The Large Area Crop Inventory Experiment (LACIE). An application of remote sensing by multispectral scanners

There are no author-identified significant results in this report

Quarterly literature review of the remote sensing of natural resources

The Technology Application Center reviewed abstracted literature sources, and selected document data and data gathering techniques which were performed or obtained remotely from space, aircraft or groundbased stations. All of the documentation was related to remote sensing sensors or the remote sensing of the natural resources. Sensors were primarily those operating within the 10 to the minus 8 power to 1 meter wavelength band. Included are NASA Tech Briefs, ARAC Industrial Applications Reports, U.S. Navy Technical Reports, U.S. Patent reports, and other technical articles and reports

Canonical Analysis : The Use of Transformed Landsat Data for Crop Type Discrimination

The primary goal of this thesis is to investigate the usefulness, accuracy, and efficiency of canonical analysis (a linear transformation technique) for the classification of crop types using multi-date multispectral scanner (MSS) Landsat digital data. The accuracy statistics and the computer processing efficiency of the crop type classification developed using a canonical transformation will be compared with accuracy and efficiency figures of a crop classification developed for the Columbia River and Tributaries Irrigation Withdrawals Analysis Project (Johnson, Loveland, Anderson, 1981) in which multi-date Landsat data covering the same area was classified. The Clarke, Oregon 7.5 minute USGS quadrangle was chosen as the study site because of the availability of timely Landsat data and the existing maximum likelihood classification from the Columbia River and Tributaries Project. In a general sense, the problem investigated is a method of gathering crop type information using remotely sensed data. As discussed in the Introduction, an important method for crop type identification is the classification of multi-temporal Landsat digital data. Using remotely sensed data in the form of Landsat computer compatible tapes (CCT\u27s) allows for the analysis of the full spatial resolution of Landsat data and the analysis and manipulation of the numeric sensitivity of digital data

Land use/land cover mapping (1:25000) of Taiwan, Republic of China by automated multispectral interpretation of LANDSAT imagery

Three methods were tested for collection of the training sets needed to establish the spectral signatures of the land uses/land covers sought due to the difficulties of retrospective collection of representative ground control data. Computer preprocessing techniques applied to the digital images to improve the final classification results were geometric corrections, spectral band or image ratioing and statistical cleaning of the representative training sets. A minimal level of statistical verification was made based upon the comparisons between the airphoto estimates and the classification results. The verifications provided a further support to the selection of MSS band 5 and 7. It also indicated that the maximum likelihood ratioing technique can achieve more agreeable classification results with the airphoto estimates than the stepwise discriminant analysis

Computer processing of peach tree decline data

There are no author-identified significant results in this report

Agricultural scene understanding, volume 1

There are no author-identified significant results in this report

Matrix of educational and training materials in remote sensing

Remote sensing educational and training materials developed by LARS have been organized in a matrix format. Each row in the matrix represents a subject area in remote sensing and the columns represent different types of instructional materials. This format has proved to be useful for displaying in a concise manner the subject matter content, prerequisite requirements and technical depth of each instructional module in the matrix. A general description of the matrix is followed by three examples designed to illustrate how the matrix can be used to synthesize training programs tailored to meet the needs of individual students. A detailed description of each of the modules in the matrix is contained in a catalog section

Skylab/EREP application to ecological, geological, and oceanographic investigations of Delaware Bay

Skylab/EREP S190A and S190B film products were optically enhanced and visually interpreted to extract data suitable for; (1) mapping coastal land use; (2) inventorying wetlands vegetation; (3) monitoring tidal conditions; (4) observing suspended sediment patterns; (5) charting surface currents; (6) locating coastal fronts and water mass boundaries; (7) monitoring industrial and municipal waste dumps in the ocean; (8) determining the size and flow direction of river, bay and man-made discharge plumes; and (9) observing ship traffic. Film products were visually analyzed to identify and map ten land-use and vegetation categories at a scale of 1:125,000. Digital tapes from the multispectral scanner were used to prepare thematic maps of land use. Classification accuracies obtained by comparison of derived thematic maps of land-use with USGS-CARETS land-use maps in southern Delaware ranged from 44 percent to 100 percent

Earth Resources Laboratory research and technology

The accomplishments of the Earth Resources Laboratory's research and technology program are reported. Sensors and data systems, the AGRISTARS project, applied research and data analysis, joint research projects, test and evaluation studies, and space station support activities are addressed