Feature Selection for Urban Land-Cover Classification using Landsat-7 ETM+ Data
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Feature Selection for Urban Land-Cover Classification using Landsat-7 ETM+ Data |
| 2. | Creator | Author's name, affiliation, country | Prakash C. R.; Centre for Spatial Information Technology, Institute of Science and Technology, Jawaharlal Nehru Technological University, Kukatpally, Hyderabad, Telangana, India |
| 2. | Creator | Author's name, affiliation, country | Sridevi B.; Directorate of Rice Research, Rajendranagar Mandal, Hyderabad, Telangana, India |
| 2. | Creator | Author's name, affiliation, country | Asra M.; Centre for Spatial Information Technology, Institute of Science and Technology, Jawaharlal Nehru Technological University, Kukatpally, Hyderabad, Telangana, India |
| 2. | Creator | Author's name, affiliation, country | Dwivedi R.S.; Centre for Spatial Information Technology, Institute of Science and Technology, Jawaharlal Nehru Technological University, Kukatpally, Hyderabad, Telangana, India |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | Enhanced Thematic Mapper Plus (ETM+); Optimum Index Factor (OIF); Principal Component Transform; Classification Accuracy |
| 4. | Description | Abstract |
We report here the results of a study carried out to reduce the dimensionality of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) digital data by principal component analysis, and generating a band triplet with maximum optimum index factor (OIF) value for developing land-cover map over a metropolitan city through Gaussian maximum likelihood algorithm. The performance of the thematic maps, thus generated from these three data sets, was done by a systematic accuracy assessment. Results indicate that a band triplet (ETM+ band 2, 4 and 5) with the maximum optimum index factor (OIF) value, and an overall accuracy of 97.5% and a kappa accuracy value of 0.9656 outperformed other two datasets viz. original 6-reflective bands of ETM+ data and a PC triplet (PC1, PC2 and PC3). The overall and a kappa accuracies values for original 6-reflective bands of ETM+ data have estimated as 96.7% and 0.9541, respectively. For a PC triplet (PC1, PC2 and PC3) these values are 94.17% and 0.9210, respectively indicating thereby the potential of transformed data in generating improved land cover information of an urban environment. The methodology and the results are discussed in detail. |
| 5. | Publisher | Organizing agency, location | |
| 6. | Contributor | Sponsor(s) | |
| 7. | Date | (YYYY-MM-DD) | 2015-09-10 |
| 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-449 |
| 11. | Source | Journal/conference title; vol., no. (year) | International Journal of Advanced Remote Sensing and GIS; Volume 4 (Year 2015) |
| 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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