DocumentCode :
3085251
Title :
Multitemporal fusion of Landsat and MERIS images
Author :
Amoros-Lopez, J. ; Gomez-Chova, Luis ; Guanter, L. ; Alonso, Luis ; Moreno, J. ; Camps-Valls, G.
Author_Institution :
Image Process. Lab. (IPL), Univ. of Valencia, Valencia, Spain
fYear :
2011
fDate :
12-14 July 2011
Firstpage :
81
Lastpage :
84
Abstract :
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.
Keywords :
agriculture; geophysical image processing; image fusion; image resolution; image sensors; terrain mapping; time series; vegetation mapping; AD 2004; Albacete; ENVISAT sensor; Earth dynamics; Landsat TM sensor; Landsat multitemporal fusion; MERIS image multitemporal fusion; MERIS sensor; NDVI; Spain; agricultural monitoring method; cloud cover probability; coarser spatial resolution; environmental change analysis; high spatial resolution sensors; image time series; land cover change; land use change; remote sensing community; temporal image series; temporal resolution; vegetation dynamics monitoring; Agriculture; Earth; Remote sensing; Satellites; Sensors; Spatial resolution; Landsat TM; MERIS; Multi-resolution; data fusion; spatial unmixing; sub-pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Analysis of Multi-temporal Remote Sensing Images (Multi-Temp), 2011 6th International Workshop on the
Conference_Location :
Trento
Print_ISBN :
978-1-4577-1202-9
Type :
conf
DOI :
10.1109/Multi-Temp.2011.6005053
Filename :
6005053
Link To Document :
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