Urban Built-up Area Extraction and Change Detection of Adama Municipal Area using Time-Series Landsat Images
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Urban Built-up Area Extraction and Change Detection of Adama Municipal Area using Time-Series Landsat Images |
| 2. | Creator | Author's name, affiliation, country | Priyakant Sinha; School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia |
| 2. | Creator | Author's name, affiliation, country | Niva Kiran Verma; School of Science and Technology, University of New England, Armidale, NSW 2351, Australia |
| 2. | Creator | Author's name, affiliation, country | Eskindir Ayele; Department of Surveying, Dire Dawa Institute, Dire Dawa University, P.O. BOX 1362, Ethiopia |
| 2. | Creator | Author's name, affiliation, country | (doi: 10.23953/cloud.ijarsg.67) |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | Remote Sensing; Built-up Area; Spectral Indices; Urban Study; Landsat |
| 4. | Description | Abstract |
Urban built-up area information is required in various applications of land use planning and management. However, urban built-up area extraction from moderate spatial resolution Landsat time-series data is challenging because of significant intra-urban heterogeneity and spectral confusion between other landcover types. This paper proposes a technique to extract urban built-up area from time-series Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imageries and determines urban area changes between 1984 to 2015 of Adama Municipal Area of Ethiopia. The study selected three indices, the Enhanced Built-Up and Bareness Index (EBBI), Soil Adjusted Vegetation Index (SAVI) and Modified Normalized Difference Water Index (MNDWI), to represent three major urban land-use classes: built-up and barren/bare land, open waterbody, and vegetation, respectively. The built-up area was extracted by taking the difference between EBBI, SAVI and MNDWI to remove the vegetation and water noises, and the resulted index image was spectrally segmented to separate built-up area from the non-urban built-up lands. The derived index was used to map built-up area for 1984, 1995, 2005 and 2015 periods. The expansion of the built-up area has been revealed as a major change in the area when city area expanded substantially by 293% between 1984 to 2015 periods. The advantage of the method was to use almost the entire spectral range of Landsat imageries which cause less spectral confusion between land cover classes and hence resulted in higher accuracies compared to other indices. The method was effective and simple to implement, and can be used for built-up extraction in other areas. |
| 5. | Publisher | Organizing agency, location | |
| 6. | Contributor | Sponsor(s) | a person |
| 7. | Date | (YYYY-MM-DD) | 2016-08-16 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | http://technical.cloud-journals.com/index.php/IJARSG/article/view/Tech-649 |
| 11. | Source | Journal/conference title; vol., no. (year) | International Journal of Advanced Remote Sensing and GIS; Volume 5 (Year 2016) |
| 12. | Language | English=en | en |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
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