention to snow, ice, water, soil, and land cover.

Gervin, J. C.↗
NASA NTRS1982

Comparison of Land Cover Information from LANDSAT MSS and Airborne TMS for Hydrological Applications: Preliminary Results

Land cover information for the Clinton River Basin (Michigan) derived from LANDSAT multispectral scanner (MSS) data was compared with that from airborne thematic mapper simulator (TMS) to investigate the probable capabilities of the thematic mapper (TM) launched aboard LANDSAT-4 in July 1982. The preliminary findings for one 7.5 minute topographic map, Mt. Clemens West, are reported. Significant improvements in land cover classification accuracy were obtained using TMS data as compared with MSS data. Overall mapping accuracy increased from 49 to 61 percent with an improvement from 71 to 84 percent in the residential category. A combination of four bands with one band in each major region of the spectrum (visible, near IR, middle IR and thermal IR) provided as good a discrimination of land cover as all seven TM bands. Based on the improved land cover classification accuracy of TM, TM data has the potential to provide more useful and effective input to US Army Corps of Engineers flood forecasting and flood damage prediction/assessment models.

Gervin, J. C.↗
NASA NTRS1982

LANDSAT Applications for the State of Delaware

The first phase of a cooperative demonstration project between the Eastern Regional Remote Sensing Applications Center and the Delaware Department of Natural Resources and Environmental Control is summarized. Separate land cover classifications were performed for three counties in Delaware using multiseasonal LANDSAT data from April 3 and July 20, 1974. The objective of the New Castle County and Kent County classifications was to provide general land cover information with special emphasis on existing farmland and deciduous and coniferous forest, respectively. A detailed study of existing inland and coastal wetland vegetation communities was attempted for Sussex County. Detailed accuracy assessments were conducted for general land cover in New Castle and Kent Counties and for wetland communities in Sussex County. The classifications were combined to provide a statewide Level I land cover map and acreage statistics. Based on these results, the participating state agencies determined that LANDSAT is a viable tool for mapping and monitoring land cover within the state.

Gervin, J. C.↗
NASA NTRS1982

Natural hydrocarbon emission estimates based on Landsat data as an input to a regional ozone photochemical model

Landsat-derived forest cover data were employed with non-methane hydrocarbon (NMHC) emission rates in a model to quantify summer forest ozone production for the Tidewater Region of Virginia. The areal extent of the three major forest types - coniferous, deciduous, and mixed - were determined from Landsat data on two adjacent scenes, using an unsupervised approach to spectral signature development. The forest type results from both data sets were verified in an extensive accuracy assessment and merged to provide regional statistics for total acreages, percent forest, and error rates. The Landsat statistics were incorporated into forest type emission factor equations to produce an estimated emission rate for natural hydrocarbons from forests. This estimate, along with measured rates for nitrogen oxides and NMHC from anthropogenic sources, was provided as input to computer simulations of atmospheric ozone generation for the Tidewater Region using a photochemical oxident model.

Middleton, E. M.↗
NASA NTRS1981

Improvements in lake volume predictions using Landsat data

A cumulative error in the water balance budget for Lake Okeechobee produces a one million acre-foot discrepancy in the predicted water volume over a 4-year period. The major source of error appears to be complex shoreline marshes that comprise 20 percent of the lake surface. The water balance budget model presently treats these marshes as open water. Using Landsat data, the vegetation in the lake's littoral zone was classified multispectrally to provide a data base for determining water budget information. First, the acreage of a given plant species in the littoral zone was obtained with satellite data. Second, the surface area occupied by plants (which therefore could not be considered open water) was used to adjust the vegetation acreage giving an effective water surface. Based on this information, more detailed representations of evapotranspiration and total water surface (and hence total lake volume) could be provided to the water balance budget computation.

Gervin, J. C.↗