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  • 1
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    Comparative techniques used to evaluate Thematic Mapper data for land cover classification in Logan County, West Virginia (1985)
    In:  CASI
    Details
    Publication Date: 2006-02-14
    Description: Several digital data processing techniques were evaluated in an effort to identify and map active/abandoned, partially reclaimed, and fully revegetated surface mine areas in the central portion of Logan County. The TM data were first subjected to various enhancement procedures, including a linear contrast stretch, principal components and canonical analysis transformations. At the same time, four general procedures were followed to produce six classifications as a means of comparing the techniques involved. Preliminary results show that various feature extraction/data reduction techniques provide classification results equal or superior to the more straightforward unsupervised clustering technique. Analyst interaction time for labelling clusters is reduced using the canonical analysis and principal components procedures, though the canonical technique has clearly produced better results to date.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: LANDSAT-4 Sci. Characterization Early Results, Vol. 4; p 403-414
    Format: text
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  • 2
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    Application of LANDSAT data to monitor land reclamation progress in Belmont County, Ohio (1981)
    In:  Other Sources
    Details
    Publication Date: 2011-08-18
    Description: Strip and contour mining techniques are reviewed as well as some studies conducted to determine the applicability of LANDSAT and associated digital image processing techniques to the surficial problems associated with mining operations. A nontraditional unsupervised classification approach to multispectral data is considered which renders increased classification separability in land cover analysis of surface mined areas. The approach also reduces the dimensionality of the data and requires only minimal analytical skills in digital data processing.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: 2nd Eastern Reg. Remote Sensing Appl. Conf.; p 167-190
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  • 3
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    A Temporal Approach to Monitor Surface Mine Reclamation Progress via LANDSAT (1982)
    In:  CASI
    Details
    Publication Date: 2014-09-09
    Description: Using LANDSAT satellite imagery, the mine reclamation process can be studied on a temporal and continuing basis. Not only can the progress of reclamation be readily monitored, but also a breakdown in the mining reclamation process can be detected. In viewing reclamation, it is important to monitor the mined site well past initial revegation stages. With present mining law and bonding procedures, fast revegetational growth is encouraged, often leading to poor soil fertilizing and inappropriate stabilizing species. As a result, the initial reclamation may exhibit good qualities for one or two years but then may experience vegetational deterioration after the state has relinquished the mining company from it's responsibility. It is this small-scale breakdown in the reclamation process that was detected using an unsupervised classification technique with eight-year temporal LANDSAT imagery coverage.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Marshall Univ. Proc. of the Natl. Conf. on Energy Resource Management, Vol. 2; p 457-462
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  • 4
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    Potential Applications of LANDSAT Data in Energy Management Associated with Kenya's Forests (1982)
    In:  CASI
    Details
    Publication Date: 2014-09-09
    Description: LANDSAT can be effectively used to monitor the extent and magnitude of forest cover change in Kenya in order to evaluate the potential for energy supply. Digital processing of LANDSAT data provides a reliable monitoring technique for forest resource management in Kenya. Data analysis was used to illustrate that Kenya's forests are indeed diminishing. A model used to make projections for the availability of fuelwood as an energy source is presented. The resulting figures imply that Kenya's forest will all but disappear around the end of the 20th century. Analysis of LANDSAT data for Mau East substantiates these alarming findings.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Marshall Univ. Proc. of the Natl. Conf. on Energy Resource Management, Vol. 2; p 508-517
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  • 5
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    Optimization of a Non-traditional Unsupervised Classification Approach for Land Cover Analysis (1982)
    In:  CASI
    Details
    Publication Date: 2016-06-07
    Description: The conditions under which a hybrid of clustering and canonical analysis for image classification produce optimum results were analyzed. The approach involves generation of classes by clustering for input to canonical analysis. The importance of the number of clusters input and the effect of other parameters of the clustering algorithm (ISOCLS) were examined. The approach derives its final result by clustering the canonically transformed data. Therefore the importance of number of clusters requested in this final stage was also examined. The effect of these variables were studied in terms of the average separability (as measured by transformed divergence) of the final clusters, the transformation matrices resulting from different numbers of input classes, and the accuracy of the final classifications. The research was performed with LANDSAT MSS data over the Hazleton/Berwick Pennsylvania area. Final classifications were compared pixel by pixel with an existing geographic information system to provide an indication of their accuracy.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Marshall Univ. Proc. of the Natl. Conf. on Energy Resource Management, Vol. 1; p 32-44
