A Comparison of Classification Techniques Using Landsat Thematic Mapper and Multispectral Scanner Data, for Landcover Classification of a Portion of Calloway and Graves Counties, Kentucky PDF Download
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Author: Lane T. Schmidt
Publisher:
ISBN:
Category : Landscapes
Languages : en
Pages : 116
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Book Description
Author: Lane T. Schmidt
Publisher:
ISBN:
Category : Landscapes
Languages : en
Pages : 116
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Book Description
Author: Wade H. Shafer
Publisher: Springer Science & Business Media
ISBN: 1468451979
Category : Science
Languages : en
Pages : 407
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Book Description
Masters Theses in the Pure and Applied Sciences was first conceived, published, and disseminated by the Center for Information and Numerical Data Analysis and Synthesis (CINDAS) * at Purdue University in 1 957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dissemination phases of the activity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the thought that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we had concluded that it was in the interest of all con cerned if the printing and distribution of the volumes were handled by an interna tional publishing house to assure improved service and broader dissemination. Hence, starting with Volume 18, Masters Theses in the Pure and Applied Sciences has been disseminated on a worldwide basis by Plenum Publishing Cor poration of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 29 (thesis year 1984) a total of 12,637 theses titles from 23 Canadian and 202 United States universities. We are sure that this broader base for these titles reported will greatly enhance the value of this important annual reference work. While Volume 29 reports theses submitted in 1984, on occasion, certain univer sities do report theses submitted in previous years but not reported at the time.
Author: American Congress on Surveying and Mapping
Publisher:
ISBN:
Category : Cartography
Languages : en
Pages : 1048
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Book Description
Author: Tim Hawes
Publisher:
ISBN:
Category : Artificial satellites in remote sensing
Languages : en
Pages : 202
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Book Description
"A radiometric normalization technique for compensating illumination and atmospheric differences between multi-temporal images should allow classification of the images with a single classification algorithm. This allows a simpler approach to land cover change detection. Land cover classification of Landsat Thematic Mapper Imagery with and without Pseudo Invariant Feature Normalization was performed to demonstrate the effect on classification and change detection accuracy. A post-classification change detection method using two separate classification algorithms, one for each date, was performed as a baseline comparison. Land cover classification using one classification algorithm was attempted with and without gain and offset correction to serve as another comparison. Accuracy verification was performed on the classification results by comparing random samples against ground truth."--Abstract.
Author:
Publisher:
ISBN:
Category : Geology
Languages : en
Pages : 1354
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Author:
Publisher:
ISBN:
Category : Landsat satellites
Languages : en
Pages : 16
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Book Description
Author: Christopher M. Swalm
Publisher:
ISBN:
Category : Digital mapping
Languages : en
Pages : 262
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Book Description
Author: Ramiro Salcedo
Publisher:
ISBN:
Category : Aerial photography in regional planning
Languages : en
Pages : 188
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Book Description
Author: Paul Michael Harris
Publisher:
ISBN:
Category :
Languages : en
Pages : 290
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Book Description
Author: Heng Huang
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages :
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Book Description
To further increase the classification accuracies, radar image processing techniques were investigated to preprocess the Radarsat data before classification. Eight processing techniques were applied to Radarsat data at various windows from 3 x 3 to 25 x 25 pixels. For a single radar feature, the Entropy processing at window size 13 x 13 provides the best overall land cover classification accuracy improvement when fused with the Landsat imagery. For multiple radar features, a higher accuracy improvement was found when combining the features (i.e., 13 x 13 Entropy, 9 x 9 data range, 19 x 19 mean) with the Landsat data. This study introduces an approach of fusing Landsat data with multiple Radarsat features to the land cover classification practice. Post-classification techniques were studied for land cover classification maps. Several weighted kernels were developed for the majority filtering process. The method evaluates the correlation between neighbor pixels according to the distance and further improves the classification accuracy. For the St. Louis study area, the Gaussian weighted kernel increases the overall land classification accuracy compared to the Landsat images. Post-classification smoothing of the sensor fusion result (Landsat and radar feature combination) further increases the accuracy. A decadal change analysis was also conducted for the St. Louis, Missouri area using Landsat imagery and census population data. This study proposes a methodology to integrate remotely sensed and census data in urban change analysis. The assessment can provide information that can highlight priority urban growth regions. The analysis shows strong correlation between population and land cover changes, which indicates the potential of satellite imagery to generate the physical feature input for tele-traffic forecasting of a cellular network.
