期刊
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
卷 23, 期 -, 页码 132-141出版社
ELSEVIER
DOI: 10.1016/j.jag.2012.12.004
关键词
Image fusion; Regularized spatial unmixing; Point-spread function; Multi-temporal NDVI; Crop monitoring
资金
- IGN project
- FP7 project SenSyf
- Spanish Ministry of Economy and Competitiveness (MINECO) [AYA2010-21432-C002-01, TIN2012-38102-C03-01]
Monitoring Earth dynamics using current and future satellites is one of the most important objectives of the remote sensing community. The exploitation of image time series from sensors with different characteristics provides new opportunities to increase the knowledge about environmental changes and to support many operational applications. This paper presents an image fusion approach based on multiresolution and multisensor regularized spatial unmixing. The approach yields a composite image with the spatial resolution of the high spatial resolution image while retaining the spectral and temporal characteristics of the medium spatial resolution image. The approach is tested using images from Landsat/TM and ENVISAT/MERIS instruments, but is general enough to be applied to other sensor pairs. The potential of the proposed spatial unmixing approach is illustrated in an agricultural monitoring application where Landsat temporal profiles from images acquired over Albacete, Spain, in 2004 and 2009 are complemented with MERIS fused images. The resulting spatial resolution from Landsat allows monitoring small and medium size crops at the required scale while the fine spectral and temporal resolution from MERIS allow a more accurate determination of the crop type and phenology as well as capturing rapidly varying land-cover changes. (C) 2012 Elsevier B.V. All rights reserved.
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