| dc.creator | Villalón-Turrubiates, Iván E. | |
| dc.date | 2017-09-15T19:05:28Z | |
| dc.date | 2017-09-15T19:05:28Z | |
| dc.date | 2017-07 | |
| dc.date.accessioned | 2023-07-21T21:58:50Z | |
| dc.date.available | 2023-07-21T21:58:50Z | |
| dc.identifier | Iván E. Villalón-Turrubiates, Identification Model for Large Remote Sensing Datasets Applied to Environmental Analysis within Mexico”, in Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS): International Cooperation for Global Awareness, Fort Worth Texas EE.UU., 2017, pp. 3019-3022. | |
| dc.identifier | 978-1-5090-4951-6 | |
| dc.identifier | http://hdl.handle.net/11117/4956 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/7756613 | |
| dc.description | The classification procedure to identify remote sensing signatures from a particular geographical region can be achieved using an accurate identification model that is based on multispectral data and uses pixel statistics for the class description. This methodology is referred to as the Multispectral Identification Model. This paper presents this particular methodology applied to large remote sensing datasets (multispectral images obtained from the SPOT-5 satellite sensors) with the objective to perform environmental and land use analysis for regions within Mexico, taking advantage of high-performance computing techniques to improve the processing time and computational load. The results obtained uses real multispectral scenes (high- resolution optical images) to probe the efficiency of the classification technique. | |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.publisher | Institute of Electrical and Electronics Engineers | |
| dc.relation | 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS): International Cooperation for Global Awareness; | |
| dc.rights | http://quijote.biblio.iteso.mx/licencias/CC-BY-NC-2.5-MX.pdf | |
| dc.subject | Image Classification | |
| dc.subject | Image Processing | |
| dc.subject | Multispectral | |
| dc.subject | Remote Sensing | |
| dc.title | Identification Model for Large Remote Sensing Datasets Applied to Environmental Analysis within Mexico | |
| dc.type | info:eu-repo/semantics/conferencePaper | |
