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DC Field | Value | Language |
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dc.contributor.author | Ajayi, Oluibukun Gbenga | - |
dc.contributor.author | Opaluwa, Y. D | - |
dc.contributor.author | Adejare, Q. A | - |
dc.contributor.author | Odumosu, J. O | - |
dc.contributor.author | Zitta, N | - |
dc.contributor.author | Adesina, E. A | - |
dc.date.accessioned | 2021-06-09T21:08:56Z | - |
dc.date.available | 2021-06-09T21:08:56Z | - |
dc.date.issued | 2016 | - |
dc.identifier.uri | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/2468 | - |
dc.description | Oluibukun G. Ajayi, Yusuf D. Opaluwa, Quadri A. Adejare, Joseph. O. Odumosu, Nanpon Zitta and Ekundayo A. Adesina. (2016). An Evaluation of Geometric Data Acquisition Using Landsat Imagery. Commonwealth Association of Land Surveying and Management (CASLE2016) International Conference. “Sustainability of the Surveying Professions & National Development in the 21st Century”, 21-23 April, 2016, Abuja-Nigeria. Pages 173-185 in the Book of Proceedings Published by Commonwealth Association of Land Surveying and Management, Faculty of Environment & Technology, University of the West of England, UK. Available online at http://www.casle.org/conferences.htm#future | en_US |
dc.description.abstract | The implementation of appropriate digital image processing method is crucial for deriving urban land cover maps of acceptable accuracy and cost. This study examines the effect of acquiring images in various spectral regions (bands), the impact of some image processing techniques on the combination of the different bands and the acceptable mode in which the features of the image could be classified using unsupervised classification (clustering) and supervised classification based on four different hard classifiers. Four different filter types were experimented on the colour composite images before classifying the images into different distinct land spectral classes. The Integrated Land and Water Information System (ILWIS) software was used to classify LandSAT 7 image of 2001, part 189r053, zone 32, bands 1 (Blue), 2 (Green), 3 (Red), 4 (Near infrared), 5 and 7 (Middle infrared) wavelength. From the study, it was observed that AVG 3x3 filter type is the most preferred. Colour composite of bands 5, 4, 3 in the RGB planes gave the best representation of the features of the image and that Box classifier, Minimum Distance to Mean Classifier and Maximum Likelihood classifier are excellent classifiers for image supervised classification. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Commonwealth Association of Surveying and Land Economy, and Faculty of Environment & Technology, University of the West of England, UK | en_US |
dc.subject | Geometric data acquisition | en_US |
dc.subject | Digital Image Processing | en_US |
dc.subject | Landsat imagery | en_US |
dc.subject | Colour composite | en_US |
dc.title | An Evaluation of Geometric Data Acquisition Using Landsat Imagery. | en_US |
dc.type | Article | en_US |
Appears in Collections: | Surveying & Geoinformatics |
Files in This Item:
File | Description | Size | Format | |
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Ajayi et al-CASLE 2016 .pdf | Ajayi et al., 2016 | 750.04 kB | Adobe PDF | View/Open |
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