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Pelletier, R. E.

Publications and source records attributed to Pelletier, R. E..

Peat analyses in the Hudson Bay Lowlands using ground penetrating radar

The use of ground penetrating radar (GPR) as a means to determine peak thickness and estimate peat volume in the Hudson Bay Lowlands of Canada is examined. Ground-based and airborne GPR data were acquired so as to extrapolate measurements to larger scales. While the ground-based measurements did an excellent job in determining peat depth, the airborne techniques did a fair job a low altitudes and demonstrated great promise with additional system engineering changes.

Pelletier, R. E.↗

Monitoring the inundation extent of the Florida Everglades with AVHRR data in a geographic information system

The purpose of the study is to develop a geographical information system capable of estimating methane and other greenhouse trace-gas fluxes from the wetlands of the Florida Everglades. Advanced very-high-resolution radiometer (AVHRR) data collected on a near-monthly basis for a year in order to monitor the seasonal dynamics of inundation extent across the Everglades is utilized in the analysis. It is noted that AVHRR data presents advantages over other remote-sensing data sources employed in covering large geographical regions due to its daily coverage with multiple opportunities during a day. This temporal resolution allows the realistic expectation of acquiring data on a frequent basis.

Pelletier, R. E.↗

A preliminary evaluation of the airborne electromagnetic bathymetry system for characterization of coastal sediments and marsh soils

Airborne electromagnetic (AEM) data acquired over a coastal region of North Carolina as part of a prototype testing program is analyzed with emphasis on multiple transects crossing a variety of geomorphic/landscape types as a means of conducting a preliminary evaluation of the sensor's ability to determine water depth and characterize a number of water and sediment physical properties such as water conductivity, sediment conductivity, sediment porosity, and sediment density. The study site is described, along with the flight line mission plan and data acquisition and processing. Good agreement between AEM-measured bathymetry and ground truth is reported, and it is concluded that in the marine environment, this system can traverse areas more rapidly than ships with acoustic systems and can collect data from shallow or inaccessible regions.

Pelletier, R. E.↗

Detection techniques using multispectral data to index soil erosional status

Indexing techniques that can be used to detect soil erosion utilizing the known band widths of the Landsat MSS and TM sensors are identified. The indexing techniques focus on iron oxides, clays, and organic matter as properties revealing soil erosional status. For data aquisition, a Collins visible and infrared intelligent spectrometer was used to collect data from 0.4-24 microns. Pressed polytetrafluorethylene was used as the reflectance standard and was aquired at the same time that the sample data were aquired.

Pelletier, R. E.↗

Preliminary investigation of Large Format Camera photography utility in soil mapping and related agricultural applications

The use of Space Shuttle Large Format Camera (LFC) color, IR/color, and B&W images in large-scale soil mapping is discussed and illustrated with sample photographs from STS 41-6 (October 1984). Consideration is given to the characteristics of the film types used; the photographic scales available; geometric and stereoscopic factors; and image interpretation and classification for soil-type mapping (detecting both sharp and gradual boundaries), soil parent material topographic and hydrologic assessment, natural-resources inventory, crop-type identification, and stress analysis. It is suggested that LFC photography can play an important role, filling the gap between aerial and satellite remote sensing.

Pelletier, R. E.↗

A gridding approach to detect patterns of change in coastal wetlands from digital data

The conversion of land to water or water to land in the Grand Bayou wetlands area from 1972 to 1981 is evaluated on the basis of Landsat MSS band 2 and 4 images. A postclassification (land vs water) procedure is employed, and grids 1, 5, 10, 25, and 50 pixels square are superimposed on the classified data in an effort to reduce the effects of poor georegistration of the images (simulated by shifting one set of grids two pixels vertically and horizontally). The results are presented in tables, maps, and sample images and characterized in detail. Grids 5 or 10 pixels square are found to give percentage land/water change values and locations similar to those obtained in pixel-by-pixel analysis of nearly perfectly matched images.

