Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Land Surveying and Geo-Informatics | en_US |
| dc.creator | Chen, Bin | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/4564 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Effect of image resolution on extraction of road features | en_US |
| dcterms.abstract | Road extraction from satellite images is an important means for updating of road map database. In the extraction of road features, two important issues need to be considered, i.e. efficiency and correctness. They are affected by many factors such as hardware, software and data source. Image resolution is one of the factors within the domain of data source. That is, a road may have quite different appearance on images with different resolutions. Therefore, it is quite understandable that different results will be obtained from images with different resolution. This project aims to investigate the effect of image resolutions on the extraction of road features. More precisely, images with different resolutions will be used to obtain information of roads in different natures. Then a set of measures (or indicators) are developed to measure the correctness of the road information. Images with four resolutions, 0.6m, 2.4m, 5m, and 10m, from two platforms (i.e. QuickBird and SPOT5) are used as source data. Both "edge detection" and "unsupervised classification" are employed to extract road boundary and road surface from these images. From the analysis of the results, it can be found that (a) a single road (central line) can be extracted if the image resolution is half of the road width, and (b) if the resolution is much higher than that value, road boundaries and other features may then be extracted. Therefore, it is not an advantage to simply purchase the high resolution satellite images. Indeed, it is advisable to select images with appropriate resolution for a particular project (i.e. road with different types). | en_US |
| dcterms.extent | x, 74 leaves : ill. ; 30 cm. | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2009 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations. | en_US |
| dcterms.LCSH | Cartography -- Remote sensing. | en_US |
| dcterms.LCSH | Roads -- Location -- Remote sensing. | en_US |
| dcterms.LCSH | Imaging systems -- Image quality. | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b23154214.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 5.38 MB | Adobe PDF | View/Open |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/4564