Advances in Classification of Crops using Remote Sensing Data
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Advances in Classification of Crops using Remote Sensing Data |
| 2. | Creator | Author's name, affiliation, country | Rajesh K. Dhumal; Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India |
| 2. | Creator | Author's name, affiliation, country | Amol D. Vibhute; Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India |
| 2. | Creator | Author's name, affiliation, country | Ajay D. Nagne; Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India |
| 2. | Creator | Author's name, affiliation, country | Yogesh D. Rajendra; Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India |
| 2. | Creator | Author's name, affiliation, country | Karbhari V. Kale; Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India |
| 2. | Creator | Author's name, affiliation, country | Suresh C. Mehrotra; Department of Computer Science & IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India |
| 3. | Subject | Discipline(s) | Remote sensing Image interpretation |
| 3. | Subject | Keyword(s) | Spatial Features; Spectral Features; Hyperspectral Data; Crops Classification |
| 3. | Subject | Subject classification | Hyper-spectral image processing |
| 4. | Description | Abstract |
Remote sensing is an efficient technology and worthy source of earth surface information, as it can capture images of reasonably large area on the earth. Due to advancement in the sensor technologies there is availability of high spatial as well as spectral resolutions imageries, and also non imaging Spectroradiometer. With the use of these imaging and non-imaging data we can easily characterize the different species. In this article we have reported work done by worldwide researchers for spatial as well as spectral feature extraction from remote sensing data; specifically we have focused on classification of crops and use narrow band vegetation indices. It may be observed from the report that both spatial resolution and hyperspectral imageries need to be used for better classification. |
| 5. | Publisher | Organizing agency, location | |
| 6. | Contributor | Sponsor(s) | DST- NRDMS Sponcered Sriniwasa Ramanujan Geospatial Chair |
| 7. | Date | (YYYY-MM-DD) | 2015-11-18 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | spatial and spectral features |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | http://technical.cloud-journals.com/index.php/IJARSG/article/view/Tech-483 |
| 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.) | Remote sensing satellite data, Imaging and non Imaging hypersprctral data |
| 15. | Rights | Copyright and permissions |
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