Pelletier, R. E.↗

Applications of TIMS data in agricultural areas and related atmospheric considerations

While much of traditional remote sensing in agricultural research was limited to the visible and reflective infrared, advances in thermal infrared remote sensing technology are adding a dimension to digital image analysis of agricultural areas. The Thermal Infrared Multispectral Scanner (TIMS) an airborne sensor having six bands over the nominal 8.2 to 12.2 m range, offers the ability to calculate land surface emissivities unlike most previous singular broadband sensors. Preliminary findings on the utility of the TIMS for several agricultural applications and related atmospheric considerations are discussed.

Pelletier, R. E.↗

Utility of remotely sensed data for identification of soil conservation practices

Discussed are a variety of remotely sensed data sources that may have utility in the identification of conservation practices and related linear features. Test sites were evaluated in Alabama, Kansas, Mississippi, and Oklahoma using one or more of a variety of remotely sensed data sources, including color infrared photography (CIR), LANDSAT Thematic Mapper (TM) data, and aircraft-acquired Thermal Infrared Multispectral Scanner (TIMS) data. Both visual examination and computer-implemented enhancement procedures were used to identify conservation practices and other linear features. For the Kansas, Mississippi, and Oklahoma test sites, photo interpretations of CIR identified up to 24 of the 109 conservation practices from a matrix derived from the SCS National Handbook of Conservation Practices. The conservation practice matrix was modified to predict the possibility of identifying the 109 practices at various photographic scales based on the observed results as well as photo interpreter experience. Some practices were successfully identified in TM data through visual identification, but a number of existing practices were of such size and shape that the resolution of the TM could not detect them accurately. A series of computer-automated decorrelation and filtering procedures served to enhance the conservation practices in TM data with only fair success. However, features such as field boundaries, roads, water bodies, and the Urban/Ag interface were easily differentiated. Similar enhancement techniques applied to 5 and 10 meter TIMS data proved much more useful in delineating terraces, grass waterways, and drainage ditches as well as the features mentioned above, due partly to improved resolution and partly to thermally influenced moisture conditions. Spatially oriented data such as those derived from remotely sensed data offer some promise in the inventory and monitoring of conservation practices as well as in supplying parameter data for a variety of computer-implemented agricultural models.

Pelletier, R. E.↗

Remote sensing techniques for the detection of soil erosion and the identification of soil conservation practices

The following paper is a summary of a number of techniques initiated under the AgRISTARS (Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing) project for the detection of soil degradation caused by water erosion and the identification of soil conservation practices for resource inventories. Discussed are methods to utilize a geographic information system to determine potential soil erosion through a USLE (Universal Soil Loss Equation) model; application of the Kauth-Thomas Transform to detect present erosional status; and the identification of conservation practices through visual interpretation and a variety of enhancement procedures applied to digital remotely sensed data.

Pelletier, R. E.↗

Agricultural applications for thermal infrared multispectral scanner data

The use of the Thermal Infrared Multispectral Scanner (TIMS) data in agricultural landscapes is discussed. The TIMS allows for narrow-band analysis in the 8.2-11.6 micron range at spatial resolutions down to 5 meters in cell size. A coastal plain region in SE Alabama was studied using the TIMS. The crop/plant vigor, canopy density, and thermal response changes for soils obtained from thermal imagery are examined. The application of TIMS data to hydrologic and topographic issues, inventory and conservation monitoring, and the enhancement and extraction of cartographic features is described.

Pelletier, R. E.↗

Spatial variation analyses of Thematic Mapper data for the identification of linear features in agricultural landscapes

A need exists for digitized information pertaining to linear features such as roads, streams, water bodies and agricultural field boundaries as component parts of a data base. For many areas where this data may not yet exist or is in need of updating, these features may be extracted from remotely sensed digital data. This paper examines two approaches for identifying linear features, one utilizing raw data and the other classified data. Each approach uses a series of data enhancement procedures including derivation of standard deviation values, principal component analysis and filtering procedures using a high-pass window matrix. Just as certain bands better classify different land covers, so too do these bands exhibit high spectral contrast by which boundaries between land covers can be delineated. A few applications for this kind of data are briefly discussed, including its potential in a Universal Soil Loss Equation Model.

Pelletier, R. E.↗