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  • 6
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    Proceedings of the National Conference on Energy Resource Management. Volume 1: Techniques, Procedures and Data Bases (1982)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: Topics dealing with the integration of remotely sensed data with geographic information system for application in energy resources management are discussed. Associated remote sensing and image analysis techniques are also addressed.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E83-10335 , NASA-CP-2261-VOL-1 , NAS 1.55:2261-VOL-1 , Sep 09, 1982 - Sep 12, 1982; Baltimore
    Format: application/pdf
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  • 7
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    Proceedings of the National Conference on Energy Resource Management. Volume 2: Applications (1982)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: Subject areas related to the integration of remotely sensed data with geographic information systems for application in energy resource management are covered. The current trends and advances in the application of these systems to a number of energy concerns are addressed.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E83-10336 , NASA-CP-2261-VOL-2 , NAS 1.55:2261-VOL-2 , Sep 09, 1982 - Sep 12, 1982; Baltimore
    Format: application/pdf
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  • 8
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    Comparing digital data processing techniques for surface mine and reclamation monitoring (1982)
    In:  Other Sources
    Details
    Publication Date: 2019-07-13
    Description: The results of three techniques used for processing Landsat digital data are compared for their utility in delineating areas of surface mining and subsequent reclamation. An unsupervised clustering algorithm (ISOCLS), a maximum-likelihood classifier (CLASFY), and a hybrid approach utilizing canonical analysis (ISOCLS/KLTRANS/ISOCLS) were compared by means of a detailed accuracy assessment with aerial photography at NASA's Goddard Space Flight Center. Results show that the hybrid approach was superior to the traditional techniques in distinguishing strip mined and reclaimed areas.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: American Congress on Surveying and Mapping and American Society of Photogrammetry Convention; APS Annual Meeting; Mar 14, 1982 - Mar 20, 1982; Denver, CO
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  • 9
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    A comparison of the usefulness of canonical analysis, principal components analysis, and band selection for extraction of features from TMS data for landcover analysis (1984)
    In:  Other Sources
    Details
    Publication Date: 2019-07-13
    Description: Three feature extraction methods, canonical analysis (CA), principal component analysis (PCA), and band selection, have been applied to Thematic Mapper Simulator (TMS) data in order to evaluate the relative performance of the methods. The results obtained show that CA is capable of providing a transformation of TMS data which leads to better classification results than provided by all seven bands, by PCA, or by band selection. A second conclusion drawn from the study is that TMS bands 2, 3, 4, and 7 (thermal) are most important for landcover classification.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: International Symposium on Remote Sensing of Environment; May 09, 1983 - May 13, 1983; Ann Arbor, MI
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  • 10
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    An unsupervised classification approach for analysis of Landsat data to monitor land reclamation in Belmont county, Ohio (1981)
    In:  Other Sources
    Details
    Publication Date: 2019-07-13
    Description: Two unsupervised classification procedures for analyzing Landsat data used to monitor land reclamation in a surface mining area in east central Ohio are compared for agreement with data collected from the corresponding locations on the ground. One procedure is based on a traditional unsupervised-clustering/maximum-likelihood algorithm sequence that assumes spectral groupings in the Landsat data in n-dimensional space; the other is based on a nontraditional unsupervised-clustering/canonical-transformation/clustering algorithm sequence that not only assumes spectral groupings in n-dimensional space but also includes an additional feature-extraction technique. It is found that the nontraditional procedure provides an appreciable improvement in spectral groupings and apparently increases the level of accuracy in the classification of land cover categories.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Machine processing of remotely sensed data with special emphasis on range, forest, and wetlands assessment; Jun 23, 1981 - Jun 26, 1981; West Lafayette, IN
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