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  • 1
    Publication Date: 2011-08-18
    Description: The approach used to obtain reliable countywide forest resource data, including statistics and a forest cover distribution map from LANDSAT data is described. Comparison of results of the LANDSAT anlysis and U.S. Forestry Survey data is presented in a table. Pine, oak/pine, and oak/hickory accounted for 22.3%, 32.6% and 45.2% respectively of the total forest area in the LANDSAT analysis, compared to 22.8%, 30.1%. and 47.1% in the Forest Survey. The corresponding figures for each forest type differ at most 2.5% for the mixed forest. The total county area in forest land measured using LANDSAT was underestimated by 1,409 acres, a 2.2% error based on the Forest Survey statistics. However, the estimate of 61,242 acres fell well within the known 4% uncertainty of the estimate for the Forest Survey figures (62,651 acres + or - 2,544 acres).
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Eastern Reg. Remote Sensing Appl. Conf.; p 91-97
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  • 2
    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
    Publication Date: 2011-08-18
    Description: The results of a study to evaluate Landsat digital data, categorized by land cover, for input to the Maryland Automated Geographic Information (MAGI) system, the state georeferenced data base, are presented. Good correspondence is found between the MAGI system and Landsat data for six of seven categories: forest, water, crop/pasture, medium-density residential, low-density residential, and transitional (disturbed land, construction). Discrepancies between the results are found for commercial/industrial/institutional areas which are due to differences in interpretative methodologies, not to deficiencies in either data source. It is concluded that Landsat data are suitable for future Maryland land cover inventories, and can also be used to augment MAGI system data.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
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  • 4
    Publication Date: 2011-08-18
    Description: 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.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
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  • 5
    Publication Date: 2016-06-07
    Description: An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Marshall Univ. Proc. of the Natl. Conf. on Energy Resource Management, Vol. 1; p 3-18
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  • 6
    Publication Date: 2019-06-28
    Description: The utility of LANDSAT digital data for mapping and monitoring surface mines in Belmont County, Ohio was investigated. Two data sets from 1976 and 1979 were processed to classify level 1 land covers and three strip mine categories in order to examine change over time and assess reclamation efforts. The two classifications were compared with aerial photographs. Results of the accuracy assessment show that both classifications are approximately 86 per cent correct, and that surface mine change detection (date-to-date comparison) is facilitated by the digital format of LANDSAT data.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E83-10209 , NASA-TM-85001 , NAS 1.15:85001
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  • 7
    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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  • 8
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    In:  Other Sources
    Publication Date: 2019-07-13
    Description: The eruption of Mount St. Helens on May 18, 1980, and subsequent destruction of approximately 593 square kilometers (229 square miles) of vegetation, clearly provided a unique opportunity for earth-oriented satellite remote sensing systems. Landsat, a relatively high resolution Multispectral Scanner (MSS) system, imaged Mount St. Helens both before and after its major eruption. Digital data have been used to create a damage assessment map and a change detection image. Several classes of timber damage and land cover modification have been developed. Acreages for each class have been tabulated.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Electro-optical instrumentation for resources evaluation; Apr 21, 1981 - Apr 22, 1981; Washington, DC
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