Multitemporal fusion of Landsat and MERIS images
Monitoring Earth dynamics from current and future observation satellites is one of the most important objectives for the remote sensing community. In this regard, the exploitation of image time series from sensors with different characteristics provides an opportunity to increase the knowledge about...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2011
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| _version_ | 1797051225104973824 |
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| author | Amorós-López, J Gómez-Chova, L Guanter, L Alonso, L Moreno, J Camps-Vails, G |
| author_facet | Amorós-López, J Gómez-Chova, L Guanter, L Alonso, L Moreno, J Camps-Vails, G |
| author_sort | Amorós-López, J |
| collection | OXFORD |
| description | Monitoring Earth dynamics from current and future observation satellites is one of the most important objectives for the remote sensing community. In this regard, the exploitation of image time series from sensors with different characteristics provides an opportunity to increase the knowledge about environmental changes, which are needed in many operational applications, such as monitoring vegetation dynamics and land cover/use changes. Many studies in the literature have proven that high spatial resolution sensors like Landsat are very useful for monitoring land cover changes. However, the cloud cover probability of many areas and the 15-days temporal resolution restrict its use to monitor rapid variation phenomena. On the contrary, sensors with coarser spatial resolution like MERIS acquire images every 1-3 days. In this paper, Landsat/TM and ENVISAT/MERIS sensors are combined in a synergistic manner to enhance image time series at high spatial resolution using the temporal information provided by the MERIS sensor. The capabilities of the proposed methodology are illustrated using a temporal image series of both sensors acquired over Albacete (Spain) in 2004. Additionally, the temporal profile of the NDVI is selected as demonstrative application of agricultural monitoring. © 2011 IEEE. |
| first_indexed | 2024-03-06T18:16:55Z |
| format | Journal article |
| id | oxford-uuid:04ee40a2-7ce0-4da5-92a2-d1bbc6f25510 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T18:16:55Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | oxford-uuid:04ee40a2-7ce0-4da5-92a2-d1bbc6f255102022-03-26T08:54:23ZMultitemporal fusion of Landsat and MERIS imagesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:04ee40a2-7ce0-4da5-92a2-d1bbc6f25510EnglishSymplectic Elements at Oxford2011Amorós-López, JGómez-Chova, LGuanter, LAlonso, LMoreno, JCamps-Vails, GMonitoring Earth dynamics from current and future observation satellites is one of the most important objectives for the remote sensing community. In this regard, the exploitation of image time series from sensors with different characteristics provides an opportunity to increase the knowledge about environmental changes, which are needed in many operational applications, such as monitoring vegetation dynamics and land cover/use changes. Many studies in the literature have proven that high spatial resolution sensors like Landsat are very useful for monitoring land cover changes. However, the cloud cover probability of many areas and the 15-days temporal resolution restrict its use to monitor rapid variation phenomena. On the contrary, sensors with coarser spatial resolution like MERIS acquire images every 1-3 days. In this paper, Landsat/TM and ENVISAT/MERIS sensors are combined in a synergistic manner to enhance image time series at high spatial resolution using the temporal information provided by the MERIS sensor. The capabilities of the proposed methodology are illustrated using a temporal image series of both sensors acquired over Albacete (Spain) in 2004. Additionally, the temporal profile of the NDVI is selected as demonstrative application of agricultural monitoring. © 2011 IEEE. |
| spellingShingle | Amorós-López, J Gómez-Chova, L Guanter, L Alonso, L Moreno, J Camps-Vails, G Multitemporal fusion of Landsat and MERIS images |
| title | Multitemporal fusion of Landsat and MERIS images |
| title_full | Multitemporal fusion of Landsat and MERIS images |
| title_fullStr | Multitemporal fusion of Landsat and MERIS images |
| title_full_unstemmed | Multitemporal fusion of Landsat and MERIS images |
| title_short | Multitemporal fusion of Landsat and MERIS images |
| title_sort | multitemporal fusion of landsat and meris images |
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