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Title: Assessment of spatiotemporal fusion algorithms for planet and worldview images
Authors: Kwan, C
Zhu, XL 
Gao, F
Chou, BY
Perez, D
Li, J
Shen, YZ
Koperski, K
Marchisio, G
Issue Date: 2018
Source: Sensors (Switzerland), Apr. 2018, v. 18, no. 4, 1051
Abstract: Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. These approaches are known as Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal Data Fusion (FSDAF), and Hybrid Color Mapping (HCM), which have been applied to the fusion of MODIS and Landsat images in recent years. Experimental results using actual Planet and Worldview images demonstrated that the three aforementioned approaches have comparable performance and can all generate high quality prediction images.
Keywords: Image fusion
Forward prediction
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Sensors (Switzerland) 
ISSN: 1424-8220
DOI: 10.3390/s18041051
Rights: Copyright © 2018 ZhonghuWu et al. This is an open access article distributed under the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The following publication Kwan, C., Zhu, X., Gao, F., Chou, B., Perez, D., Li, J., . . . Marchisio, G. (2018). Assessment of spatiotemporal fusion algorithms for planet and worldview images. Sensors (Switzerland), 18(4), 1051 is available at
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