Landsat和MERIS图像的多时相融合

J. Amorós-López, L. Gómez-Chova, L. Guanter, L. Alonso, J. Moreno, Gustau Camps-Valls
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引用次数: 1

摘要

利用当前和未来的观测卫星监测地球动力学是遥感界最重要的目标之一。在这方面,利用来自不同特征传感器的图像时间序列提供了一个机会,可以增加对环境变化的了解,这在许多业务应用中都需要,例如监测植被动态和土地覆盖/利用变化。文献中的许多研究已经证明,像Landsat这样的高空间分辨率传感器对于监测土地覆盖变化非常有用。然而,许多地区的云覆盖概率和15天时间分辨率限制了其用于监测快速变化现象。相反,MERIS等空间分辨率较粗的传感器每1-3天采集一次图像。本文将Landsat/TM和ENVISAT/MERIS传感器协同结合,利用MERIS传感器提供的时间信息,在高空间分辨率下增强图像时间序列。采用2004年在西班牙阿尔巴塞特(Albacete)上空获得的两个传感器的时序图像系列说明了所提出方法的能力。此外,选择NDVI的时间剖面作为农业监测的示范应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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.
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