Advances in Classification Techniques for Semi Urban Land Features using High Resolution Satellite Data
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Advances in Classification Techniques for Semi Urban Land Features using High Resolution Satellite Data |
| 2. | Creator | Author's name, affiliation, country | Srikrishna Shastri C.; Department of Electronics and Communication, Mangalore Institute of Technology, Moodabidri, Karnataka, India |
| 2. | Creator | Author's name, affiliation, country | Ashok Kumar T.; Department of Electronics and Communication, PES Institute of Technology, Shivamogga, Karnataka, India |
| 2. | Creator | Author's name, affiliation, country | Shiva Prakash Koliwad; Department of Electronics and Communication, Vivekananda College of Engineering, Puttur, Karnataka, India |
| 2. | Creator | Author's name, affiliation, country | (doi: 10.23953/cloud.ijarsg.49) |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | Remote Sensing; Image Fusion; High Resolution; Image Classification; Panchromatic; Multispectral |
| 4. | Description | Abstract |
Classification of satellite Images is one of the major research areas in remote sensing fields. Classification of remote sensed data is required for accurate classification of semi urban land features. Satellite image classification plays an essential role in proper monitoring and management of natural and manmade resources on the earth surface. However a good data set is required for the accurate classification of remotely sensed data. In this paper, to classify the data set, various image fusion techniques are used for fusing high resolution Panchromatic data with low resolution Multi-spectral data which gives better quality and more informative image data set. The performances of different fusion techniques are then evaluated to identify the best possible technique which gives better result for image classification. |
| 5. | Publisher | Organizing agency, location | |
| 6. | Contributor | Sponsor(s) | |
| 7. | Date | (YYYY-MM-DD) | 2016-03-14 |
| 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-541 |
| 11. | Source | Journal/conference title; vol., no. (year) | International Journal of Advanced Remote Sensing and GIS; Volume 5 (Year 2016) |
| 12. | Language | English=en | |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
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