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Publications

Below is a list of the most recent EROS peer-reviewed scientific papers, reports, fact sheets, and other publications. You can search all our publication holdings by type, topic, year, and order.

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Filter Total Items: 2614

The availability of conventional forms of remotely sensed data The availability of conventional forms of remotely sensed data

For decades Federal and State agencies have been collecting aerial photographs of various film types and scales over parts of the United States. More recently, worldwide Earth resources data acquired by orbiting satellites have inundated the remote sensing community. Determining the types of remotely sensed data that are publicly available can be confusing to the land-resource manager...
Authors
James Sturdevant, Thomas Holm

Applications of Landsat imagery to problems of petroleum exploration in Qaidam Basin, China Applications of Landsat imagery to problems of petroleum exploration in Qaidam Basin, China

Tertiary and Quaternary nonmarine, petroleum-bearing sedimentary rocks in the Qaidam basin of remote western China have been extensively deformed by compressive forces. These forces created many folds which are current targets of Chinese exploration programs. Manual techniques of image analysis and interpretation were applied to computer-enhanced Landsat images of the western part of the...
Authors
G. B. Bailey, P. Anderson

Computation with physical values from Landsat digital data Computation with physical values from Landsat digital data

Landsat digital images are commonly analyzed by using the digital numbers for each pixel recorded on a computer-compatible magnetic tape. Although this procedure may be satisfactory when only a single, internally consistent image is used, the procedure may produce incorrect results if more than one image is used for analysis as in mosaics or temporal overlays. The digital numbers for...
Authors
C.J. Robinove

Digital classification of Landsat data for vegetation and land-cover mapping in the Blackfoot River watershed, southeastern Idaho Digital classification of Landsat data for vegetation and land-cover mapping in the Blackfoot River watershed, southeastern Idaho

This paper documents the procedures, results, and final products of a digital analysis of Landsat data used to produce a vegetation and landcover map of the Blackfoot River watershed in southeastern Idaho. Resource classes were identified at two levels of detail: generalized Level I classes (for example, forest land and wetland) and detailed Levels II and III classes (for example...
Authors
L. Pettinger

Digital data base application to porphyry copper mineralization in Alaska; case study summary Digital data base application to porphyry copper mineralization in Alaska; case study summary

The purpose of this report is to summarize the progress in use of digital image analysis techniques in developing a conceptual model for assessing porphyry copper mineral potential. The study area consists of approximately the southern one-half of the 1? by 3? Nabesna quadrangle in east-central Alaska. The digital geologic data base consists of data compiled under the Alaskan Mineral...
Authors
Charles Trautwein, David Greenlee, Donald Orr

A hybrid structure for the storage and manipulation of very large spatial data sets A hybrid structure for the storage and manipulation of very large spatial data sets

The map data input and output problem for geographic information systems is rapidly diminishing with the increasing availability of mass digitizing, direct spatial data capture and graphics hardware based on raster technology. Although a large number of efficient raster-based algorithms exist for performing a wide variety of common tasks on these data, there are a number of procedures...
Authors
Donna Peuquet

An automatic optimum kernel-size selection technique for edge enhancement An automatic optimum kernel-size selection technique for edge enhancement

Edge enhancement is a technique that can be considered, to a first order, a correction for the modulation transfer function of an imaging system. Digital imaging systems sample a continuous function at discrete intervals so that high-frequency information cannot be recorded at the same precision as lower frequency data. Because of this, fine detail or edge information in digital images...
Authors
Pat Chavez, Brian Bauer

Assessing mesquite-grass vegetation condition from Landsat Assessing mesquite-grass vegetation condition from Landsat

Landsat multispectral scanner (MSS) band values, band ratios, and vegetation index models were compared with selected rangeland vegetation parameters collected at six test sites within the honey mesquitellotebushlmixed grass association in north-central Texas. The comparisons at four dates showed that two vegetation index models, TV16 and GVI, are highly correlated (P = 0.01) with green...
Authors
Kirk McDaniel, Robert Haas

Evaluating the crop coefficient using spectral reflectance Evaluating the crop coefficient using spectral reflectance

A field study was conducted in four differentially irrigated plots of alfalfa (Medicago sativa L.) planted in Shiprock sandy loam (coarseloamy, mixed, mesic Typic Haplargid) to assess spectral reflectance for estimating the crop coefficient (Kc), defined here as the ratio of actual to potential evapotranspiration (ET). A bidirectional reflectance factor was measured using a three-channel...
Authors
J. Heilman, W. Heilman, Donald Moore

An assessment of Landsat data acquisition history on identification and area estimation of corn and soybeans An assessment of Landsat data acquisition history on identification and area estimation of corn and soybeans

In the past decade, numerous studies have demonstrated the potential of satellite remote sensing for providing accurate timely crop area information. This study assessed the impact of Landsat data acquisition history on classification and area estimation accuracy of corn and soybeans in the U.S. Corn Belt. The results illustrate the importance of selecting Landsat acquisitions based on...
Authors
M. Hixson, M. Bauer, Donna Scholz

Evaluation of AMOEBA: a spectral-spatial classification method Evaluation of AMOEBA: a spectral-spatial classification method

Muitispectral remotely sensed images have been treated as arbitrary multivariate spectral data for purposes of clustering and classifying. However, the spatial properties of image data can also be exploited. AMOEBA is a clustering and classification method that is based on a spatially derived model for image data. In an evaluation test, Landsat data were classified with both AMOEBA and a...
Authors
Susan Jenson, Thomas R. Loveland, J. Bryant

Landsat monitoring of albedo changes in northwestern Arizona, 1977-1980 Landsat monitoring of albedo changes in northwestern Arizona, 1977-1980

As part of a cooperative project between the U.S. Geological Survey and the Bureau of Land Management, changes in albedo (percentage of light reflected from the ground) were calculated and mapped from Landsat images for an area in northwestern Arizona for three periods: August 26, 1977, to September 3, 1979; September 3, 1979, to August 28, 1980; and August 26, 1977, to August 28, 1980...
Authors
Charles Robinove
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